Source code for texar.utils.mode

# Copyright 2018 The Texar Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
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"""
Utility functions related to mode.
"""

from __future__ import absolute_import
from __future__ import print_function
from __future__ import division

import tensorflow as tf

from texar import context

__all__ = [
    "maybe_global_mode",
    "is_train_mode",
    "is_eval_mode",
    "is_predict_mode",
    "is_train_mode_py",
    "is_eval_mode_py",
    "is_predict_mode_py",
    "switch_dropout"
]

[docs]def maybe_global_mode(mode): """Returns :func:`texar.global_mode` if :attr:`mode` is `None`, otherwise returns :attr:`mode` as-is. """ if mode is None: return context.global_mode() else: return mode
[docs]def is_train_mode(mode): """Returns a bool Tensor indicating whether the global mode is TRAIN. If :attr:`mode` is `None`, the mode is determined by :func:`texar.global_mode`. """ if mode is None: return context.global_mode_train() else: return tf.equal(mode, tf.estimator.ModeKeys.TRAIN)
[docs]def is_eval_mode(mode): """Returns a bool Tensor indicating whether the global mode is EVAL. If :attr:`mode` is `None`, the mode is determined by :func:`texar.global_mode`. """ if mode is None: return context.global_mode_eval() else: return tf.equal(mode, tf.estimator.ModeKeys.EVAL)
[docs]def is_predict_mode(mode): """Returns a bool Tensor indicating whether the global mode is PREDICT. If :attr:`mode` is `None`, the mode is determined by :func:`texar.global_mode`. """ if mode is None: return context.global_mode_predict() else: return tf.equal(mode, tf.estimator.ModeKeys.PREDICT)
[docs]def is_train_mode_py(mode, default=True): """Returns a python boolean indicating whether the mode is TRAIN. Args: mode: A string taking value in :tf_main:`tf.estimator.ModeKeys <estimator/ModeKeys>`. Can be `None`. default (bool): The return value when :attr:`mode` is `None`. Default is `True`. Returns: A python boolean. """ if mode is None: return default if mode not in context.valid_modes(): raise ValueError('Unknown mode: {}'.format(mode)) return mode == tf.estimator.ModeKeys.TRAIN
[docs]def is_eval_mode_py(mode, default=False): """Returns a python boolean indicating whether the mode is EVAL. Args: mode: A string taking value in :tf_main:`tf.estimator.ModeKeys <estimator/ModeKeys>`. Can be `None`. default (bool): The return value when :attr:`mode` is `None`. Default is `False`. Returns: A python boolean. """ if mode is None: return default if mode not in context.valid_modes(): raise ValueError('Unknown mode: {}'.format(mode)) return mode == tf.estimator.ModeKeys.EVAL
[docs]def is_predict_mode_py(mode, default=False): """Returns a python boolean indicating whether the mode is PREDICT. Args: mode: A string taking value in :tf_main:`tf.estimator.ModeKeys <estimator/ModeKeys>`. Can be `None`. default (bool): The return value when :attr:`mode` is `None`. Default is `False`. Returns: A python boolean. """ if mode is None: return default if mode not in context.valid_modes(): raise ValueError('Unknown mode: {}'.format(mode)) return mode == tf.estimator.ModeKeys.PREDICT
[docs]def switch_dropout(dropout_keep_prob, mode=None): """Turns off dropout when not in training mode. Args: dropout_keep_prob: Dropout keep probability in training mode mode (optional): A Tensor taking values of :tf_main:`tf.estimator.ModeKeys <estimator/ModeKeys>`. Dropout is activated if :attr:`mode` is `TRAIN`. If `None`, the mode is inferred from :func:`texar.global_mode`. Returns: A unit Tensor that equals the dropout keep probability in `TRAIN` mode, and `1.0` in other modes. """ return 1. - (1. - dropout_keep_prob) * tf.to_float(is_train_mode(mode))