tflite_micro_person_detection_init

components/tflite_micro/tensorflow/lite/micro/kernels/reshape.cc

@@ -0,0 +1,116 @@
+/* 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 reshape {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus ReshapeOutput(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  // Tensorflow's Reshape allows one of the shape components to have the
+  // special -1 value, meaning it will be calculated automatically based on the
+  // input. Here we calculate what that dimension should be so that the number
+  // of output elements in the same as the number of input elements.
+  int num_input_elements = NumElements(input);
+  TfLiteIntArray* output_shape = output->dims;
+
+  if (NumInputs(node) == 1 &&  // Legacy scalar supported with params.
+      output_shape->size == 1 && output_shape->data[0] == 0) {
+    // Legacy tflite models use a shape parameter of [0] to indicate scalars,
+    // so adjust accordingly. TODO(b/111614235): Allow zero-sized buffers during
+    // toco conversion.
+    output_shape->size = 0;
+  }
+
+  int num_output_elements = 1;
+  int stretch_dim = -1;
+  for (int i = 0; i < output_shape->size; ++i) {
+    int value = output_shape->data[i];
+    if (value == -1) {
+      TF_LITE_ENSURE_EQ(context, stretch_dim, -1);
+      stretch_dim = i;
+    } else {
+      num_output_elements *= value;
+    }
+  }
+  if (stretch_dim != -1) {
+    output_shape->data[stretch_dim] = num_input_elements / num_output_elements;
+    num_output_elements *= output_shape->data[stretch_dim];
+  }
+
+  TF_LITE_ENSURE_TYPES_EQ(context, input->type, output->type);
+  TF_LITE_ENSURE_EQ(context, num_input_elements, num_output_elements);
+  return kTfLiteOk;
+}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE(context, NumInputs(node) == 1 || NumInputs(node) == 2);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, ReshapeOutput(context, node), kTfLiteOk);
+  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);
+
+  // TODO(b/162522304): storing input bytes in OpData increases some models
+  // significantly, possibly due to alignment issues.
+  size_t input_bytes;
+  TF_LITE_ENSURE_STATUS(TfLiteTypeSizeOf(input->type, &input_bytes));
+  input_bytes *= ElementCount(*input->dims);
+
+  // Do nothing for in-place reshape.
+  if (input->data.raw != output->data.raw) {
+    // Otherwise perform reshape with copy.
+    for (size_t i = 0; i < input_bytes; ++i) {
+      output->data.raw[i] = input->data.raw[i];
+    }
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace reshape
+
+TfLiteRegistration Register_RESHAPE() {
+  return {/*init=*/nullptr,
+          /*free=*/nullptr,
+          /*prepare=*/reshape::Prepare,
+          /*invoke=*/reshape::Eval,
+          /*profiling_string=*/nullptr,
+          /*builtin_code=*/0,
+          /*custom_name=*/nullptr,
+          /*version=*/0};
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite