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