From 41cdc34891c929615c62b3aa93c5142d71dda806 Mon Sep 17 00:00:00 2001 From: =?utf8?q?=EC=9D=B4=EC=B6=98=EC=84=9D/=EB=8F=99=EC=9E=91=EC=A0=9C?= =?utf8?q?=EC=96=B4Lab=28SR=29/Staff=20Engineer/=EC=82=BC=EC=84=B1?= =?utf8?q?=EC=A0=84=EC=9E=90?= Date: Fri, 13 Jul 2018 16:49:45 +0900 Subject: [PATCH] Update nn_android_runtime_test to p-preview-4 (#1935) commit: c73accf066d4f05372 link : https://android.googlesource.com/platform/frameworks/ml/+/android-p-preview-4 cf) all *relaxed* tests are omitted Signed-off-by: Chunseok Lee --- .../generated/all_generated_tests.cpp | 560 ++++++++++++++++++++- .../generated/examples/batch_to_space.example.cpp | 22 + .../examples/batch_to_space_float_1.example.cpp | 22 + .../examples/batch_to_space_quant8_1.example.cpp | 22 + .../generated/examples/div.example.cpp | 22 + .../examples/div_broadcast_float.example.cpp | 22 + .../generated/examples/floor.example.cpp | 22 + .../examples/fully_connected_float_3.example.cpp | 22 + .../fully_connected_float_4d_simple.example.cpp | 22 + .../generated/examples/mean.example.cpp | 22 + .../generated/examples/mean_float_1.example.cpp | 22 + .../generated/examples/mean_float_2.example.cpp | 22 + .../generated/examples/mean_quant8_1.example.cpp | 22 + .../generated/examples/mean_quant8_2.example.cpp | 22 + .../generated/examples/pad.example.cpp | 22 + .../generated/examples/pad_float_1.example.cpp | 22 + .../generated/examples/space_to_batch.example.cpp | 22 + .../examples/space_to_batch_float_1.example.cpp | 22 + .../examples/space_to_batch_float_2.example.cpp | 22 + .../examples/space_to_batch_float_3.example.cpp | 22 + .../examples/space_to_batch_quant8_1.example.cpp | 22 + .../examples/space_to_batch_quant8_2.example.cpp | 22 + .../examples/space_to_batch_quant8_3.example.cpp | 22 + .../generated/examples/squeeze.example.cpp | 22 + .../generated/examples/squeeze_float_1.example.cpp | 22 + .../examples/squeeze_quant8_1.example.cpp | 22 + .../examples/strided_slice_float_11.example.cpp | 22 + .../examples/strided_slice_qaunt8_10.example.cpp | 22 + .../examples/strided_slice_qaunt8_11.example.cpp | 22 + .../examples/strided_slice_quant8_1.example.cpp | 22 + .../examples/strided_slice_quant8_2.example.cpp | 22 + .../examples/strided_slice_quant8_3.example.cpp | 22 + .../examples/strided_slice_quant8_4.example.cpp | 22 + .../examples/strided_slice_quant8_5.example.cpp | 22 + .../examples/strided_slice_quant8_6.example.cpp | 22 + .../examples/strided_slice_quant8_7.example.cpp | 22 + .../examples/strided_slice_quant8_8.example.cpp | 22 + .../examples/strided_slice_quant8_9.example.cpp | 22 + .../examples/sub_broadcast_float.example.cpp | 4 +- .../generated/examples/tanh.example.cpp | 22 + .../generated/examples/transpose.example.cpp | 22 + .../examples/transpose_float_1.example.cpp | 22 + .../examples/transpose_quant8_1.example.cpp | 22 + .../generated/models/batch_to_space.model.cpp | 24 + .../models/batch_to_space_float_1.model.cpp | 24 + .../models/batch_to_space_quant8_1.model.cpp | 24 + .../generated/models/div.model.cpp | 24 + .../generated/models/div_broadcast_float.model.cpp | 25 + .../generated/models/floor.model.cpp | 19 + .../models/fully_connected_float_3.model.cpp | 32 ++ .../fully_connected_float_4d_simple.model.cpp | 32 ++ .../generated/models/mean.model.cpp | 28 ++ .../generated/models/mean_float_1.model.cpp | 28 ++ .../generated/models/mean_float_2.model.cpp | 28 ++ .../generated/models/mean_quant8_1.model.cpp | 28 ++ .../generated/models/mean_quant8_2.model.cpp | 28 ++ .../generated/models/pad.model.cpp | 24 + .../generated/models/pad_float_1.model.cpp | 24 + .../generated/models/space_to_batch.model.cpp | 28 ++ .../models/space_to_batch_float_1.model.cpp | 28 ++ .../models/space_to_batch_float_2.model.cpp | 28 ++ .../models/space_to_batch_float_3.model.cpp | 28 ++ .../models/space_to_batch_quant8_1.model.cpp | 28 ++ .../models/space_to_batch_quant8_2.model.cpp | 28 ++ .../models/space_to_batch_quant8_3.model.cpp | 28 ++ .../generated/models/squeeze.model.cpp | 24 + .../generated/models/squeeze_float_1.model.cpp | 24 + .../generated/models/squeeze_quant8_1.model.cpp | 24 + .../generated/models/strided_slice.model.cpp | 5 +- .../models/strided_slice_float_1.model.cpp | 5 +- .../models/strided_slice_float_10.model.cpp | 5 +- .../models/strided_slice_float_11.model.cpp | 40 ++ .../models/strided_slice_float_2.model.cpp | 5 +- .../models/strided_slice_float_3.model.cpp | 5 +- .../models/strided_slice_float_4.model.cpp | 5 +- .../models/strided_slice_float_5.model.cpp | 5 +- .../models/strided_slice_float_6.model.cpp | 5 +- .../models/strided_slice_float_7.model.cpp | 5 +- .../models/strided_slice_float_8.model.cpp | 5 +- .../models/strided_slice_float_9.model.cpp | 5 +- .../models/strided_slice_qaunt8_10.model.cpp | 40 ++ .../models/strided_slice_qaunt8_11.model.cpp | 40 ++ .../models/strided_slice_quant8_1.model.cpp | 40 ++ .../models/strided_slice_quant8_2.model.cpp | 40 ++ .../models/strided_slice_quant8_3.model.cpp | 40 ++ .../models/strided_slice_quant8_4.model.cpp | 40 ++ .../models/strided_slice_quant8_5.model.cpp | 40 ++ .../models/strided_slice_quant8_6.model.cpp | 40 ++ .../models/strided_slice_quant8_7.model.cpp | 39 ++ .../models/strided_slice_quant8_8.model.cpp | 40 ++ .../models/strided_slice_quant8_9.model.cpp | 40 ++ .../generated/models/sub_broadcast_float.model.cpp | 8 +- .../generated/models/tanh.model.cpp | 19 + .../generated/models/transpose.model.cpp | 23 + .../generated/models/transpose_float_1.model.cpp | 24 + .../generated/models/transpose_quant8_1.model.cpp | 24 + .../specs/Ex/sub_broadcast_float.mod.py | 19 - .../specs/V1_0/fully_connected_float_3.mod.py | 32 ++ .../specs/V1_1/batch_to_space.mod.py | 16 + .../specs/V1_1/batch_to_space_float_1.mod.py | 16 + .../specs/V1_1/batch_to_space_quant8_1.mod.py | 16 + .../specs/V1_1/div_broadcast_float.mod.py | 19 + .../V1_1/fully_connected_float_4d_simple.mod.py | 42 ++ .../neural_networks_test/specs/V1_1/mean.mod.py | 19 + .../specs/V1_1/mean_float_1.mod.py | 18 + .../specs/V1_1/mean_float_2.mod.py | 18 + .../specs/V1_1/mean_quant8_1.mod.py | 19 + .../specs/V1_1/mean_quant8_2.mod.py | 19 + .../neural_networks_test/specs/V1_1/pad.mod.py | 20 + .../specs/V1_1/pad_float_1.mod.py | 18 + .../specs/V1_1/space_to_batch.mod.py | 17 + .../specs/V1_1/space_to_batch_float_1.mod.py | 17 + .../specs/V1_1/space_to_batch_float_2.mod.py | 18 + .../specs/V1_1/space_to_batch_float_3.mod.py | 19 + .../specs/V1_1/space_to_batch_quant8_1.mod.py | 17 + .../specs/V1_1/space_to_batch_quant8_2.mod.py | 18 + .../specs/V1_1/space_to_batch_quant8_3.mod.py | 19 + .../neural_networks_test/specs/V1_1/squeeze.mod.py | 16 + .../specs/V1_1/squeeze_float_1.mod.py | 18 + .../specs/V1_1/squeeze_quant8_1.mod.py | 18 + .../specs/V1_1/strided_slice.mod.py | 3 +- .../specs/V1_1/strided_slice_float_1.mod.py | 3 +- .../specs/V1_1/strided_slice_float_10.mod.py | 3 +- .../specs/V1_1/strided_slice_float_11.mod.py | 22 + .../specs/V1_1/strided_slice_float_2.mod.py | 3 +- .../specs/V1_1/strided_slice_float_3.mod.py | 3 +- .../specs/V1_1/strided_slice_float_4.mod.py | 3 +- .../specs/V1_1/strided_slice_float_5.mod.py | 3 +- .../specs/V1_1/strided_slice_float_6.mod.py | 3 +- .../specs/V1_1/strided_slice_float_7.mod.py | 3 +- .../specs/V1_1/strided_slice_float_8.mod.py | 3 +- .../specs/V1_1/strided_slice_float_9.mod.py | 3 +- .../specs/V1_1/strided_slice_qaunt8_10.mod.py | 22 + .../specs/V1_1/strided_slice_qaunt8_11.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_1.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_2.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_3.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_4.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_5.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_6.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_7.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_8.mod.py | 22 + .../specs/V1_1/strided_slice_quant8_9.mod.py | 22 + .../specs/V1_1/sub_broadcast_float.mod.py | 19 + .../specs/V1_1/transpose.mod.py | 18 + .../specs/V1_1/transpose_float_1.mod.py | 32 ++ .../specs/V1_1/transpose_quant8_1.mod.py | 32 ++ 147 files changed, 3563 insertions(+), 61 deletions(-) create mode 100644 runtimes/tests/neural_networks_test/generated/examples/batch_to_space.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/batch_to_space_float_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/batch_to_space_quant8_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/div.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/div_broadcast_float.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/floor.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_3.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_4d_simple.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/mean.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/mean_float_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/mean_float_2.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/mean_quant8_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/mean_quant8_2.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/pad.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/pad_float_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/space_to_batch.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_2.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_3.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_2.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_3.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/squeeze.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/squeeze_float_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/squeeze_quant8_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_11.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_10.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_11.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_2.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_3.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_4.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_5.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_6.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_7.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_8.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_9.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/tanh.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/transpose.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/transpose_float_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/examples/transpose_quant8_1.example.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/div.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/floor.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/mean.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/pad.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp create mode 100644 runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp create mode 100644 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create mode 100644 runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp delete mode 100644 runtimes/tests/neural_networks_test/specs/Ex/sub_broadcast_float.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_0/fully_connected_float_3.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space_float_1.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space_quant8_1.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/div_broadcast_float.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/fully_connected_float_4d_simple.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/mean.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/mean_float_1.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/mean_float_2.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/mean_quant8_1.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/mean_quant8_2.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/pad.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/pad_float_1.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_1.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_2.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_3.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_1.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_2.mod.py create mode 100644 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runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_4.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_5.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_6.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_7.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_8.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_9.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/sub_broadcast_float.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/transpose.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/transpose_float_1.mod.py create mode 100644 runtimes/tests/neural_networks_test/specs/V1_1/transpose_quant8_1.mod.py diff --git a/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp b/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp index 798d8f1..f20216a 100644 --- a/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp +++ b/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp @@ -855,6 +855,20 @@ TEST_F(GeneratedTests, fully_connected_float_2) { fully_connected_float_2::examples); } +namespace fully_connected_float_3 { +std::vector examples = { +// Generated fully_connected_float_3 test +#include "generated/examples/fully_connected_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/fully_connected_float_3.model.cpp" +} // namespace fully_connected_float_3 +TEST_F(GeneratedTests, fully_connected_float_3) { + execute(fully_connected_float_3::CreateModel, + fully_connected_float_3::is_ignored, + fully_connected_float_3::examples); +} + namespace fully_connected_float_large { std::vector examples = { // Generated fully_connected_float_large test @@ -2045,6 +2059,62 @@ TEST_F(GeneratedTests, tanh_) { tanh_::examples); } +namespace batch_to_space_float_1 { +std::vector examples = { +// Generated batch_to_space_float_1 test +#include "generated/examples/batch_to_space_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/batch_to_space_float_1.model.cpp" +} // namespace batch_to_space_float_1 +TEST_F(GeneratedTests, batch_to_space_float_1) { + execute(batch_to_space_float_1::CreateModel, + batch_to_space_float_1::is_ignored, + batch_to_space_float_1::examples); +} + +namespace batch_to_space { +std::vector examples = { +// Generated batch_to_space test +#include "generated/examples/batch_to_space.example.cpp" +}; +// Generated model constructor +#include "generated/models/batch_to_space.model.cpp" +} // namespace batch_to_space +TEST_F(GeneratedTests, batch_to_space) { + execute(batch_to_space::CreateModel, + batch_to_space::is_ignored, + batch_to_space::examples); +} + +namespace batch_to_space_quant8_1 { +std::vector examples = { +// Generated batch_to_space_quant8_1 test +#include "generated/examples/batch_to_space_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/batch_to_space_quant8_1.model.cpp" +} // namespace batch_to_space_quant8_1 +TEST_F(GeneratedTests, batch_to_space_quant8_1) { + execute(batch_to_space_quant8_1::CreateModel, + batch_to_space_quant8_1::is_ignored, + batch_to_space_quant8_1::examples); +} + +namespace div_broadcast_float { +std::vector examples = { +// Generated div_broadcast_float test +#include "generated/examples/div_broadcast_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/div_broadcast_float.model.cpp" +} // namespace div_broadcast_float +TEST_F(GeneratedTests, div_broadcast_float) { + execute(div_broadcast_float::CreateModel, + div_broadcast_float::is_ignored, + div_broadcast_float::examples); +} + namespace div_ { std::vector examples = { // Generated div_ test @@ -2059,6 +2129,258 @@ TEST_F(GeneratedTests, div_) { div_::examples); } +namespace fully_connected_float_4d_simple { +std::vector examples = { +// Generated fully_connected_float_4d_simple test +#include "generated/examples/fully_connected_float_4d_simple.example.cpp" +}; +// Generated model constructor +#include "generated/models/fully_connected_float_4d_simple.model.cpp" +} // namespace fully_connected_float_4d_simple +TEST_F(GeneratedTests, fully_connected_float_4d_simple) { + execute(fully_connected_float_4d_simple::CreateModel, + fully_connected_float_4d_simple::is_ignored, + fully_connected_float_4d_simple::examples); +} + +namespace mean_float_1 { +std::vector examples = { +// Generated mean_float_1 test +#include "generated/examples/mean_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_float_1.model.cpp" +} // namespace mean_float_1 +TEST_F(GeneratedTests, mean_float_1) { + execute(mean_float_1::CreateModel, + mean_float_1::is_ignored, + mean_float_1::examples); +} + +namespace mean_float_2 { +std::vector examples = { +// Generated mean_float_2 test +#include "generated/examples/mean_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_float_2.model.cpp" +} // namespace mean_float_2 +TEST_F(GeneratedTests, mean_float_2) { + execute(mean_float_2::CreateModel, + mean_float_2::is_ignored, + mean_float_2::examples); +} + +namespace mean { +std::vector examples = { +// Generated mean test +#include "generated/examples/mean.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean.model.cpp" +} // namespace mean +TEST_F(GeneratedTests, mean) { + execute(mean::CreateModel, + mean::is_ignored, + mean::examples); +} + +namespace mean_quant8_1 { +std::vector examples = { +// Generated mean_quant8_1 test +#include "generated/examples/mean_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_quant8_1.model.cpp" +} // namespace mean_quant8_1 +TEST_F(GeneratedTests, mean_quant8_1) { + execute(mean_quant8_1::CreateModel, + mean_quant8_1::is_ignored, + mean_quant8_1::examples); +} + +namespace mean_quant8_2 { +std::vector examples = { +// Generated mean_quant8_2 test +#include "generated/examples/mean_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_quant8_2.model.cpp" +} // namespace mean_quant8_2 +TEST_F(GeneratedTests, mean_quant8_2) { + execute(mean_quant8_2::CreateModel, + mean_quant8_2::is_ignored, + mean_quant8_2::examples); +} + +namespace pad_float_1 { +std::vector examples = { +// Generated pad_float_1 test +#include "generated/examples/pad_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/pad_float_1.model.cpp" +} // namespace pad_float_1 +TEST_F(GeneratedTests, pad_float_1) { + execute(pad_float_1::CreateModel, + pad_float_1::is_ignored, + pad_float_1::examples); +} + +namespace pad { +std::vector examples = { +// Generated pad test +#include "generated/examples/pad.example.cpp" +}; +// Generated model constructor +#include "generated/models/pad.model.cpp" +} // namespace pad +TEST_F(GeneratedTests, pad) { + execute(pad::CreateModel, + pad::is_ignored, + pad::examples); +} + +namespace space_to_batch_float_1 { +std::vector examples = { +// Generated space_to_batch_float_1 test +#include "generated/examples/space_to_batch_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_float_1.model.cpp" +} // namespace space_to_batch_float_1 +TEST_F(GeneratedTests, space_to_batch_float_1) { + execute(space_to_batch_float_1::CreateModel, + space_to_batch_float_1::is_ignored, + space_to_batch_float_1::examples); +} + +namespace space_to_batch_float_2 { +std::vector examples = { +// Generated space_to_batch_float_2 test +#include "generated/examples/space_to_batch_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_float_2.model.cpp" +} // namespace space_to_batch_float_2 +TEST_F(GeneratedTests, space_to_batch_float_2) { + execute(space_to_batch_float_2::CreateModel, + space_to_batch_float_2::is_ignored, + space_to_batch_float_2::examples); +} + +namespace space_to_batch_float_3 { +std::vector examples = { +// Generated space_to_batch_float_3 test +#include "generated/examples/space_to_batch_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_float_3.model.cpp" +} // namespace space_to_batch_float_3 +TEST_F(GeneratedTests, space_to_batch_float_3) { + execute(space_to_batch_float_3::CreateModel, + space_to_batch_float_3::is_ignored, + space_to_batch_float_3::examples); +} + +namespace space_to_batch { +std::vector examples = { +// Generated space_to_batch test +#include "generated/examples/space_to_batch.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch.model.cpp" +} // namespace space_to_batch +TEST_F(GeneratedTests, space_to_batch) { + execute(space_to_batch::CreateModel, + space_to_batch::is_ignored, + space_to_batch::examples); +} + +namespace space_to_batch_quant8_1 { +std::vector examples = { +// Generated space_to_batch_quant8_1 test +#include "generated/examples/space_to_batch_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_quant8_1.model.cpp" +} // namespace space_to_batch_quant8_1 +TEST_F(GeneratedTests, space_to_batch_quant8_1) { + execute(space_to_batch_quant8_1::CreateModel, + space_to_batch_quant8_1::is_ignored, + space_to_batch_quant8_1::examples); +} + +namespace space_to_batch_quant8_2 { +std::vector examples = { +// Generated space_to_batch_quant8_2 test +#include "generated/examples/space_to_batch_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_quant8_2.model.cpp" +} // namespace space_to_batch_quant8_2 +TEST_F(GeneratedTests, space_to_batch_quant8_2) { + execute(space_to_batch_quant8_2::CreateModel, + space_to_batch_quant8_2::is_ignored, + space_to_batch_quant8_2::examples); +} + +namespace space_to_batch_quant8_3 { +std::vector examples = { +// Generated space_to_batch_quant8_3 test +#include "generated/examples/space_to_batch_quant8_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_quant8_3.model.cpp" +} // namespace space_to_batch_quant8_3 +TEST_F(GeneratedTests, space_to_batch_quant8_3) { + execute(space_to_batch_quant8_3::CreateModel, + space_to_batch_quant8_3::is_ignored, + space_to_batch_quant8_3::examples); +} + +namespace squeeze_float_1 { +std::vector examples = { +// Generated squeeze_float_1 test +#include "generated/examples/squeeze_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/squeeze_float_1.model.cpp" +} // namespace squeeze_float_1 +TEST_F(GeneratedTests, squeeze_float_1) { + execute(squeeze_float_1::CreateModel, + squeeze_float_1::is_ignored, + squeeze_float_1::examples); +} + +namespace squeeze { +std::vector examples = { +// Generated squeeze test +#include "generated/examples/squeeze.example.cpp" +}; +// Generated model constructor +#include "generated/models/squeeze.model.cpp" +} // namespace squeeze +TEST_F(GeneratedTests, squeeze) { + execute(squeeze::CreateModel, + squeeze::is_ignored, + squeeze::examples); +} + +namespace squeeze_quant8_1 { +std::vector examples = { +// Generated squeeze_quant8_1 test +#include "generated/examples/squeeze_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/squeeze_quant8_1.model.cpp" +} // namespace squeeze_quant8_1 +TEST_F(GeneratedTests, squeeze_quant8_1) { + execute(squeeze_quant8_1::CreateModel, + squeeze_quant8_1::is_ignored, + squeeze_quant8_1::examples); +} + namespace strided_slice_float_10 { std::vector examples = { // Generated strided_slice_float_10 test @@ -2073,6 +2395,20 @@ TEST_F(GeneratedTests, strided_slice_float_10) { strided_slice_float_10::examples); } +namespace strided_slice_float_11 { +std::vector examples = { +// Generated strided_slice_float_11 test +#include "generated/examples/strided_slice_float_11.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_11.model.cpp" +} // namespace strided_slice_float_11 +TEST_F(GeneratedTests, strided_slice_float_11) { + execute(strided_slice_float_11::CreateModel, + strided_slice_float_11::is_ignored, + strided_slice_float_11::examples); +} + namespace strided_slice_float_1 { std::vector examples = { // Generated strided_slice_float_1 test @@ -2213,6 +2549,174 @@ TEST_F(GeneratedTests, strided_slice) { strided_slice::examples); } +namespace strided_slice_qaunt8_10 { +std::vector examples = { +// Generated strided_slice_qaunt8_10 test +#include "generated/examples/strided_slice_qaunt8_10.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_qaunt8_10.model.cpp" +} // namespace strided_slice_qaunt8_10 +TEST_F(GeneratedTests, strided_slice_qaunt8_10) { + execute(strided_slice_qaunt8_10::CreateModel, + strided_slice_qaunt8_10::is_ignored, + strided_slice_qaunt8_10::examples); +} + +namespace strided_slice_qaunt8_11 { +std::vector examples = { +// Generated strided_slice_qaunt8_11 test +#include "generated/examples/strided_slice_qaunt8_11.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_qaunt8_11.model.cpp" +} // namespace strided_slice_qaunt8_11 +TEST_F(GeneratedTests, strided_slice_qaunt8_11) { + execute(strided_slice_qaunt8_11::CreateModel, + strided_slice_qaunt8_11::is_ignored, + strided_slice_qaunt8_11::examples); +} + +namespace strided_slice_quant8_1 { +std::vector examples = { +// Generated strided_slice_quant8_1 test +#include "generated/examples/strided_slice_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_1.model.cpp" +} // namespace strided_slice_quant8_1 +TEST_F(GeneratedTests, strided_slice_quant8_1) { + execute(strided_slice_quant8_1::CreateModel, + strided_slice_quant8_1::is_ignored, + strided_slice_quant8_1::examples); +} + +namespace strided_slice_quant8_2 { +std::vector examples = { +// Generated strided_slice_quant8_2 test +#include "generated/examples/strided_slice_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_2.model.cpp" +} // namespace strided_slice_quant8_2 +TEST_F(GeneratedTests, strided_slice_quant8_2) { + execute(strided_slice_quant8_2::CreateModel, + strided_slice_quant8_2::is_ignored, + strided_slice_quant8_2::examples); +} + +namespace strided_slice_quant8_3 { +std::vector examples = { +// Generated strided_slice_quant8_3 test +#include "generated/examples/strided_slice_quant8_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_3.model.cpp" +} // namespace strided_slice_quant8_3 +TEST_F(GeneratedTests, strided_slice_quant8_3) { + execute(strided_slice_quant8_3::CreateModel, + strided_slice_quant8_3::is_ignored, + strided_slice_quant8_3::examples); +} + +namespace strided_slice_quant8_4 { +std::vector examples = { +// Generated strided_slice_quant8_4 test +#include "generated/examples/strided_slice_quant8_4.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_4.model.cpp" +} // namespace strided_slice_quant8_4 +TEST_F(GeneratedTests, strided_slice_quant8_4) { + execute(strided_slice_quant8_4::CreateModel, + strided_slice_quant8_4::is_ignored, + strided_slice_quant8_4::examples); +} + +namespace strided_slice_quant8_5 { +std::vector examples = { +// Generated strided_slice_quant8_5 test +#include "generated/examples/strided_slice_quant8_5.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_5.model.cpp" +} // namespace strided_slice_quant8_5 +TEST_F(GeneratedTests, strided_slice_quant8_5) { + execute(strided_slice_quant8_5::CreateModel, + strided_slice_quant8_5::is_ignored, + strided_slice_quant8_5::examples); +} + +namespace strided_slice_quant8_6 { +std::vector examples = { +// Generated strided_slice_quant8_6 test +#include "generated/examples/strided_slice_quant8_6.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_6.model.cpp" +} // namespace strided_slice_quant8_6 +TEST_F(GeneratedTests, strided_slice_quant8_6) { + execute(strided_slice_quant8_6::CreateModel, + strided_slice_quant8_6::is_ignored, + strided_slice_quant8_6::examples); +} + +namespace strided_slice_quant8_7 { +std::vector examples = { +// Generated strided_slice_quant8_7 test +#include "generated/examples/strided_slice_quant8_7.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_7.model.cpp" +} // namespace strided_slice_quant8_7 +TEST_F(GeneratedTests, strided_slice_quant8_7) { + execute(strided_slice_quant8_7::CreateModel, + strided_slice_quant8_7::is_ignored, + strided_slice_quant8_7::examples); +} + +namespace strided_slice_quant8_8 { +std::vector examples = { +// Generated strided_slice_quant8_8 test +#include "generated/examples/strided_slice_quant8_8.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_8.model.cpp" +} // namespace strided_slice_quant8_8 +TEST_F(GeneratedTests, strided_slice_quant8_8) { + execute(strided_slice_quant8_8::CreateModel, + strided_slice_quant8_8::is_ignored, + strided_slice_quant8_8::examples); +} + +namespace strided_slice_quant8_9 { +std::vector examples = { +// Generated strided_slice_quant8_9 test +#include "generated/examples/strided_slice_quant8_9.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_9.model.cpp" +} // namespace strided_slice_quant8_9 +TEST_F(GeneratedTests, strided_slice_quant8_9) { + execute(strided_slice_quant8_9::CreateModel, + strided_slice_quant8_9::is_ignored, + strided_slice_quant8_9::examples); +} + +namespace sub_broadcast_float { +std::vector examples = { +// Generated sub_broadcast_float test +#include "generated/examples/sub_broadcast_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/sub_broadcast_float.model.cpp" +} // namespace sub_broadcast_float +TEST_F(GeneratedTests, sub_broadcast_float) { + execute(sub_broadcast_float::CreateModel, + sub_broadcast_float::is_ignored, + sub_broadcast_float::examples); +} + namespace sub { std::vector examples = { // Generated sub test @@ -2227,6 +2731,48 @@ TEST_F(GeneratedTests, sub) { sub::examples); } +namespace transpose_float_1 { +std::vector examples = { +// Generated transpose_float_1 test +#include "generated/examples/transpose_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/transpose_float_1.model.cpp" +} // namespace transpose_float_1 +TEST_F(GeneratedTests, transpose_float_1) { + execute(transpose_float_1::CreateModel, + transpose_float_1::is_ignored, + transpose_float_1::examples); +} + +namespace transpose { +std::vector examples = { +// Generated transpose test +#include "generated/examples/transpose.example.cpp" +}; +// Generated model constructor +#include "generated/models/transpose.model.cpp" +} // namespace transpose +TEST_F(GeneratedTests, transpose) { + execute(transpose::CreateModel, + transpose::is_ignored, + transpose::examples); +} + +namespace transpose_quant8_1 { +std::vector examples = { +// Generated transpose_quant8_1 test +#include "generated/examples/transpose_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/transpose_quant8_1.model.cpp" +} // namespace transpose_quant8_1 +TEST_F(GeneratedTests, transpose_quant8_1) { + execute(transpose_quant8_1::CreateModel, + transpose_quant8_1::is_ignored, + transpose_quant8_1::examples); +} + namespace cast_ex_float32_to_int32 { std::vector examples = { // Generated cast_ex_float32_to_int32 test @@ -2479,20 +3025,6 @@ TEST_F(GeneratedTests, strided_slice_ex_float_9) { strided_slice_ex_float_9::examples); } -namespace sub_broadcast_float { -std::vector examples = { -// Generated sub_broadcast_float test -#include "generated/examples/sub_broadcast_float.example.cpp" -}; -// Generated model constructor -#include "generated/models/sub_broadcast_float.model.cpp" -} // namespace sub_broadcast_float -TEST_F(GeneratedTests, sub_broadcast_float) { - execute(sub_broadcast_float::CreateModel, - sub_broadcast_float::is_ignored, - sub_broadcast_float::examples); -} - namespace tensorflowmax_ex_2D_float { std::vector examples = { // Generated tensorflowmax_ex_2D_float test diff --git a/runtimes/tests/neural_networks_test/generated/examples/batch_to_space.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space.example.cpp new file mode 100644 index 0000000..1113262 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: batch_to_space.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_float_1.example.cpp new file mode 100644 index 0000000..45a7580 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: batch_to_space_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_quant8_1.example.cpp new file mode 100644 index 0000000..6d1d6f7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: batch_to_space_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/div.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/div.example.cpp new file mode 100644 index 0000000..23ad4b0 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/div.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: div.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2.0f, -4.0f, 8.0f, -16.0f}}, {1, {2.0f, -2.0f, -4.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, -2.0f, -4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/div_broadcast_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/div_broadcast_float.example.cpp new file mode 100644 index 0000000..ccbb571 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/div_broadcast_float.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: div_broadcast_float.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2}}, {1, {1, 1, 2, 2}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 0.5f, 1}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/floor.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/floor.example.cpp new file mode 100644 index 0000000..f15d984 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/floor.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: floor.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-1.5f, -1.0f, -0.5f, 0.0f, 0.5f, 1.0f, 1.5f, 10.2f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-2.0f, -1.0f, -1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_3.example.cpp new file mode 100644 index 0000000..14ee46d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: fully_connected_float_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 2, 1}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {11, 9}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_4d_simple.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_4d_simple.example.cpp new file mode 100644 index 0000000..4086bc5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_4d_simple.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: fully_connected_float_4d_simple.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, -9, -10, 1, 2, 3, 4, 5, 6, 7, -8, 9, -10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {24, 25, 26, 58, 59, 60}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean.example.cpp new file mode 100644 index 0000000..27b8258 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.5f, 3.5f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_float_1.example.cpp new file mode 100644 index 0000000..4c53d77 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {12.0f, 13.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_float_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_float_2.example.cpp new file mode 100644 index 0000000..844dd2a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_float_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_float_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {10.5f, 12.5f, 14.5f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_1.example.cpp new file mode 100644 index 0000000..652c847 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {12, 13}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_2.example.cpp new file mode 100644 index 0000000..56dec24 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_quant8_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {10, 12, 14}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/pad.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/pad.example.cpp new file mode 100644 index 0000000..dbec433 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/pad.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: pad.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 2.0f, 0.0f, 0.0f, 3.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/pad_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/pad_float_1.example.cpp new file mode 100644 index 0000000..873149b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/pad_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: pad_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch.example.cpp new file mode 100644 index 0000000..e226e36 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_1.example.cpp new file mode 100644 index 0000000..06d0ff3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 3, 9, 11, 2, 4, 10, 12, 5, 7, 13, 15, 6, 8, 14, 16}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_2.example.cpp new file mode 100644 index 0000000..a7b0010 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_float_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 0, 0, 5, 0, 0, 0, 6, 0, 1, 0, 7, 0, 2, 0, 8, 0, 3, 0, 9, 0, 4, 0, 10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_3.example.cpp new file mode 100644 index 0000000..5198bae --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_float_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 1, 0, 0, 0, 7, 0, 0, 0, 2, 0, 0, 0, 8, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_1.example.cpp new file mode 100644 index 0000000..1c86710 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 3, 9, 11, 2, 4, 10, 12, 5, 7, 13, 15, 6, 8, 14, 16}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_2.example.cpp new file mode 100644 index 0000000..4e615d0 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_quant8_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {0, 0, 0, 5, 0, 0, 0, 6, 0, 1, 0, 7, 0, 2, 0, 8, 0, 3, 0, 9, 0, 4, 0, 10}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_3.example.cpp new file mode 100644 index 0000000..13745ac --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_quant8_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 1, 0, 0, 0, 7, 0, 0, 0, 2, 0, 0, 0, 8, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/squeeze.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/squeeze.example.cpp new file mode 100644 index 0000000..bcbc54f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/squeeze.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: squeeze.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/squeeze_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/squeeze_float_1.example.cpp new file mode 100644 index 0000000..2616d65 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/squeeze_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: squeeze_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/squeeze_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/squeeze_quant8_1.example.cpp new file mode 100644 index 0000000..53bb0a8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/squeeze_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: squeeze_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_11.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_11.example.cpp new file mode 100644 index 0000000..19bb573 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_11.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_11.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_10.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_10.example.cpp new file mode 100644 index 0000000..091aa06 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_10.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_qaunt8_10.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {4, 5, 6}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_11.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_11.example.cpp new file mode 100644 index 0000000..8e8c23e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_11.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_qaunt8_11.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_1.example.cpp new file mode 100644 index 0000000..6eb2d95 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_2.example.cpp new file mode 100644 index 0000000..481fe2e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_3.example.cpp new file mode 100644 index 0000000..a68e882 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_4.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_4.example.cpp new file mode 100644 index 0000000..aa486a4 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_4.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_4.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {2}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_5.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_5.example.cpp new file mode 100644 index 0000000..db84580 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_5.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_5.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_6.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_6.example.cpp new file mode 100644 index 0000000..232e8c4 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_6.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_6.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {2, 3, 4}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_7.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_7.example.cpp new file mode 100644 index 0000000..86f32fe --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_7.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_7.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {3, 2, 1}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_8.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_8.example.cpp new file mode 100644 index 0000000..fe5026d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_8.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_8.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {6, 5, 4}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_9.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_9.example.cpp new file mode 100644 index 0000000..dd590e4 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_9.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_9.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 4, 5}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/sub_broadcast_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/sub_broadcast_float.example.cpp index f11c66d..4888c76 100644 --- a/runtimes/tests/neural_networks_test/generated/examples/sub_broadcast_float.example.cpp +++ b/runtimes/tests/neural_networks_test/generated/examples/sub_broadcast_float.example.cpp @@ -4,7 +4,7 @@ //Input(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map - {{0, {1, 2, 3, 4}}, {1, {2}}}, + {{0, {1, 2}}, {1, {1, 2, 3, 4}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map @@ -13,7 +13,7 @@ //Output(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map - {{0, {-1, 0, 1, 2}}}, + {{0, {0, 0, -2, -2}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map diff --git a/runtimes/tests/neural_networks_test/generated/examples/tanh.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/tanh.example.cpp new file mode 100644 index 0000000..5c12ca0 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/tanh.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: tanh.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-1, 0, 1, 10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-0.761594156f, 0, 0.761594156f, 0.999999996f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/transpose.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/transpose.example.cpp new file mode 100644 index 0000000..790923c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/transpose.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: transpose.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 3.0f, 2.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/transpose_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/transpose_float_1.example.cpp new file mode 100644 index 0000000..31f6799 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/transpose_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: transpose_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 1, 2, 3, 4, 20, 21, 22, 23, 24, 40, 41, 42, 43, 44, 60, 61, 62, 63, 64, 80, 81, 82, 83, 84, 100, 101, 102, 103, 104, 5, 6, 7, 8, 9, 25, 26, 27, 28, 29, 45, 46, 47, 48, 49, 65, 66, 67, 68, 69, 85, 86, 87, 88, 89, 105, 106, 107, 108, 109, 10, 11, 12, 13, 14, 30, 31, 32, 33, 34, 50, 51, 52, 53, 54, 70, 71, 72, 73, 74, 90, 91, 92, 93, 94, 110, 111, 112, 113, 114, 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 55, 56, 57, 58, 59, 75, 76, 77, 78, 79, 95, 96, 97, 98, 99, 115, 116, 117, 118, 119}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/transpose_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/transpose_quant8_1.example.cpp new file mode 100644 index 0000000..f1bb2fa --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/transpose_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: transpose_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {0, 1, 2, 3, 4, 20, 21, 22, 23, 24, 40, 41, 42, 43, 44, 60, 61, 62, 63, 64, 80, 81, 82, 83, 84, 100, 101, 102, 103, 104, 5, 6, 7, 8, 9, 25, 26, 27, 28, 29, 45, 46, 47, 48, 49, 65, 66, 67, 68, 69, 85, 86, 87, 88, 89, 105, 106, 107, 108, 109, 10, 11, 12, 13, 14, 30, 31, 32, 33, 34, 50, 51, 52, 53, 54, 70, 71, 72, 73, 74, 90, 91, 92, 93, 94, 110, 111, 112, 113, 114, 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 55, 56, 57, 58, 59, 75, 76, 77, 78, 79, 95, 96, 97, 98, 99, 115, 116, 117, 118, 119}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp new file mode 100644 index 0000000..6c6d590 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp new file mode 100644 index 0000000..e074783 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp new file mode 100644 index 0000000..8922740 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 4, 4, 1}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/div.model.cpp b/runtimes/tests/neural_networks_test/generated/models/div.model.cpp new file mode 100644 index 0000000..31213de --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/div.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: div.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto act = model->addOperand(&type1); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp new file mode 100644 index 0000000..e6f442d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: div_broadcast_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type1(Type::TENSOR_FLOAT32, {2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type1); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/floor.model.cpp b/runtimes/tests/neural_networks_test/generated/models/floor.model.cpp new file mode 100644 index 0000000..2425f47 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/floor.model.cpp @@ -0,0 +1,19 @@ +// Generated file (from: floor.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_FLOOR, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp new file mode 100644 index 0000000..1527525 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp @@ -0,0 +1,32 @@ +// Generated file (from: fully_connected_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type4(Type::INT32, {}); + OperandType type1(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {1}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto b0 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + auto act = model->addOperand(&type4); + // Phase 2, operations + static float op2_init[] = {2.0f, 4.0f}; + model->setOperandValue(op2, op2_init, sizeof(float) * 2); + static float b0_init[] = {1.0f}; + model->setOperandValue(b0, b0_init, sizeof(float) * 1); + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp new file mode 100644 index 0000000..aa645d9 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp @@ -0,0 +1,32 @@ +// Generated file (from: fully_connected_float_4d_simple.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type4(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_FLOAT32, {3, 10}); + OperandType type2(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 5, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto b0 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + auto act = model->addOperand(&type4); + // Phase 2, operations + static float op2_init[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f}; + model->setOperandValue(op2, op2_init, sizeof(float) * 30); + static float b0_init[] = {1.0f, 2.0f, 3.0f}; + model->setOperandValue(b0, b0_init, sizeof(float) * 3); + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp new file mode 100644 index 0000000..7d26f9f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 2, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp new file mode 100644 index 0000000..7a3ce25 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 0, -3, -3}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp new file mode 100644 index 0000000..9838db4 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0, 2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp new file mode 100644 index 0000000..bbc6c10 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {4}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 0.8, 5); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 3, 2}, 0.8, 5); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 0, -3, -3}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp new file mode 100644 index 0000000..dec9d81 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3, 1}, 0.8, 5); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 3, 2}, 0.8, 5); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0, 2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp b/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp new file mode 100644 index 0000000..97e173e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: pad.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type1(Type::TENSOR_INT32, {4, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t op2_init[] = {0, 0, 1, 1, 1, 1, 0, 0}; + model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8); + model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp new file mode 100644 index 0000000..61ae0b7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: pad_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 7, 1}); + OperandType type1(Type::TENSOR_INT32, {4, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t op2_init[] = {0, 0, 0, 2, 1, 3, 0, 0}; + model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8); + model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp new file mode 100644 index 0000000..4064c94 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + OperandType type3(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp new file mode 100644 index 0000000..f4dfab9 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {4, 2, 2, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp new file mode 100644 index 0000000..44dee00 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 5, 2, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {6, 2, 2, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 0, 2, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp new file mode 100644 index 0000000..f2fa990 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 2, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {6, 2, 4, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 1, 2, 4}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp new file mode 100644 index 0000000..cfd56c2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 4, 4, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {4, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp new file mode 100644 index 0000000..8ab61a1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 5, 2, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {6, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 0, 2, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp new file mode 100644 index 0000000..7ee3884 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 4, 2, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {6, 2, 4, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 1, 2, 4}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp new file mode 100644 index 0000000..806a10c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {4, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {1, 2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp new file mode 100644 index 0000000..2277e38 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 24, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 24}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp new file mode 100644 index 0000000..f122d43 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 24, 1}, 1.0, 0); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 24}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp index 371d084..5f1b875 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {0, 0}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp index d37e8e6..fcd2f6d 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {1}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp index 6fecfd3..1463f13 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {1, 0}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {2}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp new file mode 100644 index 0000000..2197b50 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_11.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {0, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {1, 3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {1}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp index 81e8796..47179ca 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {-3}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp index 343455a..113c775 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {-5}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp index b7524de..af5ffa8 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {1}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp index a590fc5..a0280d3 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {1}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp index db1de2b..cb40c85 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {1}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {1}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp index d4d12e9..1580128 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp @@ -10,6 +10,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type0); // Phase 2, operations static int32_t begins_init[] = {-1}; @@ -22,7 +23,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp index 30c96b5..0dd3884 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {1, -1}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp index a93a1f8..22e0e70 100644 --- a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp @@ -11,6 +11,7 @@ void CreateModel(Model *model) { auto strides = model->addOperand(&type1); auto beginMask = model->addOperand(&type2); auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); auto output = model->addOperand(&type3); // Phase 2, operations static int32_t begins_init[] = {1, 0}; @@ -23,7 +24,9 @@ void CreateModel(Model *model) { model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); static int32_t endMask_init[] = {0}; model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask}, {output}); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input}, diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp new file mode 100644 index 0000000..a6eec78 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_qaunt8_10.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {2}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp new file mode 100644 index 0000000..170dc7e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_qaunt8_11.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {0, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {1, 3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {1}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp new file mode 100644 index 0000000..7f8e602 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp new file mode 100644 index 0000000..e604214 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-3}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp new file mode 100644 index 0000000..2cc75a4 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-5}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp new file mode 100644 index 0000000..2fe2277 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_4.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp new file mode 100644 index 0000000..1ed3ed1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_5.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp new file mode 100644 index 0000000..73da2fc --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_6.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {1}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp new file mode 100644 index 0000000..089388b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp @@ -0,0 +1,39 @@ +// Generated file (from: strided_slice_quant8_7.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t begins_init[] = {-1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {-1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp new file mode 100644 index 0000000..ef55fc1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, -1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, -4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, -1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp new file mode 100644 index 0000000..37bb289 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_9.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp index f48feaf..cf1f61a 100644 --- a/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp @@ -1,17 +1,17 @@ // Generated file (from: sub_broadcast_float.mod.py). Do not edit void CreateModel(Model *model) { OperandType type2(Type::INT32, {}); - OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); - OperandType type1(Type::TENSOR_FLOAT32, {1}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type1(Type::TENSOR_FLOAT32, {2, 2}); // Phase 1, operands auto op1 = model->addOperand(&type0); auto op2 = model->addOperand(&type1); auto act = model->addOperand(&type2); - auto op3 = model->addOperand(&type0); + auto op3 = model->addOperand(&type1); // Phase 2, operations static int32_t act_init[] = {0}; model->setOperandValue(act, act_init, sizeof(int32_t) * 1); - model->addOperationEx(ANEURALNETWORKS_SUB_EX, {op1, op2, act}, {op3}); + model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {op1, op2}, diff --git a/runtimes/tests/neural_networks_test/generated/models/tanh.model.cpp b/runtimes/tests/neural_networks_test/generated/models/tanh.model.cpp new file mode 100644 index 0000000..bc3cd4a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/tanh.model.cpp @@ -0,0 +1,19 @@ +// Generated file (from: tanh.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_TANH, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp new file mode 100644 index 0000000..e4c7414 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp @@ -0,0 +1,23 @@ +// Generated file (from: transpose.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t perms_init[] = {0, 2, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp new file mode 100644 index 0000000..f6d0d08 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: transpose_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {2, 3, 4, 5}); + OperandType type2(Type::TENSOR_FLOAT32, {4, 2, 3, 5}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t perms_init[] = {2, 0, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp new file mode 100644 index 0000000..808ad2b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: transpose_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {4}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3, 4, 5}, 1.0, 0); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {4, 2, 3, 5}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t perms_init[] = {2, 0, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/specs/Ex/sub_broadcast_float.mod.py b/runtimes/tests/neural_networks_test/specs/Ex/sub_broadcast_float.mod.py deleted file mode 100644 index 2a3ee5e..0000000 --- a/runtimes/tests/neural_networks_test/specs/Ex/sub_broadcast_float.mod.py +++ /dev/null @@ -1,19 +0,0 @@ -# model -model = Model() -i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") -i2 = Input("op2", "TENSOR_FLOAT32", "{1}") -act = Int32Scalar("act", 0) -i3 = Output("op3", "TENSOR_FLOAT32", "{1, 2, 2, 1}") -model = model.Operation("SUB_EX", i1, i2, act).To(i3) - -# Example 1. Input in operand 0, -input0 = {i1: # input 0 - [1, 2, 3, 4], - i2: # input 1 - [2]} - -output0 = {i3: # output 0 - [-1, 0, 1, 2]} - -# Instantiate an example -Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_0/fully_connected_float_3.mod.py b/runtimes/tests/neural_networks_test/specs/V1_0/fully_connected_float_3.mod.py new file mode 100644 index 0000000..804f812 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_0/fully_connected_float_3.mod.py @@ -0,0 +1,32 @@ +# +# Copyright (C) 2018 The Android Open Source Project +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +model = Model() +in0 = Input("op1", "TENSOR_FLOAT32", "{2, 2}") +weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 2}", [2, 4]) +bias = Parameter("b0", "TENSOR_FLOAT32", "{1}", [1]) +out0 = Output("op3", "TENSOR_FLOAT32", "{2, 1}") +act = Int32Scalar("act", 0) +model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) + +# Example 1. Input in operand 0, +input0 = {in0: # input 0 + [1, 2, 2, 1]} +output0 = {out0: # output 0 + [11, 9]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space.mod.py new file mode 100644 index 0000000..bf8f56a --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space.mod.py @@ -0,0 +1,16 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{4, 1, 1, 2}") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [2, 2]) +output = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 2}") + +model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1]} + +output0 = {output: # output 0 + [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space_float_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space_float_1.mod.py new file mode 100644 index 0000000..019242a --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space_float_1.mod.py @@ -0,0 +1,16 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{4, 2, 2, 1}") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [2, 2]) +output = Output("output", "TENSOR_FLOAT32", "{1, 4, 4, 1}") + +model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]} + +output0 = {output: # output 0 + [1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16]} + +# Instantiate an example +Example((input0, output0)) \ No newline at end of file diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space_quant8_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space_quant8_1.mod.py new file mode 100644 index 0000000..8c6a727 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/batch_to_space_quant8_1.mod.py @@ -0,0 +1,16 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4, 2, 2, 1}, 1.0, 0") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [2, 2]) +output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 4, 4, 1}, 1.0, 0") + +model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]} + +output0 = {output: # output 0 + [1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16]} + +# Instantiate an example +Example((input0, output0)) \ No newline at end of file diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/div_broadcast_float.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/div_broadcast_float.mod.py new file mode 100644 index 0000000..d4e0ea9 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/div_broadcast_float.mod.py @@ -0,0 +1,19 @@ +# model +model = Model() +i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2}") +i2 = Input("op2", "TENSOR_FLOAT32", "{2, 2}") +act = Int32Scalar("act", 0) +i3 = Output("op3", "TENSOR_FLOAT32", "{2, 2}") +model = model.Operation("DIV", i1, i2, act).To(i3) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2], + i2: # input 1 + [1, 1, 2, 2]} + +output0 = {i3: # output 0 + [1, 2, 0.5, 1]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/fully_connected_float_4d_simple.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/fully_connected_float_4d_simple.mod.py new file mode 100644 index 0000000..b9a6290 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/fully_connected_float_4d_simple.mod.py @@ -0,0 +1,42 @@ +# +# Copyright (C) 2018 The Android Open Source Project +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +# This test is for testing the input requirements of Fully Connected Op: +# the input's first dimension doesn't have to be the batch size, the +# input is reshaped as needed. + +model = Model() +in0 = Input("op1", "TENSOR_FLOAT32", "{4, 1, 5, 1}") +weights = Parameter("op2", "TENSOR_FLOAT32", "{3, 10}", [ + 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, # u = 0 + 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, # u = 1 + 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, # u = 1 +]) +bias = Parameter("b0", "TENSOR_FLOAT32", "{3}", [1, 2, 3]) +out0 = Output("op3", "TENSOR_FLOAT32", "{2, 3}") +act = Int32Scalar("act", 0) +model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) + +# Example 1. Input in operand 0, +input0 = {in0: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, -9, -10, + 1, 2, 3, 4, 5, 6, 7, -8, 9, -10]} +output0 = {out0: # output 0 + [24, 25, 26, + 58, 59, 60]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/mean.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/mean.mod.py new file mode 100644 index 0000000..28bd6af --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/mean.mod.py @@ -0,0 +1,19 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{1, 2, 2, 1}") +axis = Parameter("axis", "TENSOR_INT32", "{1}", [2]) +keepDims = Int32Scalar("keepDims", 0) +output = Output("output", "TENSOR_FLOAT32", "{1, 2, 1}") + +model = model.Operation("MEAN", i1, axis, keepDims).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.0, 2.0, + 3.0, 4.0]} + +output0 = {output: # output 0 + [1.5, + 3.5]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/mean_float_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/mean_float_1.mod.py new file mode 100644 index 0000000..5fde65d --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/mean_float_1.mod.py @@ -0,0 +1,18 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{4, 3, 2}") +axis = Parameter("axis", "TENSOR_INT32", "{4}", [1, 0, -3, -3]) +keepDims = Int32Scalar("keepDims", 0) +output = Output("output", "TENSOR_FLOAT32", "{2}") + +model = model.Operation("MEAN", i1, axis, keepDims).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, + 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0]} + +output0 = {output: # output 0 + [12.0, 13.0]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/mean_float_2.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/mean_float_2.mod.py new file mode 100644 index 0000000..4b71d47 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/mean_float_2.mod.py @@ -0,0 +1,18 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{4, 3, 2}") +axis = Parameter("axis", "TENSOR_INT32", "{2}", [0, 2]) +keepDims = Int32Scalar("keepDims", 1) +output = Output("output", "TENSOR_FLOAT32", "{1, 3, 1}") + +model = model.Operation("MEAN", i1, axis, keepDims).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, + 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0]} + +output0 = {output: # output 0 + [10.5, 12.5, 14.5]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/mean_quant8_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/mean_quant8_1.mod.py new file mode 100644 index 0000000..666b0c2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/mean_quant8_1.mod.py @@ -0,0 +1,19 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4, 3, 2}, 0.8, 5") +axis = Parameter("axis", "TENSOR_INT32", "{4}", [1, 0, -3, -3]) +keepDims = Int32Scalar("keepDims", 0) +output = Output("output", "TENSOR_QUANT8_ASYMM", "{2}, 0.8, 5") + +model = model.Operation("MEAN", i1, axis, keepDims).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, + 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24]} + +output0 = {output: # output 0 + [12, 13]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/mean_quant8_2.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/mean_quant8_2.mod.py new file mode 100644 index 0000000..23fd87c --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/mean_quant8_2.mod.py @@ -0,0 +1,19 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4, 3, 2}, 0.8, 5") +axis = Parameter("axis", "TENSOR_INT32", "{2}", [0, 2]) +keepDims = Int32Scalar("keepDims", 1) +output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 3, 1}, 0.8, 5") + +model = model.Operation("MEAN", i1, axis, keepDims).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, + 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24]} + +output0 = {output: # output 0 + [10, 12, 14]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/pad.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/pad.mod.py new file mode 100644 index 0000000..54a5a46 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/pad.mod.py @@ -0,0 +1,20 @@ +# model +model = Model() +i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") +i2 = Parameter("op2", "TENSOR_INT32", "{4, 2}", [0, 0, 1, 1, 1, 1, 0, 0]) +i3 = Output("op3", "TENSOR_FLOAT32", "{1, 4, 4, 1}") +model = model.Operation("PAD", i1, i2).To(i3) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.0, 2.0, + 3.0, 4.0,]} + +output0 = {i3: # output 0 + [0.0, 0.0, 0.0, 0.0, + 0.0, 1.0, 2.0, 0.0, + 0.0, 3.0, 4.0, 0.0, + 0.0, 0.0, 0.0, 0.0]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/pad_float_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/pad_float_1.mod.py new file mode 100644 index 0000000..0817127 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/pad_float_1.mod.py @@ -0,0 +1,18 @@ +# model +model = Model() +i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 3, 1}") +i2 = Parameter("op2", "TENSOR_INT32", "{4, 2}", [0, 0, 0, 2, 1, 3, 0, 0]) +i3 = Output("op3", "TENSOR_FLOAT32", "{1, 4, 7, 1}") +model = model.Operation("PAD", i1, i2).To(i3) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.0, 2.0, 3.0, + 4.0, 5.0, 6.0]} + +output0 = {i3: # output 0 + [0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0, + 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch.mod.py new file mode 100644 index 0000000..8c10231 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch.mod.py @@ -0,0 +1,17 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{1, 2, 2, 2}") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [2, 2]) +paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) +output = Output("output", "TENSOR_FLOAT32", "{4, 1, 1, 2}") + +model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1]} + +output0 = {output: # output 0 + [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_1.mod.py new file mode 100644 index 0000000..890ced8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_1.mod.py @@ -0,0 +1,17 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{1, 4, 4, 1}") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [2, 2]) +paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) +output = Output("output", "TENSOR_FLOAT32", "{4, 2, 2, 1}") + +model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]} + +output0 = {output: # output 0 + [1, 3, 9, 11, 2, 4, 10, 12, 5, 7, 13, 15, 6, 8, 14, 16]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_2.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_2.mod.py new file mode 100644 index 0000000..c625900 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_2.mod.py @@ -0,0 +1,18 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{1, 5, 2, 1}") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [3, 2]) +paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) +output = Output("output", "TENSOR_FLOAT32", "{6, 2, 2, 1}") + +model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]} + +output0 = {output: # output 0 + [0, 0, 0, 5, 0, 0, 0, 6, 0, 1, 0, 7, + 0, 2, 0, 8, 0, 3, 0, 9, 0, 4, 0, 10]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_3.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_3.mod.py new file mode 100644 index 0000000..9d7c8b3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_float_3.mod.py @@ -0,0 +1,19 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{1, 4, 2, 1}") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [3, 2]) +paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 1, 2, 4]) +output = Output("output", "TENSOR_FLOAT32", "{6, 2, 4, 1}") + +model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8]} + +output0 = {output: # output 0 + [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, + 0, 1, 0, 0, 0, 7, 0, 0, 0, 2, 0, 0, 0, 8, 0, 0, + 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_1.mod.py new file mode 100644 index 0000000..726250d --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_1.mod.py @@ -0,0 +1,17 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{1, 4, 4, 1}, 1.0, 0") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [2, 2]) +paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) +output = Output("output", "TENSOR_QUANT8_ASYMM", "{4, 2, 2, 1}, 1.0, 0") + +model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]} + +output0 = {output: # output 0 + [1, 3, 9, 11, 2, 4, 10, 12, 5, 7, 13, 15, 6, 8, 14, 16]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_2.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_2.mod.py new file mode 100644 index 0000000..8adc262 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_2.mod.py @@ -0,0 +1,18 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{1, 5, 2, 1}, 1.0, 0") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [3, 2]) +paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) +output = Output("output", "TENSOR_QUANT8_ASYMM", "{6, 2, 2, 1}, 1.0, 0") + +model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]} + +output0 = {output: # output 0 + [0, 0, 0, 5, 0, 0, 0, 6, 0, 1, 0, 7, + 0, 2, 0, 8, 0, 3, 0, 9, 0, 4, 0, 10]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_3.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_3.mod.py new file mode 100644 index 0000000..e9e88bb --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/space_to_batch_quant8_3.mod.py @@ -0,0 +1,19 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{1, 4, 2, 1}, 1.0, 0") +block = Parameter("block_size", "TENSOR_INT32", "{2}", [3, 2]) +paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 1, 2, 4]) +output = Output("output", "TENSOR_QUANT8_ASYMM", "{6, 2, 4, 1}, 1.0, 0") + +model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8]} + +output0 = {output: # output 0 + [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, + 0, 1, 0, 0, 0, 7, 0, 0, 0, 2, 0, 0, 0, 8, 0, 0, + 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/squeeze.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/squeeze.mod.py new file mode 100644 index 0000000..4bf3189 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/squeeze.mod.py @@ -0,0 +1,16 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{4, 1, 1, 2}") +squeezeDims = Parameter("squeezeDims", "TENSOR_INT32", "{2}", [1, 2]) +output = Output("output", "TENSOR_FLOAT32", "{4, 2}") + +model = model.Operation("SQUEEZE", i1, squeezeDims).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1]} + +output0 = {output: # output 0 + [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/squeeze_float_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/squeeze_float_1.mod.py new file mode 100644 index 0000000..1a54ae7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/squeeze_float_1.mod.py @@ -0,0 +1,18 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{1, 24, 1}") +squeezeDims = Parameter("squeezeDims", "TENSOR_INT32", "{1}", [2]) +output = Output("output", "TENSOR_FLOAT32", "{1, 24}") + +model = model.Operation("SQUEEZE", i1, squeezeDims).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, + 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]} + +output0 = {output: # output 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, + 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/squeeze_quant8_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/squeeze_quant8_1.mod.py new file mode 100644 index 0000000..5710c1d --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/squeeze_quant8_1.mod.py @@ -0,0 +1,18 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{1, 24, 1}, 1.0, 0") +squeezeDims = Parameter("squeezeDims", "TENSOR_INT32", "{1}", [2]) +output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 24}, 1.0, 0") + +model = model.Operation("SQUEEZE", i1, squeezeDims).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, + 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]} + +output0 = {output: # output 0 + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, + 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice.mod.py index 26c65e7..9bc94d1 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, 3]) strides = Parameter("strides", "TENSOR_INT32", "{2}", [2, 2]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{1, 2}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_1.mod.py index 507dac6..0725cff 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_1.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_1.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{2}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_10.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_10.mod.py index 804f259..178421f 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_10.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_10.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, 2]) strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 2) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{1, 3}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_11.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_11.mod.py new file mode 100644 index 0000000..444ae63 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_11.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{2, 3}") +begins = Parameter("begins", "TENSOR_INT32", "{2}", [0, 0]) +ends = Parameter("ends", "TENSOR_INT32", "{2}", [1, 3]) +strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 1) + +output = Output("output", "TENSOR_FLOAT32", "{3}") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6]} + +output0 = {output: # output 0 + [1, 2, 3]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_2.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_2.mod.py index 483d23e..7dd3d83 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_2.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_2.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{2}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_3.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_3.mod.py index 6f71c31..e476bca 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_3.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_3.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{3}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_4.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_4.mod.py index 3583465..939cc14 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_4.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_4.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{1}", [-2]) strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{1}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_5.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_5.mod.py index 48107de..db73727 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_5.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_5.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) beginMask = Int32Scalar("beginMask", 1) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{3}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_6.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_6.mod.py index d6ce07d..c8d42d9 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_6.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_6.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 1) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{3}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_7.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_7.mod.py index cfe10db..668748a 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_7.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_7.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{1}", [-4]) strides = Parameter("strides", "TENSOR_INT32", "{1}", [-1]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{3}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_8.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_8.mod.py index 0c2cb79..2c1cc94 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_8.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_8.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, -4]) strides = Parameter("strides", "TENSOR_INT32", "{2}", [2, -1]) beginMask = Int32Scalar("beginMask", 0) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{1, 3}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_9.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_9.mod.py index d1e0ad8..4bafd3d 100644 --- a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_9.mod.py +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_float_9.mod.py @@ -5,10 +5,11 @@ ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, 2]) strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1]) beginMask = Int32Scalar("beginMask", 1) endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) output = Output("output", "TENSOR_FLOAT32", "{2, 2}") -model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask).To(output) +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) # Example 1. Input in operand 0, input0 = {i1: # input 0 diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_qaunt8_10.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_qaunt8_10.mod.py new file mode 100644 index 0000000..fc29552 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_qaunt8_10.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{2, 3}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{2}", [1, 0]) +ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, 2]) +strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 2) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 3}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6]} + +output0 = {output: # output 0 + [4, 5, 6]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_qaunt8_11.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_qaunt8_11.mod.py new file mode 100644 index 0000000..d7374ab --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_qaunt8_11.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{2, 3}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{2}", [0, 0]) +ends = Parameter("ends", "TENSOR_INT32", "{2}", [1, 3]) +strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 1) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{3}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6]} + +output0 = {output: # output 0 + [1, 2, 3]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_1.mod.py new file mode 100644 index 0000000..4b76de2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_1.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{1}", [1]) +ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) +strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{2}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4]} + +output0 = {output: # output 0 + [2, 3]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_2.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_2.mod.py new file mode 100644 index 0000000..d6cd6aa --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_2.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{1}", [-3]) +ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) +strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{2}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4]} + +output0 = {output: # output 0 + [2, 3]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_3.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_3.mod.py new file mode 100644 index 0000000..411a6fa --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_3.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{1}", [-5]) +ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) +strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{3}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4]} + +output0 = {output: # output 0 + [1, 2, 3]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_4.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_4.mod.py new file mode 100644 index 0000000..f8a54f2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_4.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{1}", [1]) +ends = Parameter("ends", "TENSOR_INT32", "{1}", [-2]) +strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{1}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4]} + +output0 = {output: # output 0 + [2]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_5.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_5.mod.py new file mode 100644 index 0000000..4fa42f5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_5.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{1}", [1]) +ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) +strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) +beginMask = Int32Scalar("beginMask", 1) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{3}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4]} + +output0 = {output: # output 0 + [1, 2, 3]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_6.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_6.mod.py new file mode 100644 index 0000000..bcd8841 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_6.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{4}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{1}", [1]) +ends = Parameter("ends", "TENSOR_INT32", "{1}", [3]) +strides = Parameter("strides", "TENSOR_INT32", "{1}", [1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 1) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{3}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4]} + +output0 = {output: # output 0 + [2, 3, 4]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_7.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_7.mod.py new file mode 100644 index 0000000..e1ae9db --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_7.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{3}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{1}", [-1]) +ends = Parameter("ends", "TENSOR_INT32", "{1}", [-4]) +strides = Parameter("strides", "TENSOR_INT32", "{1}", [-1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{3}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3]} + +output0 = {output: # output 0 + [3, 2, 1]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_8.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_8.mod.py new file mode 100644 index 0000000..6531dd3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_8.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{2, 3}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{2}", [1, -1]) +ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, -4]) +strides = Parameter("strides", "TENSOR_INT32", "{2}", [2, -1]) +beginMask = Int32Scalar("beginMask", 0) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 3}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6]} + +output0 = {output: # output 0 + [6, 5, 4]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_9.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_9.mod.py new file mode 100644 index 0000000..7f06601 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/strided_slice_quant8_9.mod.py @@ -0,0 +1,22 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{2, 3}, 1.0, 0") +begins = Parameter("begins", "TENSOR_INT32", "{2}", [1, 0]) +ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, 2]) +strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1]) +beginMask = Int32Scalar("beginMask", 1) +endMask = Int32Scalar("endMask", 0) +shrinkAxisMask = Int32Scalar("shrinkAxisMask", 0) + +output = Output("output", "TENSOR_QUANT8_ASYMM", "{2, 2}, 1.0, 0") + +model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2, 3, 4, 5, 6]} + +output0 = {output: # output 0 + [1, 2, 4, 5]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/sub_broadcast_float.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/sub_broadcast_float.mod.py new file mode 100644 index 0000000..53bdf9e --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/sub_broadcast_float.mod.py @@ -0,0 +1,19 @@ +# model +model = Model() +i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2}") +i2 = Input("op2", "TENSOR_FLOAT32", "{2, 2}") +act = Int32Scalar("act", 0) +i3 = Output("op3", "TENSOR_FLOAT32", "{2, 2}") +model = model.Operation("SUB", i1, i2, act).To(i3) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1, 2], + i2: # input 1 + [1, 2, 3, 4]} + +output0 = {i3: # output 0 + [0, 0, -2, -2]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/transpose.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/transpose.mod.py new file mode 100644 index 0000000..49f15a7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/transpose.mod.py @@ -0,0 +1,18 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{1, 2, 2, 1}") +perms = Parameter("perms", "TENSOR_INT32", "{4}", [0, 2, 1, 3]) +output = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 1}") + +model = model.Operation("TRANSPOSE", i1, perms).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [1.0, 2.0, + 3.0, 4.0]} + +output0 = {output: # output 0 + [1.0, 3.0, + 2.0, 4.0]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/transpose_float_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/transpose_float_1.mod.py new file mode 100644 index 0000000..e8f0ea8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/transpose_float_1.mod.py @@ -0,0 +1,32 @@ +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{2, 3, 4, 5}") +perms = Parameter("perms", "TENSOR_INT32", "{4}", [2, 0, 1, 3]) +output = Output("output", "TENSOR_FLOAT32", "{4, 2, 3, 5}") + +model = model.Operation("TRANSPOSE", i1, perms).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, + 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, + 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, + 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, + 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, + 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, + 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, + 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, + 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, + 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119]} + +output0 = {output: # output 0 + [0, 1, 2, 3, 4, 20, 21, 22, 23, 24, 40, 41, 42, 43, 44, + 60, 61, 62, 63, 64, 80, 81, 82, 83, 84, 100, 101, 102, 103, 104, + 5, 6, 7, 8, 9, 25, 26, 27, 28, 29, 45, 46, 47, 48, 49, + 65, 66, 67, 68, 69, 85, 86, 87, 88, 89, 105, 106, 107, 108, 109, + 10, 11, 12, 13, 14, 30, 31, 32, 33, 34, 50, 51, 52, 53, 54, + 70, 71, 72, 73, 74, 90, 91, 92, 93, 94, 110, 111, 112, 113, 114, + 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 55, 56, 57, 58, 59, + 75, 76, 77, 78, 79, 95, 96, 97, 98, 99, 115, 116, 117, 118, 119]} + +# Instantiate an example +Example((input0, output0)) diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/transpose_quant8_1.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/transpose_quant8_1.mod.py new file mode 100644 index 0000000..6893a62 --- /dev/null +++ b/runtimes/tests/neural_networks_test/specs/V1_1/transpose_quant8_1.mod.py @@ -0,0 +1,32 @@ +model = Model() +i1 = Input("input", "TENSOR_QUANT8_ASYMM", "{2, 3, 4, 5}, 1.0, 0") +perms = Parameter("perms", "TENSOR_INT32", "{4}", [2, 0, 1, 3]) +output = Output("output", "TENSOR_QUANT8_ASYMM", "{4, 2, 3, 5}, 1.0, 0") + +model = model.Operation("TRANSPOSE", i1, perms).To(output) + +# Example 1. Input in operand 0, +input0 = {i1: # input 0 + [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, + 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, + 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, + 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, + 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, + 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, + 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, + 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, + 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, + 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119]} + +output0 = {output: # output 0 + [0, 1, 2, 3, 4, 20, 21, 22, 23, 24, 40, 41, 42, 43, 44, + 60, 61, 62, 63, 64, 80, 81, 82, 83, 84, 100, 101, 102, 103, 104, + 5, 6, 7, 8, 9, 25, 26, 27, 28, 29, 45, 46, 47, 48, 49, + 65, 66, 67, 68, 69, 85, 86, 87, 88, 89, 105, 106, 107, 108, 109, + 10, 11, 12, 13, 14, 30, 31, 32, 33, 34, 50, 51, 52, 53, 54, + 70, 71, 72, 73, 74, 90, 91, 92, 93, 94, 110, 111, 112, 113, 114, + 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 55, 56, 57, 58, 59, + 75, 76, 77, 78, 79, 95, 96, 97, 98, 99, 115, 116, 117, 118, 119]} + +# Instantiate an example +Example((input0, output0)) -- 2.7.4