From b5633e6b5f78a897bb04fec5f20c2fc6c51f8752 Mon Sep 17 00:00:00 2001
From: ddavis-2015 <ddavis@bdti.com>
Date: Fri, 12 Feb 2021 02:29:06 -0800
Subject: [PATCH] micro: prepare to port operator ADD_N kernel from lite with
test
Implement skeleton (non-working) code for operator and test.
Header files changed.
Namespaces changed.
Some original code deleted.
Some original code modified.
PR step 4 of the work to port operator ADD_N as tracked in Issue #46162
---
tensorflow/lite/micro/kernels/add_n.cc | 18 ++----
tensorflow/lite/micro/kernels/add_n_test.cc | 70 ++++++---------------
2 files changed, 24 insertions(+), 64 deletions(-)
diff --git a/tensorflow/lite/micro/kernels/add_n.cc b/tensorflow/lite/micro/kernels/add_n.cc
index 390d285f3bb..be0fd47fdd2 100644
--- a/tensorflow/lite/micro/kernels/add_n.cc
+++ b/tensorflow/lite/micro/kernels/add_n.cc
@@ -22,8 +22,9 @@ limitations under the License.
namespace tflite {
namespace ops {
-namespace builtin {
+namespace micro {
namespace add_n {
+namespace {
constexpr int kInputTensor1 = 0;
constexpr int kOutputTensor = 0;
@@ -49,11 +50,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
TF_LITE_ENSURE_TYPES_EQ(context, input1->type, input->type);
}
- // Use the first input node's dimension to be the dimension of the output
- // node.
- TfLiteIntArray* input1_dims = input1->dims;
- TfLiteIntArray* output_dims = TfLiteIntArrayCopy(input1_dims);
- return context->ResizeTensor(context, output, output_dims);
+ return kTfLiteError;
}
template <typename T>
@@ -88,14 +85,11 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
return kTfLiteOk;
}
+} // namespace
} // namespace add_n
-TfLiteRegistration* Register_ADD_N() {
- static TfLiteRegistration r = {/*init*/ nullptr, /*free*/ nullptr,
- add_n::Prepare, add_n::Eval};
- return &r;
-}
+TfLiteRegistration* Register_ADD_N() { return nullptr; }
-} // namespace builtin
+} // namespace micro
} // namespace ops
} // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/add_n_test.cc b/tensorflow/lite/micro/kernels/add_n_test.cc
index 4b229b6563b..d09c32ceb79 100644
--- a/tensorflow/lite/micro/kernels/add_n_test.cc
+++ b/tensorflow/lite/micro/kernels/add_n_test.cc
@@ -12,59 +12,25 @@ 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.
==============================================================================*/
-#include <stdint.h>
-#include <vector>
+#include <type_traits>
-#include "flatbuffers/flatbuffers.h" // from @flatbuffers
-#include "tensorflow/lite/kernels/test_util.h"
-#include "tensorflow/lite/schema/schema_generated.h"
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/micro/kernels/kernel_runner.h"
+#include "tensorflow/lite/micro/test_helpers.h"
+#include "tensorflow/lite/micro/testing/micro_test.h"
namespace tflite {
-namespace {
+namespace testing {
+namespace {} // namespace
+} // namespace testing
+} // namespace tflite
-using ::testing::ElementsAreArray;
+TF_LITE_MICRO_TESTS_BEGIN
-class BaseAddNOpModel : public SingleOpModel {
- public:
- BaseAddNOpModel(const std::vector<TensorData>& inputs,
- const TensorData& output) {
- int num_inputs = inputs.size();
- std::vector<std::vector<int>> input_shapes;
-
- for (int i = 0; i < num_inputs; ++i) {
- inputs_.push_back(AddInput(inputs[i]));
- input_shapes.push_back(GetShape(inputs_[i]));
- }
-
- output_ = AddOutput(output);
- SetBuiltinOp(BuiltinOperator_ADD_N, BuiltinOptions_AddNOptions,
- CreateAddNOptions(builder_).Union());
- BuildInterpreter(input_shapes);
- }
-
- int input(int i) { return inputs_[i]; }
-
- protected:
- std::vector<int> inputs_;
- int output_;
-};
-
-class FloatAddNOpModel : public BaseAddNOpModel {
- public:
- using BaseAddNOpModel::BaseAddNOpModel;
-
- std::vector<float> GetOutput() { return ExtractVector<float>(output_); }
-};
-
-class IntegerAddNOpModel : public BaseAddNOpModel {
- public:
- using BaseAddNOpModel::BaseAddNOpModel;
-
- std::vector<int32_t> GetOutput() { return ExtractVector<int32_t>(output_); }
-};
-
-TEST(FloatAddNOpModel, AddMultipleTensors) {
+TF_LITE_MICRO_TEST(FloatAddNOpAddMultipleTensors) {
+#ifdef notdef
FloatAddNOpModel m({{TensorType_FLOAT32, {1, 2, 2, 1}},
{TensorType_FLOAT32, {1, 2, 2, 1}},
{TensorType_FLOAT32, {1, 2, 2, 1}}},
@@ -72,11 +38,12 @@ TEST(FloatAddNOpModel, AddMultipleTensors) {
m.PopulateTensor<float>(m.input(0), {-2.0, 0.2, 0.7, 0.8});
m.PopulateTensor<float>(m.input(1), {0.1, 0.2, 0.3, 0.5});
m.PopulateTensor<float>(m.input(2), {0.5, 0.1, 0.1, 0.2});
- m.Invoke();
EXPECT_THAT(m.GetOutput(), ElementsAreArray({-1.4, 0.5, 1.1, 1.5}));
+#endif // notdef
}
-TEST(IntegerAddNOpModel, AddMultipleTensors) {
+TF_LITE_MICRO_TEST(IntegerAddNOpAddMultipleTensors) {
+#ifdef notdef
IntegerAddNOpModel m({{TensorType_INT32, {1, 2, 2, 1}},
{TensorType_INT32, {1, 2, 2, 1}},
{TensorType_INT32, {1, 2, 2, 1}}},
@@ -84,9 +51,8 @@ TEST(IntegerAddNOpModel, AddMultipleTensors) {
m.PopulateTensor<int32_t>(m.input(0), {-20, 2, 7, 8});
m.PopulateTensor<int32_t>(m.input(1), {1, 2, 3, 5});
m.PopulateTensor<int32_t>(m.input(2), {10, -5, 1, -2});
- m.Invoke();
EXPECT_THAT(m.GetOutput(), ElementsAreArray({-9, -1, 11, 11}));
+#endif // notdef
}
-} // namespace
-} // namespace tflite
+TF_LITE_MICRO_TESTS_END