This is for addressing the builtin code shortage problem. PiperOrigin-RevId: 336083510 Change-Id: I0ca615ed0893e948ad6299221117e2c59f81cdba
50 lines
2.0 KiB
C++
50 lines
2.0 KiB
C++
/* Copyright 2020 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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#ifndef TENSORFLOW_LITE_SCHEMA_SCHEMA_UTILS_H_
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#define TENSORFLOW_LITE_SCHEMA_SCHEMA_UTILS_H_
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#include "flatbuffers/flatbuffers.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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namespace tflite {
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// The following methods are introduced to resolve op builtin code shortage
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// problem. The new builtin opreator will be assigned to the extended builtin
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// code field in the flatbuffer schema. Those methods helps to hide builtin code
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// details.
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BuiltinOperator GetBuiltinCode(const OperatorCode *op_code);
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BuiltinOperator GetBuiltinCode(const OperatorCodeT *op_code);
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int8_t ConvertBuiltinCodeToDeprecatedBuiltinCode(
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const BuiltinOperator builtin_code);
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// The following methods are for backward compatibility for the early version
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// three, which does not have an extended builtin code.
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flatbuffers::Offset<OperatorCode> CreateOperatorCode(
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flatbuffers::FlatBufferBuilder &_fbb,
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BuiltinOperator builtin_code = BuiltinOperator_ADD,
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flatbuffers::Offset<flatbuffers::String> custom_code = 0,
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int32_t version = 1);
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flatbuffers::Offset<OperatorCode> CreateOperatorCodeDirect(
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flatbuffers::FlatBufferBuilder &_fbb,
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BuiltinOperator builtin_code = BuiltinOperator_ADD,
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const char *custom_code = nullptr, int32_t version = 1);
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} // namespace tflite
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#endif // TENSORFLOW_LITE_SCHEMA_SCHEMA_UTILS_H_
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