b885fb44dd
This change: * Improved the per-op profiling to the interpreter. * Maintains state within the MicroProfiler object such that all the logging can happen external to the interpreter. * Refactors the benchmarks to make use of this new functionality.
37 lines
1.3 KiB
C++
37 lines
1.3 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_MICRO_MICRO_TIME_H_
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#define TENSORFLOW_LITE_MICRO_MICRO_TIME_H_
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#include <cstdint>
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namespace tflite {
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// These functions should be implemented by each target platform, and provide an
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// accurate tick count along with how many ticks there are per second.
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int32_t ticks_per_second();
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// Return time in ticks. The meaning of a tick varies per platform.
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int32_t GetCurrentTimeTicks();
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inline int32_t TicksToMs(int32_t ticks) {
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return static_cast<int32_t>(1000.0f * static_cast<float>(ticks) /
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static_cast<float>(ticks_per_second()));
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}
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} // namespace tflite
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#endif // TENSORFLOW_LITE_MICRO_MICRO_TIME_H_
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