Added SHAPE op and tests for micro

tensorflow/lite/core/api/flatbuffer_conversions.cc

@@ -1514,6 +1514,20 @@ TfLiteStatus ParseRsqrt(const Operator*, ErrorReporter*, BuiltinDataAllocator*,
   return kTfLiteOk;
 }
 
+// We have this parse function instead of directly returning kTfLiteOk from the
+// switch-case in ParseOpData because this function is used as part of the
+// selective registration for the OpResolver implementation in micro.
+TfLiteStatus ParseShape(const Operator*, ErrorReporter* error_reporter,
+  
+  SafeBuiltinDataAllocator safe_allocator(allocator);
+  std::unique_ptr<TfLiteShapeParams,
+                  SafeBuiltinDataAllocator::BuiltinDataDeleter>
+      params = safe_allocator.Allocate<TfLiteShapeParams>();
+  TF_LITE_ENSURE(error_reporter, params != nullptr);
+  *builtin_data = params.release();
+  return kTfLiteOk;
+}  // namespace tflite
+
 // We have this parse function instead of directly returning kTfLiteOk from the
 // switch-case in ParseOpData because this function is used as part of the
 // selective registration for the OpResolver implementation in micro.

tensorflow/lite/core/api/flatbuffer_conversions.h

@@ -216,6 +216,9 @@ TfLiteStatus ParseRound(const Operator* op, ErrorReporter* error_reporter,
 TfLiteStatus ParseRsqrt(const Operator* op, ErrorReporter* error_reporter,
                         BuiltinDataAllocator* allocator, void** builtin_data);
 
+TfLiteStatus ParseShape(const Operator* op, ErrorReporter* error_reporter,
+                        BuiltinDataAllocator* allocator, void** builtin_data);
+
 TfLiteStatus ParseSin(const Operator* op, ErrorReporter* error_reporter,
                       BuiltinDataAllocator* allocator, void** builtin_data);
 

tensorflow/lite/micro/all_ops_resolver.cc

@@ -70,6 +70,7 @@ AllOpsResolver::AllOpsResolver() {
   AddResizeNearestNeighbor();
   AddRound();
   AddRsqrt();
+  AddShape();
   AddSin();
   AddSoftmax();
   AddSplit();

tensorflow/lite/micro/kernels/BUILD

@@ -53,6 +53,7 @@ cc_library(
         "reshape.cc",
         "resize_nearest_neighbor.cc",
         "round.cc",
+        "shape.cc",
         "split.cc",
         "split_v.cc",
         "strided_slice.cc",

tensorflow/lite/micro/kernels/micro_ops.h

@@ -74,6 +74,7 @@ TfLiteRegistration Register_RESHAPE();
 TfLiteRegistration Register_RESIZE_NEAREST_NEIGHBOR();
 TfLiteRegistration Register_ROUND();
 TfLiteRegistration Register_RSQRT();
+TfLiteRegistration Register_SHAPE();
 TfLiteRegistration Register_SIN();
 TfLiteRegistration Register_SOFTMAX();
 TfLiteRegistration Register_SPLIT();

tensorflow/lite/micro/kernels/shape.cc

@@ -0,0 +1,80 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+#include "tensorflow/lite/micro/kernels/kernel_util.h"
+#include "tensorflow/lite/micro/memory_helpers.h"
+#include "tensorflow/lite/micro/micro_utils.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace shape {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+void ExtractShape(const TfLiteEvalTensor* input, int32_t* output_data) {
+  int numInputDims = input->dims->size;
+
+  for (int i = 0; i < numInputDims; ++i) {
+    output_data[i] = input->dims->data[i];
+  }
+}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteEvalTensor* input =
+      tflite::micro::GetEvalInput(context, node, kInputTensor);
+  TfLiteEvalTensor* output =
+      tflite::micro::GetEvalOutput(context, node, kOutputTensor);
+
+  switch (output->type) {
+    case kTfLiteInt32:
+      ExtractShape(input, tflite::micro::GetTensorData<int32_t>(output));
+      break;
+    default:
+      return kTfLiteError;
+  }
+
+  return kTfLiteOk;
+}
+
+}  // namespace shape
+
+TfLiteRegistration Register_SHAPE() {
+  return {/*init=*/nullptr,
+          /*free=*/nullptr,
+          /*prepare=*/shape::Prepare,
+          /*invoke=*/shape::Eval,
+          /*profiling_string=*/nullptr,
+          /*builtin_code=*/0,
+          /*custom_name=*/nullptr,
+          /*version=*/0};
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

tensorflow/lite/micro/kernels/shape_test.cc

@@ -0,0 +1,139 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+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.
+==============================================================================*/
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/micro/all_ops_resolver.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 testing {
+namespace {
+
+void ValidateShape(TfLiteTensor* tensors, const int tensor_count,
+                   int* output_data, const int* expected_output,
+                   int output_dims_count) {
+  TfLiteShapeParams builtin_data;
+  int inputs_array_data[] = {1, 0};
+  TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
+  int outputs_array_data[] = {1, 1};
+  TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);
+
+  const TfLiteRegistration registration = tflite::ops::micro::Register_SHAPE();
+  micro::KernelRunner runner(registration, tensors, tensor_count, inputs_array,
+                             outputs_array, nullptr, micro_test::reporter);
+
+  TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.InitAndPrepare());
+  TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.Invoke());
+
+  for (int i = 0; i < output_dims_count; ++i) {
+    TF_LITE_MICRO_EXPECT_EQ(expected_output[i], output_data[i]);
+  }
+}
+
+void TestShape(const int* input_dims_data, const float* input_data,
+               const int* output_dims_data, const int* expected_output_data,
+               int* output_data) {
+  TfLiteIntArray* input_dims = IntArrayFromInts(input_dims_data);
+  TfLiteIntArray* output_dims = IntArrayFromInts(output_dims_data);
+  const int output_dims_count = ElementCount(*output_dims);
+
+  constexpr int inputs_size = 1;
+  constexpr int outputs_size = 1;
+  constexpr int tensors_size = inputs_size + outputs_size;
+  TfLiteTensor tensors[tensors_size] = {
+      CreateFloatTensor(input_data, input_dims),
+      CreateInt32Tensor(output_data, output_dims, true),
+  };
+
+  ValidateShape(tensors, tensors_size, output_data, expected_output_data,
+                output_dims_count);
+}
+
+}  // namespace
+}  // namespace testing
+}  // namespace tflite
+
+TF_LITE_MICRO_TESTS_BEGIN
+
+TF_LITE_MICRO_TEST(TestShape0) {
+  int input_shape[] = {1, 5};
+  float input_values[] = {1, 3, 1, 3, 5};
+  int output_dims[] = {1, 1};  // this is actually input_shapes shape
+  int expected_output_data[] = {5};
+  int output_data[1];
+
+  tflite::testing::TestShape(input_shape, input_values, output_dims,
+                             expected_output_data, output_data);
+}
+
+TF_LITE_MICRO_TEST(TestShape1) {
+  int input_shape[] = {2, 4, 3};
+  float input_values[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
+  int output_dims[] = {2, 1, 1};
+  int expected_output_data[] = {4, 3};
+  int output_data[2];
+
+  tflite::testing::TestShape(input_shape, input_values, output_dims,
+                             expected_output_data, output_data);
+}
+
+TF_LITE_MICRO_TEST(TestShape2) {
+  int input_shape[] = {2, 12, 1};
+  float input_values[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
+  int output_dims[] = {2, 1, 1};
+  int expected_output_data[] = {12, 1};
+  int output_data[2];
+
+  tflite::testing::TestShape(input_shape, input_values, output_dims,
+                             expected_output_data, output_data);
+}
+
+TF_LITE_MICRO_TEST(TestShape3) {
+  int input_shape[] = {2, 2, 6};
+  float input_values[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
+  int output_dims[] = {2, 1, 1};
+  int expected_output_data[] = {2, 6};
+  int output_data[2];
+
+  tflite::testing::TestShape(input_shape, input_values, output_dims,
+                             expected_output_data, output_data);
+}
+
+TF_LITE_MICRO_TEST(TestShape4) {
+  int input_shape[] = {2, 2, 2, 3};
+  float input_values[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
+  int output_dims[] = {3, 1, 1, 1};
+  int expected_output_data[] = {2, 2, 3};
+  int output_data[3];
+
+  tflite::testing::TestShape(input_shape, input_values, output_dims,
+                             expected_output_data, output_data);
+}
+
+TF_LITE_MICRO_TEST(TestShape5) {
+  int input_shape[] = {1, 1};
+  float input_values[] = {1};
+  int output_dims[] = {1, 1};
+  int expected_output_data[] = {1};
+  int output_data[1];
+
+  tflite::testing::TestShape(input_shape, input_values, output_dims,
+                             expected_output_data, output_data);
+}
+
+TF_LITE_MICRO_TESTS_END

tensorflow/lite/micro/micro_mutable_op_resolver.h

@@ -345,6 +345,11 @@ class MicroMutableOpResolver : public MicroOpResolver {
                       tflite::ops::micro::Register_RSQRT(), ParseRsqrt);
   }
 
+  TfLiteStatus AddShape() {
+    return AddBuiltin(BuiltinOperator_SHAPE,
+                      tflite::ops::micro::Register_SHAPE(), ParseShape);
+  }
+
   TfLiteStatus AddSin() {
     return AddBuiltin(BuiltinOperator_SIN, tflite::ops::micro::Register_SIN(),
                       ParseSin);