wehub-resource-sync
108 lines
3.5 KiB
C++
108 lines
3.5 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/lite/python/testdata/test_registerer.h"
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#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
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#include "tensorflow/lite/kernels/kernel_util.h"
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namespace tflite {
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namespace {
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static int num_test_registerer_calls = 0;
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TfLiteRegistration* GetFakeRegistration() {
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static TfLiteRegistration fake_op;
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return &fake_op;
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}
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namespace double_op {
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constexpr int kInputTensor = 0;
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constexpr int kOutputTensor = 0;
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TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
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TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
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TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
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const TfLiteTensor* input;
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TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input));
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TfLiteTensor* output;
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TF_LITE_ENSURE_OK(context,
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GetOutputSafe(context, node, kOutputTensor, &output));
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TfLiteIntArray* output_shape = TfLiteIntArrayCopy(input->dims);
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TF_LITE_ENSURE_TYPES_EQ(context, output->type, input->type);
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return context->ResizeTensor(context, output, output_shape);
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}
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TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
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const TfLiteTensor* input;
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TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input));
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TfLiteTensor* output;
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TF_LITE_ENSURE_OK(context,
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GetOutputSafe(context, node, kOutputTensor, &output));
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TF_LITE_ENSURE_TYPES_EQ(context, output->type, input->type);
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const size_t size = GetTensorShape(input).FlatSize();
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if (input->type == kTfLiteFloat32) {
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const float* input_ptr = input->data.f;
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float* output_ptr = output->data.f;
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for (int i = 0; i < size; ++i) {
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output_ptr[i] = input_ptr[i] + input_ptr[i];
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}
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} else if (input->type == kTfLiteInt32) {
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const int32_t* input_ptr = input->data.i32;
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int32_t* output_ptr = output->data.i32;
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for (int i = 0; i < size; ++i) {
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output_ptr[i] = input_ptr[i] + input_ptr[i];
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}
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} else {
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return kTfLiteError;
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}
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return kTfLiteOk;
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}
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} // namespace double_op
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TfLiteRegistration* GetDoubleRegistration() {
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static TfLiteRegistration double_op = {nullptr, nullptr, double_op::Prepare,
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double_op::Eval};
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return &double_op;
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}
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} // namespace
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// Dummy registerer function with the correct signature. Registers a fake custom
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// op needed by test models. Increments the num_test_registerer_calls counter by
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// one. The TF_ prefix is needed to get past the version script in the OSS
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// build.
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extern "C" void TF_TestRegisterer(tflite::MutableOpResolver *resolver) {
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resolver->AddCustom("FakeOp", GetFakeRegistration());
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resolver->AddCustom("Double", GetDoubleRegistration());
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num_test_registerer_calls++;
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}
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// Returns the num_test_registerer_calls counter and re-sets it.
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int get_num_test_registerer_calls() {
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const int result = num_test_registerer_calls;
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num_test_registerer_calls = 0;
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return result;
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}
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} // namespace tflite
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