146 lines
4.0 KiB
Python
146 lines
4.0 KiB
Python
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# Copyright 2017 The TensorFlow Authors. 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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# ==============================================================================
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"""Logging and debugging utilities."""
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import os
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import sys
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import traceback
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# TODO(mdan): Use a custom logger class.
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from tensorflow.python.platform import tf_logging as logging
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from tensorflow.python.util.tf_export import tf_export
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VERBOSITY_VAR_NAME = 'AUTOGRAPH_VERBOSITY'
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DEFAULT_VERBOSITY = 0
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verbosity_level = None # vlog-like. Takes precedence over the env variable.
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echo_log_to_stdout = False
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# In interactive Python, logging echo is enabled by default.
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if hasattr(sys, 'ps1') or hasattr(sys, 'ps2'):
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echo_log_to_stdout = True
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@tf_export('autograph.set_verbosity')
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def set_verbosity(level, alsologtostdout=False):
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"""Sets the AutoGraph verbosity level.
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_Debug logging in AutoGraph_
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More verbose logging is useful to enable when filing bug reports or doing
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more in-depth debugging.
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There are two means to control the logging verbosity:
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* The `set_verbosity` function
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* The `AUTOGRAPH_VERBOSITY` environment variable
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`set_verbosity` takes precedence over the environment variable.
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For example:
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```python
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import os
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import tensorflow as tf
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os.environ['AUTOGRAPH_VERBOSITY'] = '5'
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# Verbosity is now 5
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tf.autograph.set_verbosity(0)
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# Verbosity is now 0
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os.environ['AUTOGRAPH_VERBOSITY'] = '1'
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# No effect, because set_verbosity was already called.
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```
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Logs entries are output to [absl](https://abseil.io)'s
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[default output](https://abseil.io/docs/python/guides/logging),
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with `INFO` level.
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Logs can be mirrored to stdout by using the `alsologtostdout` argument.
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Mirroring is enabled by default when Python runs in interactive mode.
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Args:
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level: int, the verbosity level; larger values specify increased verbosity;
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0 means no logging. When reporting bugs, it is recommended to set this
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value to a larger number, like 10.
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alsologtostdout: bool, whether to also output log messages to `sys.stdout`.
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"""
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global verbosity_level
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global echo_log_to_stdout
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verbosity_level = level
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echo_log_to_stdout = alsologtostdout
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@tf_export('autograph.trace')
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def trace(*args):
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"""Traces argument information at compilation time.
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`trace` is useful when debugging, and it always executes during the tracing
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phase, that is, when the TF graph is constructed.
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_Example usage_
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```python
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import tensorflow as tf
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for i in tf.range(10):
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tf.autograph.trace(i)
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# Output: <Tensor ...>
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```
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Args:
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*args: Arguments to print to `sys.stdout`.
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"""
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print(*args)
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def get_verbosity():
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global verbosity_level
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if verbosity_level is not None:
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return verbosity_level
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return int(os.getenv(VERBOSITY_VAR_NAME, DEFAULT_VERBOSITY))
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def has_verbosity(level):
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return get_verbosity() >= level
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def _output_to_stdout(msg, *args, **kwargs):
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print(msg % args)
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if kwargs.get('exc_info', False):
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traceback.print_exc()
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def error(level, msg, *args, **kwargs):
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if has_verbosity(level):
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logging.error(msg, *args, **kwargs)
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if echo_log_to_stdout:
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_output_to_stdout('ERROR: ' + msg, *args, **kwargs)
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def log(level, msg, *args, **kwargs):
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if has_verbosity(level):
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logging.info(msg, *args, **kwargs)
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if echo_log_to_stdout:
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_output_to_stdout(msg, *args, **kwargs)
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def warning(msg, *args, **kwargs):
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logging.warning(msg, *args, **kwargs)
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if echo_log_to_stdout:
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_output_to_stdout('WARNING: ' + msg, *args, **kwargs)
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sys.stdout.flush()
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