mirror of
https://github.com/vee1e/tflite-micro.git
synced 2026-09-01 17:57:27 +00:00
93d4b1ccc6
efactor init, prepare , and eval functions to be unique names for kernels who's name starts with the Letters N-Z BUG=[b/313963581](https://b.corp.google.com/issues/313963581)
118 lines
4.3 KiB
C++
118 lines
4.3 KiB
C++
/* Copyright 2020 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/quantization_util.h"
|
|
#include "tensorflow/lite/kernels/internal/reference/process_broadcast_shapes.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_log.h"
|
|
|
|
namespace tflite {
|
|
namespace {
|
|
|
|
struct SqueezeContext {
|
|
SqueezeContext(TfLiteContext* context, TfLiteNode* node) {
|
|
params = reinterpret_cast<TfLiteSqueezeParams*>(node->builtin_data);
|
|
micro_context = GetMicroContext(context);
|
|
input = micro_context->AllocateTempInputTensor(node, 0);
|
|
output = micro_context->AllocateTempOutputTensor(node, 0);
|
|
}
|
|
~SqueezeContext() {
|
|
micro_context->DeallocateTempTfLiteTensor(input);
|
|
micro_context->DeallocateTempTfLiteTensor(output);
|
|
}
|
|
MicroContext* micro_context;
|
|
TfLiteSqueezeParams* params;
|
|
TfLiteTensor* input;
|
|
TfLiteTensor* output;
|
|
};
|
|
|
|
TfLiteStatus SqueezePrepare(TfLiteContext* context, TfLiteNode* node) {
|
|
TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
|
|
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
|
|
|
|
SqueezeContext op_context(context, node);
|
|
const int input_num_dims = NumDimensions(op_context.input);
|
|
const int num_squeeze_dims = op_context.params->num_squeeze_dims;
|
|
|
|
// Determines number of dimensions of output tensor after squeeze.
|
|
const TfLiteIntArray* input_dims = op_context.input->dims;
|
|
const TfLiteIntArray* output_dims = op_context.output->dims;
|
|
const int32_t* squeeze_dims = op_context.params->squeeze_dims;
|
|
|
|
constexpr int max_squeeze_dims = 8;
|
|
TF_LITE_ENSURE(context, input_num_dims <= max_squeeze_dims);
|
|
bool should_squeeze[max_squeeze_dims] = {};
|
|
|
|
if (num_squeeze_dims == 0) {
|
|
for (int idx = 0; idx < input_num_dims; ++idx) {
|
|
if (input_dims->data[idx] == 1) {
|
|
should_squeeze[idx] = true;
|
|
}
|
|
}
|
|
} else {
|
|
for (int idx = 0; idx < num_squeeze_dims; ++idx) {
|
|
int current = squeeze_dims[idx] < 0 ? squeeze_dims[idx] + input_num_dims
|
|
: squeeze_dims[idx];
|
|
TF_LITE_ENSURE(context, current >= 0 && current < input_num_dims &&
|
|
input_dims->data[current] == 1);
|
|
should_squeeze[current] = true;
|
|
}
|
|
}
|
|
|
|
// Ensure output dimensions are big enough.
|
|
for (int in_idx = 0, out_idx = 0; in_idx < input_num_dims; ++in_idx) {
|
|
if (!should_squeeze[in_idx]) {
|
|
TFLITE_CHECK_GE(output_dims->data[out_idx++], input_dims->data[in_idx]);
|
|
}
|
|
}
|
|
|
|
return kTfLiteOk;
|
|
}
|
|
|
|
TfLiteStatus SqueezeEval(TfLiteContext* context, TfLiteNode* node) {
|
|
const TfLiteEvalTensor* input = tflite::micro::GetEvalInput(context, node, 0);
|
|
|
|
if (input->type == kTfLiteString) {
|
|
MicroPrintf("Type %s (%d) not supported.", TfLiteTypeGetName(input->type),
|
|
input->type);
|
|
return kTfLiteError;
|
|
}
|
|
|
|
TfLiteEvalTensor* output = tflite::micro::GetEvalOutput(context, node, 0);
|
|
size_t input_byte_size;
|
|
size_t output_byte_size;
|
|
TF_LITE_ENSURE_OK(context,
|
|
TfLiteEvalTensorByteLength(input, &input_byte_size));
|
|
TF_LITE_ENSURE_OK(context,
|
|
TfLiteEvalTensorByteLength(output, &output_byte_size));
|
|
|
|
TF_LITE_ENSURE_EQ(context, input_byte_size, output_byte_size);
|
|
memcpy(output->data.raw, input->data.raw, input_byte_size);
|
|
return kTfLiteOk;
|
|
}
|
|
|
|
} // namespace
|
|
|
|
TFLMRegistration Register_SQUEEZE() {
|
|
return tflite::micro::RegisterOp(nullptr, SqueezePrepare, SqueezeEval);
|
|
}
|
|
|
|
} // namespace tflite
|