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67 lines (60 loc) · 2.75 KB
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# Copyright 2017 The TensorFlow 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
# 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.
# ==============================================================================
"""Helpers constructing Datasets."""
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
def optional_param_to_tensor(argument_name,
argument_value,
argument_default=0,
argument_dtype=dtypes.int64):
if argument_value is not None:
return ops.convert_to_tensor(
argument_value, dtype=argument_dtype, name=argument_name)
else:
return constant_op.constant(
argument_default, dtype=argument_dtype, name=argument_name)
def partial_shape_to_tensor(shape_like):
"""Returns a `tf.Tensor` that represents the given shape.
Args:
shape_like: A value that can be converted to a `tf.TensorShape` or a
`tf.Tensor`.
Returns:
A 1-D `tf.Tensor` of `tf.int64` elements representing the given shape, where
`-1` is substituted for any unknown dimensions.
"""
try:
# First attempt to convert the input to a shape, and return the
# "canonical" tensor representation, which uses `-1` in place of
# `None`.
shape_like = tensor_shape.as_shape(shape_like)
return ops.convert_to_tensor(
[dim if dim is not None else -1 for dim in shape_like.as_list()],
dtype=dtypes.int64)
except (TypeError, ValueError):
# The argument was not trivially convertible to a
# `tf.TensorShape`, so fall back on the conversion to tensor
# machinery.
ret = ops.convert_to_tensor(shape_like, preferred_dtype=dtypes.int64)
if ret.shape.dims is not None and len(ret.shape.dims) != 1:
raise ValueError("The given shape {} must be a 1-D tensor of `tf.int64` "
"values, but the shape was {}.".format(
shape_like, ret.shape))
if ret.dtype != dtypes.int64:
raise TypeError("The given shape {} must be a 1-D tensor of `tf.int64` "
"values, but the element type was {}.".format(
shape_like, ret.dtype.name))
return ret