forked from huawei/mindspore2022
69 lines
2.3 KiB
Python
69 lines
2.3 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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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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# ============================================================================
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"""TimeMonitor Callback class."""
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import time
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from ._callback import Callback
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class TimeMonitor(Callback):
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"""
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Monitor the time in training.
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Args:
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data_size (int): How many steps are the intervals between print information each time.
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if the program get `batch_num` during training, `data_size` will be set to `batch_num`,
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otherwise `data_size` will be used. Default: None.
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Raises:
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ValueError: If data_size is not positive int.
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"""
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def __init__(self, data_size=None):
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super(TimeMonitor, self).__init__()
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self.data_size = data_size
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self.epoch_time = time.time()
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def epoch_begin(self, run_context):
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"""
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Record time at the begin of epoch.
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Args:
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run_context (RunContext): Context of the process running.
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"""
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self.epoch_time = time.time()
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def epoch_end(self, run_context):
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"""
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Print process cost time at the end of epoch.
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Args:
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run_context (RunContext): Context of the process running.
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"""
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epoch_seconds = (time.time() - self.epoch_time) * 1000
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step_size = self.data_size
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cb_params = run_context.original_args()
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if hasattr(cb_params, "batch_num"):
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batch_num = cb_params.batch_num
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if isinstance(batch_num, int) and batch_num > 0:
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step_size = cb_params.batch_num
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if not isinstance(step_size, int) or step_size < 1:
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raise ValueError("data_size must be positive int.")
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step_seconds = epoch_seconds / step_size
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print("epoch time: {:5.3f} ms, per step time: {:5.3f} ms".format(epoch_seconds, step_seconds), flush=True)
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