77 lines
2.6 KiB
Python
77 lines
2.6 KiB
Python
# Copyright 2020 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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"""Ops to manipulate hashmap of tensors."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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# go/tf-wildcard-import
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# pylint: disable=wildcard-import
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from tensorflow.python.framework import ops
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from tensorflow.python.ops import array_ops
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from tensorflow.python.ops import control_flow_ops
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from tensorflow.python.ops import gen_map_ops
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from tensorflow.python.ops.gen_map_ops import *
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ops.NotDifferentiable("EmptyTensorMap")
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def empty_tensor_map():
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return gen_map_ops.empty_tensor_map()
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def tensor_map_size(input_handle):
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return gen_map_ops.tensor_map_size(input_handle)
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def tensor_map_insert(input_handle, key, value):
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return gen_map_ops.tensor_map_insert(input_handle, key, value)
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def tensor_map_lookup(input_handle, key, value_dtype):
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return gen_map_ops.tensor_map_lookup(input_handle, key, value_dtype)
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def tensor_map_erase(input_handle, key, value_dtype):
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return gen_map_ops.tensor_map_erase(input_handle, key, value_dtype)
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def tensor_map_has_key(input_handle, key):
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return gen_map_ops.tensor_map_has_key(input_handle, key)
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def tensor_map_stack_keys(input_handle, key_dtype):
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return gen_map_ops.tensor_map_stack_keys(input_handle, key_dtype)
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@ops.RegisterGradient("TensorMapLookup")
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def LookupGrad(op, dval):
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_, k = op.inputs
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map_grad = empty_tensor_map()
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map_grad = tensor_map_insert(map_grad, k, dval)
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key_grad = None
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return map_grad, key_grad
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@ops.RegisterGradient("TensorMapInsert")
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def InsertGrad(op, dmap):
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_, k, v = op.inputs
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key_grad = None
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(value_grad, map_grad) = control_flow_ops.cond(
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tensor_map_has_key(dmap, k), lambda:
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(tensor_map_lookup(dmap, k, v.dtype), tensor_map_erase(dmap, k, v.dtype)),
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lambda: (array_ops.zeros_like(v), dmap))
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return map_grad, key_grad, value_grad
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@ops.RegisterGradient("TensorMapErase")
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def EraseGrad(op, dmap):
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key_grad = None
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map_grad = dmap
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return map_grad, key_grad
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