wehub-resource-sync
61 lines
2.4 KiB
C++
61 lines
2.4 KiB
C++
/* Copyright 2018 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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// Loads the input tflite file into interpreter, serializes it back to a tflite
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// buffer, and then verifies that the generated output can be loaded back into
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// an interpreter and the model prepared (i.e., AllocateTensors returns ok).
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//
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// Usage:
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// writer_test <input tflite>
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#include <cstddef>
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#include <cstdint>
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#include <cstdio>
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#include <memory>
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#include "tensorflow/lite/c/c_api_types.h"
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#include "tensorflow/lite/core/interpreter_builder.h"
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#include "tensorflow/lite/core/kernels/register.h"
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#include "tensorflow/lite/interpreter.h"
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#include "tensorflow/lite/model_builder.h"
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#include "tensorflow/lite/tools/serialization/writer_lib.h"
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int main(int argc, char* argv[]) {
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if (argc != 2) {
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fprintf(stderr, "Usage: %s input_file\n", argv[0]);
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return 1;
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}
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std::unique_ptr<tflite::FlatBufferModel> model =
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tflite::FlatBufferModel::BuildFromFile(argv[1]);
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std::unique_ptr<tflite::Interpreter> interpreter;
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tflite::ops::builtin::BuiltinOpResolverWithoutDefaultDelegates
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builtin_op_resolver;
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tflite::InterpreterBuilder(*model, builtin_op_resolver)(&interpreter);
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tflite::ModelWriter writer(interpreter.get());
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std::unique_ptr<uint8_t[]> output_buffer;
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size_t output_buffer_size;
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writer.GetBuffer(&output_buffer, &output_buffer_size);
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// Verify the generated model.
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std::unique_ptr<tflite::Interpreter> new_interpreter;
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model = tflite::FlatBufferModel::BuildFromBuffer(
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reinterpret_cast<char*>(output_buffer.get()), output_buffer_size);
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tflite::InterpreterBuilder(*model, builtin_op_resolver)(&new_interpreter);
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if (new_interpreter->AllocateTensors() != kTfLiteOk) {
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fprintf(stderr, "AllocateTensors failed on the round-tripped model.\n");
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return 1;
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}
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return 0;
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}
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