56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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import time
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import numpy as np
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import tensorflow as tf
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import horovod.tensorflow as hvd
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from utils.parse_results import process_performance_stats
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class ProfilingHook(tf.estimator.SessionRunHook):
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def __init__(self, logger, batch_size, log_every, warmup_steps, mode):
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self._log_every = log_every
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self._warmup_steps = warmup_steps
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self._current_step = 0
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self._global_batch_size = batch_size * hvd.size()
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self._t0 = 0
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self._timestamps = []
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self.logger = logger
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self.mode = mode
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def before_run(self, run_context):
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if self._current_step > self._warmup_steps:
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self._t0 = time.time()
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def after_run(self,
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run_context,
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run_values):
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if self._current_step > self._warmup_steps:
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self._timestamps.append(time.time() - self._t0)
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self._current_step += 1
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def begin(self):
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pass
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def end(self, session):
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if hvd.rank() == 0:
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stats = process_performance_stats(np.array(self._timestamps),
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self._global_batch_size,
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self.mode)
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self.logger.log(step=(), data=stats)
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