50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
# 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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"""This module defines tensor utilities not found in TensorFlow.
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The reason these utilities are not defined in TensorFlow is because they may
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not be not fully robust, although they work in the vast majority of cases. So
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we define them here in order for their behavior to be consistently verified.
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"""
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import sparse_tensor
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from tensorflow.python.framework import tensor_util
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from tensorflow.python.ops import tensor_array_ops
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def is_dense_tensor(t):
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# TODO(mdan): Resolve this inconsistency.
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return (tensor_util.is_tf_type(t) and
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not isinstance(t, sparse_tensor.SparseTensor))
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def is_tensor_array(t):
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return isinstance(t, tensor_array_ops.TensorArray)
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def is_tensor_list(t):
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# TODO(mdan): This is just a heuristic.
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# With TF lacking support for templated types, this is unfortunately the
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# closest we can get right now. A dedicated op ought to be possible to
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# construct.
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return (tensor_util.is_tf_type(t) and t.dtype == dtypes.variant and
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not t.shape.ndims)
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def is_range_tensor(t):
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"""Returns True if a tensor is the result of a tf.range op. Best effort."""
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return tensor_util.is_tf_type(t) and hasattr(t, 'op') and t.op.type == 'Range'
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