Introduce testcases for reduce mean (#2302)

* Introduce testcases for reduce mean

This commit introduces testcases for reduce_mean operation.
-4D input
-axises (width-height)
-keep dims

These are test cases for RS7-RuntimeNTools/ComputeLibrary#34

related issue:#2003

Signed-off-by: SungJin Choi lotieye.choi@samsung.com
* Modify mean_axis01_2 test case

This commit modifies mean_axis01_2 test case.

Signed-off-by: SungJin Choi <lotieye.choi@samsung.com>

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 306ada7..7c562b9 100644 (file)
--- a/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp
+++ b/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp
@@ -2171,6 +2171,34 @@ TEST_F(GeneratedTests, fully_connected_float_4d_simple) {
             fully_connected_float_4d_simple::examples);
 }
 
+namespace mean_axis01_1_nnfw {
+std::vector<MixedTypedExample> examples = {
+// Generated mean_axis01_1_nnfw test
+#include "generated/examples/mean_axis01_1_nnfw.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/mean_axis01_1_nnfw.model.cpp"
+} // namespace mean_axis01_1_nnfw
+TEST_F(GeneratedTests, mean_axis01_1_nnfw) {
+    execute(mean_axis01_1_nnfw::CreateModel,
+            mean_axis01_1_nnfw::is_ignored,
+            mean_axis01_1_nnfw::examples);
+}
+
+namespace mean_axis01_2_nnfw {
+std::vector<MixedTypedExample> examples = {
+// Generated mean_axis01_2_nnfw test
+#include "generated/examples/mean_axis01_2_nnfw.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/mean_axis01_2_nnfw.model.cpp"
+} // namespace mean_axis01_2_nnfw
+TEST_F(GeneratedTests, mean_axis01_2_nnfw) {
+    execute(mean_axis01_2_nnfw::CreateModel,
+            mean_axis01_2_nnfw::is_ignored,
+            mean_axis01_2_nnfw::examples);
+}
+
 namespace mean_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated mean_float_1 test

diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_1_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_1_nnfw.example.cpp
new file mode 100644 (file)
index 0000000..99d196f
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_1_nnfw.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: mean_axis01_1_nnfw.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, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 1.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example

diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_2_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_2_nnfw.example.cpp
new file mode 100644 (file)
index 0000000..4ea3230
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_2_nnfw.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: mean_axis01_2_nnfw.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/models/mean_axis01_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_1_nnfw.model.cpp
new file mode 100644 (file)
index 0000000..e14f688
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_1_nnfw.model.cpp
@@ -0,0 +1,28 @@
+// Generated file (from: mean_axis01_1_nnfw.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 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[] = {1, 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<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}

diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp
new file mode 100644 (file)
index 0000000..26afa5a
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp
@@ -0,0 +1,28 @@
+// Generated file (from: mean_axis01_2_nnfw.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 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, 2, -3, -3};
+  model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4);
+  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<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}

diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/mean_axis01_1_nnfw.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/mean_axis01_1_nnfw.mod.py
new file mode 100644 (file)
index 0000000..00b63a5
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/specs/V1_1/mean_axis01_1_nnfw.mod.py
@@ -0,0 +1,18 @@
+model = Model()
+i1 = Input("input", "TENSOR_FLOAT32", "{1, 4, 3, 2}")
+axis = Parameter("axis", "TENSOR_INT32", "{2}", [1, 2])
+keepDims = Int32Scalar("keepDims", 1)
+output = Output("output", "TENSOR_FLOAT32", "{1, 1, 1, 2}")
+
+model = model.Operation("MEAN", i1, axis, keepDims).To(output)
+
+# Example 1. Input in operand 0,
+input0 = {i1: # input 0
+          [1.0,  1.0,  1.0,  1.0,  1.0,  1.0,  1.0,  1.0,  1.0,  1.0, 1.0, 1.0,
+           1.0,  1.0,  1.0,  1.0,  1.0,  1.0,  1.0,  1.0,  1.0,  1.0, 1.0, 1.0]}
+
+output0 = {output: # output 0
+          [1.0, 1.0]}
+
+# Instantiate an example
+Example((input0, output0))

diff --git a/runtimes/tests/neural_networks_test/specs/V1_1/mean_axis01_2_nnfw.mod.py b/runtimes/tests/neural_networks_test/specs/V1_1/mean_axis01_2_nnfw.mod.py
new file mode 100644 (file)
index 0000000..1f0eb9c
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/specs/V1_1/mean_axis01_2_nnfw.mod.py
@@ -0,0 +1,17 @@
+model = Model()
+i1 = Input("input", "TENSOR_FLOAT32", "{1, 4, 3, 2}")
+axis = Parameter("axis", "TENSOR_INT32", "{4}", [1, 2, -3, -3])
+keepDims = Int32Scalar("keepDims", 1)
+output = Output("output", "TENSOR_FLOAT32", "{1, 1, 1, 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))