Fix test data of depthwise_conv2d_float_large_2_weights_as_inputs (#2300)

`depthwise_conv2d_float_large_2_weights_as_inputs` is another test version, using same data of `depthwise_conv2d_float_large_2`
This commit will fix the test data to be same

Signed-off-by: Seok NamKoong <sk.namkoong@samsung.com>

diff --git a/runtimes/tests/neural_networks_test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs.example.cpp
index 9b097ac..1840bc9 100644 (file)
--- a/runtimes/tests/neural_networks_test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs.example.cpp
+++ b/runtimes/tests/neural_networks_test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs.example.cpp
@@ -4,7 +4,7 @@
 //Input(s)
 { // See tools/test_generator/include/TestHarness.h:MixedTyped
   // int -> FLOAT32 map
-  {{0, {10, 21, 100, 10, 22, 200, 10, 23, 300, 10, 24, 400}}, {1, {0.25f, 0, 10, 100, 0.25f, 1, 20, 100, 0.25f, 0, 30, 100, 0.25f, 1, 40, 100}}, {2, {600000, 700000, 800000, 900000}}},
+  {{0, {10, 21, 100, 0, 10, 22, 200, 0, 10, 23, 300, 0, 10, 24, 400, 0}}, {1, {0.25f, 0, 10, 100, 0.25f, 1, 20, 100, 0.25f, 0, 30, 100, 0.25f, 1, 40, 100}}, {2, {600000, 700000, 800000, 900000}}},
   // int -> INT32 map
   {},
   // int -> QUANT8_ASYMM map

diff --git a/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp b/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp
index 19de705..b0ad1e9 100644 (file)
--- a/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp
+++ b/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp
@@ -2,7 +2,7 @@
 void CreateModel(Model *model) {
   OperandType type3(Type::INT32, {});
   OperandType type4(Type::TENSOR_FLOAT32, {1, 1, 1, 4});
-  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
   OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
   OperandType type2(Type::TENSOR_FLOAT32, {4});
   // Phase 1, operands

diff --git a/runtimes/tests/neural_networks_test/specs/V1_0/depthwise_conv2d_float_large_2_weights_as_inputs.mod.py b/runtimes/tests/neural_networks_test/specs/V1_0/depthwise_conv2d_float_large_2_weights_as_inputs.mod.py
index b91f309..d759cf2 100644 (file)
--- a/runtimes/tests/neural_networks_test/specs/V1_0/depthwise_conv2d_float_large_2_weights_as_inputs.mod.py
+++ b/runtimes/tests/neural_networks_test/specs/V1_0/depthwise_conv2d_float_large_2_weights_as_inputs.mod.py
@@ -15,7 +15,7 @@
 #
 
 model = Model()
-i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 3}") # depth_in = 3
+i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 4}") # depth_in = 4
 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}") # depth_out = 4
 b1 = Input("op3", "TENSOR_FLOAT32", "{4}") # depth_out = 4
 pad0 = Int32Scalar("pad0", 0)
@@ -33,10 +33,10 @@ model = model.Operation("DEPTHWISE_CONV_2D",
 # Example 1. Input in operand 0,
 input0 = {
     i1: [ # input 0
-     10, 21, 100,
-     10, 22, 200,
-     10, 23, 300,
-     10, 24, 400],
+     10, 21, 100, 0,
+     10, 22, 200, 0,
+     10, 23, 300, 0,
+     10, 24, 400, 0],
     f1: [
      .25, 0, 10, 100,
      .25, 1, 20, 100,