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81 lines
2.9 KiB
Python
81 lines
2.9 KiB
Python
# Copyright 2019 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 for computing default gradients."""
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import tensor_shape
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from tensorflow.python.ops import array_ops
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from tensorflow.python.ops import resource_variable_ops
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def get_zeros_dtype(t):
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"""Return the dtype for the default gradient for a Tensor."""
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if t.dtype == dtypes.resource:
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handle_data = resource_variable_ops.get_eager_safe_handle_data(t)
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if (handle_data is None or not handle_data.is_set or
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len(handle_data.shape_and_type) != 1):
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raise ValueError("Internal error: Tried to take gradients (or similar) "
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"of a variable without handle data:\n%s" % str(t))
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return handle_data.shape_and_type[0].dtype
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return t.dtype
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def shape_and_dtype(t):
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"""Return the shape and dtype for the default gradient for a Tensor."""
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if t.dtype == dtypes.resource:
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handle_data = resource_variable_ops.get_eager_safe_handle_data(t)
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if (handle_data is None or not handle_data.is_set or
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len(handle_data.shape_and_type) != 1):
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raise ValueError("Internal error: Tried to take gradients (or similar) "
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"of a variable without handle data:\n%s" % str(t))
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shape_and_type = handle_data.shape_and_type[0]
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return (tensor_shape.TensorShape(shape_and_type.shape),
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dtypes.as_dtype(shape_and_type.dtype))
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return t.shape, t.dtype
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def zeros_like(t):
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"""Like array_ops.zeros_like, but respects resource handles."""
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if t.dtype == dtypes.resource:
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return array_ops.zeros(*shape_and_dtype(t))
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else:
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return array_ops.zeros_like(t)
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def ones_like(t):
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"""Like array_ops.ones_like, but respects resource handles."""
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if t.dtype == dtypes.resource:
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return array_ops.ones(*shape_and_dtype(t))
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else:
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return array_ops.ones_like(t)
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def supports_default_grad(t):
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"""Whether tensor `t` supports creating a default gradient.
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This function assumes that `t` is of a trainable type.
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Args:
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t: Tensor
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Returns:
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Bool
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"""
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if t.dtype == dtypes.resource:
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handle_data = resource_variable_ops.get_eager_safe_handle_data(t)
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if (handle_data is None or not handle_data.is_set or
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len(handle_data.shape_and_type) != 1):
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return False
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return True
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