1 | /* Copyright 2020 The TensorFlow Authors. All Rights Reserved. |
2 | |
3 | Licensed under the Apache License, Version 2.0 (the "License"); |
4 | you may not use this file except in compliance with the License. |
5 | You may obtain a copy of the License at |
6 | |
7 | http://www.apache.org/licenses/LICENSE-2.0 |
8 | |
9 | Unless required by applicable law or agreed to in writing, software |
10 | distributed under the License is distributed on an "AS IS" BASIS, |
11 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
12 | See the License for the specific language governing permissions and |
13 | limitations under the License. |
14 | ==============================================================================*/ |
15 | |
16 | #include "tensorflow/core/kernels/tensor_map.h" |
17 | |
18 | #include "tensorflow/core/framework/tensor_shape.h" |
19 | #include "tensorflow/core/framework/tensor_shape.pb.h" |
20 | #include "tensorflow/core/framework/variant_op_registry.h" |
21 | #include "tensorflow/core/lib/core/coding.h" |
22 | |
23 | namespace tensorflow { |
24 | |
25 | TensorMap::~TensorMap() { |
26 | if (tensors_) tensors_->Unref(); |
27 | } |
28 | |
29 | void TensorMap::Encode(VariantTensorData* data) const { |
30 | data->set_type_name(TypeName()); |
31 | |
32 | absl::flat_hash_map<TensorKey, Tensor>::const_iterator map_it = |
33 | tensors().begin(); |
34 | while (map_it != tensors().end()) { |
35 | Tensor k = map_it->first; |
36 | Tensor v = map_it->second; |
37 | // TODO: k should also not be DT_RESOURCE or DT_VARIANT |
38 | CHECK_NE(k.dtype(), DT_INVALID); |
39 | CHECK_NE(v.dtype(), DT_INVALID); |
40 | *data->add_tensors() = k; |
41 | *data->add_tensors() = v; |
42 | map_it++; |
43 | } |
44 | } |
45 | |
46 | static Status TensorMapDeviceCopy( |
47 | const TensorMap& from, TensorMap* to, |
48 | const UnaryVariantOpRegistry::AsyncTensorDeviceCopyFn& copy) { |
49 | for (const std::pair<TensorKey, Tensor>& p : from.tensors()) { |
50 | TensorKey to_key(p.first.dtype()); |
51 | Tensor to_val(p.second.dtype()); |
52 | TF_RETURN_IF_ERROR(copy(p.first, &to_key)); |
53 | TF_RETURN_IF_ERROR(copy(p.second, &to_val)); |
54 | to->tensors().emplace(to_key, to_val); |
55 | } |
56 | return OkStatus(); |
57 | } |
58 | |
59 | #define REGISTER_LIST_COPY(DIRECTION) \ |
60 | INTERNAL_REGISTER_UNARY_VARIANT_DEVICE_COPY_FUNCTION(TensorMap, DIRECTION, \ |
61 | TensorMapDeviceCopy) |
62 | |
63 | REGISTER_LIST_COPY(VariantDeviceCopyDirection::HOST_TO_DEVICE); |
64 | REGISTER_LIST_COPY(VariantDeviceCopyDirection::DEVICE_TO_HOST); |
65 | REGISTER_LIST_COPY(VariantDeviceCopyDirection::DEVICE_TO_DEVICE); |
66 | |
67 | REGISTER_UNARY_VARIANT_DECODE_FUNCTION(TensorMap, TensorMap::kTypeName); |
68 | |
69 | bool TensorMap::Decode(const VariantTensorData& data) { |
70 | // TODO(srbs): Change the signature to Decode(VariantTensorData data) so |
71 | // that we do not have to copy each tensor individually below. This would |
72 | // require changing VariantTensorData::tensors() as well. |
73 | std::vector<Tensor>::const_iterator tensors_it = data.tensors().begin(); |
74 | |
75 | while (tensors_it != data.tensors().end()) { |
76 | if (std::next(tensors_it) == data.tensors().end()) { |
77 | return false; |
78 | } |
79 | tensors().emplace(tensors_it[0], tensors_it[1]); |
80 | tensors_it += 2; |
81 | } |
82 | return true; |
83 | } |
84 | |
85 | const char TensorMap::kTypeName[] = "tensorflow::TensorMap" ; |
86 | |
87 | } // namespace tensorflow |
88 | |