Add a generated test for broadcast add (#3125)

This test is consist of an ADD, a CONCATENATION and a RESHAPE operation.
CONCATENATION and RESHAPE are NOP just copy the value to the output.
They are exist for making test easier with different layouts(NCHW/NHWC)
on neurun.

Signed-off-by: Hanjoung Lee <hanjoung.lee@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 0de0f50..19567d2 100644 (file)
--- a/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp
+++ b/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp
@@ -1,6 +1,20 @@
 // DO NOT EDIT;
 // Generated by nnfw/runtimes/tests/neural_networks_test/specs/generate_test.sh
 
+namespace add_broadcast_4D_2D_after_nops_float_nnfw {
+std::vector<MixedTypedExample> examples = {
+// Generated add_broadcast_4D_2D_after_nops_float_nnfw test
+#include "generated/examples/add_broadcast_4D_2D_after_nops_float_nnfw.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/add_broadcast_4D_2D_after_nops_float_nnfw.model.cpp"
+} // namespace add_broadcast_4D_2D_after_nops_float_nnfw
+TEST_F(GeneratedTests, add_broadcast_4D_2D_after_nops_float_nnfw) {
+    execute(add_broadcast_4D_2D_after_nops_float_nnfw::CreateModel,
+            add_broadcast_4D_2D_after_nops_float_nnfw::is_ignored,
+            add_broadcast_4D_2D_after_nops_float_nnfw::examples);
+}
+
 namespace add_broadcast_quant8 {
 std::vector<MixedTypedExample> examples = {
 // Generated add_broadcast_quant8 test

diff --git a/runtimes/tests/neural_networks_test/generated/examples/add_broadcast_4D_2D_after_nops_float_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/add_broadcast_4D_2D_after_nops_float_nnfw.example.cpp
new file mode 100644 (file)
index 0000000..b93ffc4
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/examples/add_broadcast_4D_2D_after_nops_float_nnfw.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: add_broadcast_4D_2D_after_nops_float_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, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}}, {1, {100, 200}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example

diff --git a/runtimes/tests/neural_networks_test/generated/models/add_broadcast_4D_2D_after_nops_float_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/add_broadcast_4D_2D_after_nops_float_nnfw.model.cpp
new file mode 100644 (file)
index 0000000..9b48118
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/models/add_broadcast_4D_2D_after_nops_float_nnfw.model.cpp
@@ -0,0 +1,37 @@
+// Generated file (from: add_broadcast_4D_2D_after_nops_float_nnfw.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 3, 4});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 1, 1});
+  OperandType type4(Type::TENSOR_FLOAT32, {1, 2, 3, 4});
+  OperandType type3(Type::TENSOR_INT32, {4});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto axis0 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto op4 = model->addOperand(&type3);
+  auto op5 = model->addOperand(&type0);
+  auto op6 = model->addOperand(&type2);
+  auto op7 = model->addOperand(&type4);
+  auto act = model->addOperand(&type1);
+  // Phase 2, operations
+  static int32_t axis0_init[] = {0};
+  model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1);
+  static int32_t op4_init[] = {1, 2, 1, 1};
+  model->setOperandValue(op4, op4_init, sizeof(int32_t) * 4);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONCATENATION, {op1, axis0}, {op5});
+  model->addOperation(ANEURALNETWORKS_RESHAPE, {op3, op4}, {op6});
+  model->addOperation(ANEURALNETWORKS_ADD, {op5, op6, act}, {op7});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op3},
+    {op7});
+  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_0/add_broadcast_4D_2D_after_nops_float_nnfw.mod.py b/runtimes/tests/neural_networks_test/specs/V1_0/add_broadcast_4D_2D_after_nops_float_nnfw.mod.py
new file mode 100644 (file)
index 0000000..141682e
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/specs/V1_0/add_broadcast_4D_2D_after_nops_float_nnfw.mod.py
@@ -0,0 +1,31 @@
+# model
+model = Model()
+
+i1 = Input("op1", "TENSOR_FLOAT32", "{1, 1, 3, 4}")
+axis0 = Int32Scalar("axis0", 0)
+
+i3 = Input("op3", "TENSOR_FLOAT32", "{1, 2, 1, 1}")
+i4 = Parameter("op4", "TENSOR_INT32", "{4}", [1, 2, 1, 1])
+
+i5 = Internal("op5", "TENSOR_FLOAT32", "{1, 1, 3, 4}")
+i6 = Internal("op6", "TENSOR_FLOAT32", "{1, 2, 1, 1}")
+
+i7 = Output("op7", "TENSOR_FLOAT32", "{1, 2, 3, 4}")
+
+act = Int32Scalar("act", 0)
+
+model = model.Operation("CONCATENATION", i1, axis0).To(i5) # Actually NOP
+model = model.Operation("RESHAPE", i3, i4).To(i6) # Actually NOP
+model = model.Operation("ADD", i5, i6, act).To(i7)
+
+# Example 1. Input in operand 0,
+input0 = {i1: # input 0
+          [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
+          i3: # input 1
+          [100, 200]}
+
+output0 = {i7: # output 0
+           [101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212]}
+
+# Instantiate an example
+Example((input0, output0))