128 lines
3.9 KiB
Python
128 lines
3.9 KiB
Python
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# Copyright 2018 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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"""Utilities related to disk I/O."""
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import os
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import sys
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import threading
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from absl import logging
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from keras.utils import keras_logging
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# isort: off
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from tensorflow.python.util.tf_export import keras_export
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INTERACTIVE_LOGGING = threading.local()
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INTERACTIVE_LOGGING.enable = keras_logging.INTERACTIVE_LOGGING_DEFAULT
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@keras_export("keras.utils.enable_interactive_logging")
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def enable_interactive_logging():
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"""Turn on interactive logging.
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When interactive logging is enabled, Keras displays logs via stdout.
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This provides the best experience when using Keras in an interactive
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environment such as a shell or a notebook.
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"""
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INTERACTIVE_LOGGING.enable = True
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@keras_export("keras.utils.disable_interactive_logging")
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def disable_interactive_logging():
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"""Turn off interactive logging.
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When interactive logging is disabled, Keras sends logs to `absl.logging`.
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This is the best option when using Keras in a non-interactive
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way, such as running a training or inference job on a server.
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"""
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INTERACTIVE_LOGGING.enable = False
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@keras_export("keras.utils.is_interactive_logging_enabled")
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def is_interactive_logging_enabled():
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"""Check if interactive logging is enabled.
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To switch between writing logs to stdout and `absl.logging`, you may use
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`keras.utils.enable_interactive_logging()` and
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`keras.utils.disable_interactie_logging()`.
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Returns:
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Boolean (True if interactive logging is enabled and False otherwise).
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"""
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# Use `getattr` in case `INTERACTIVE_LOGGING`
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# does not have the `enable` attribute.
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return getattr(
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INTERACTIVE_LOGGING, "enable", keras_logging.INTERACTIVE_LOGGING_DEFAULT
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)
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def print_msg(message, line_break=True):
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"""Print the message to absl logging or stdout."""
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if is_interactive_logging_enabled():
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if line_break:
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sys.stdout.write(message + "\n")
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else:
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sys.stdout.write(message)
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sys.stdout.flush()
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else:
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logging.info(message)
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def path_to_string(path):
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"""Convert `PathLike` objects to their string representation.
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If given a non-string typed path object, converts it to its string
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representation.
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If the object passed to `path` is not among the above, then it is
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returned unchanged. This allows e.g. passthrough of file objects
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through this function.
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Args:
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path: `PathLike` object that represents a path
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Returns:
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A string representation of the path argument, if Python support exists.
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"""
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if isinstance(path, os.PathLike):
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return os.fspath(path)
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return path
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def ask_to_proceed_with_overwrite(filepath):
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"""Produces a prompt asking about overwriting a file.
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Args:
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filepath: the path to the file to be overwritten.
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Returns:
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True if we can proceed with overwrite, False otherwise.
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"""
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overwrite = (
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input(f"[WARNING] {filepath} already exists - overwrite? [y/n]")
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.strip()
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.lower()
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)
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while overwrite not in ("y", "n"):
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overwrite = (
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input('Enter "y" (overwrite) or "n" (cancel).').strip().lower()
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)
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if overwrite == "n":
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return False
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print_msg("[TIP] Next time specify overwrite=True!")
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return True
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