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tf_utils.py
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tf_utils.py
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# 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
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Diverse TensorFlow utils, for training, evaluation and so on!
"""
import tensorflow as tf
slim = tf.contrib.slim
# =========================================================================== #
# General tools.
# =========================================================================== #
def reshape_list(l, shape=None):
"""Reshape list of (list): 1D to 2D or the other way around.
Args:
l: List or List of list.
shape: 1D or 2D shape.
Return
Reshaped list.
"""
r = []
if shape is None:
# Flatten everything.
for a in l:
if isinstance(a, (list, tuple)):
r = r + list(a)
else:
r.append(a)
else:
# Reshape to list of list.
i = 0
for s in shape:
if s == 1:
r.append(l[i])
else:
r.append(l[i:i+s])
i += s
return r
def pad_list_fixed_size(l, size=20):
r = []
n = tf.shape(l)[0]
if len(l.get_shape()) == 1:
paddings = [[0, 0], [0, size-n]]
r = tf.reshape(l, [n, 1])
r = tf.pad(r, paddings, 'CONSTANT', constant_values=-1)
r = tf.reshape(r, [size])
elif len(l.get_shape()) == 2:
paddings = [[0, 0], [0, size-n]]
r = tf.pad(l, paddings, 'CONSTANT', constant_values=-1)
r = tf.reshape(r, [size, 4])
return r