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/framework/op.h" |
17 | #include "tensorflow/core/framework/op_kernel.h" |
18 | #include "tensorflow/core/framework/op_requires.h" |
19 | #include "tensorflow/core/framework/variant.h" |
20 | #include "tensorflow/core/framework/variant_encode_decode.h" |
21 | #include "tensorflow/core/kernels/composite_tensor_variant.h" |
22 | #include "tensorflow/core/platform/errors.h" |
23 | #include "tensorflow/core/protobuf/composite_tensor_variant.pb.h" |
24 | #include "tensorflow/core/protobuf/struct.pb.h" |
25 | |
26 | namespace tensorflow { |
27 | |
28 | class CompositeTensorVariantFromComponents : public OpKernel { |
29 | public: |
30 | explicit CompositeTensorVariantFromComponents(OpKernelConstruction* context) |
31 | : OpKernel(context) { |
32 | string type_spec_string; |
33 | OP_REQUIRES_OK(context, context->GetAttr("metadata" , &type_spec_string)); |
34 | OP_REQUIRES(context, metadata_.ParseFromString(type_spec_string), |
35 | errors::InvalidArgument("Error parsing metadata" )); |
36 | } |
37 | |
38 | void Compute(OpKernelContext* context) override { |
39 | OpInputList components_in; |
40 | OP_REQUIRES_OK(context, context->input_list("components" , &components_in)); |
41 | |
42 | Tensor* encoded; |
43 | OP_REQUIRES_OK(context, |
44 | context->allocate_output(0, TensorShape({}), &encoded)); |
45 | |
46 | std::vector<Tensor> components{components_in.begin(), components_in.end()}; |
47 | encoded->flat<Variant>()(0) = |
48 | CompositeTensorVariant(metadata_, absl::MakeSpan(components)); |
49 | } |
50 | |
51 | private: |
52 | CompositeTensorVariantMetadata metadata_; |
53 | }; |
54 | |
55 | class CompositeTensorVariantToComponents : public OpKernel { |
56 | public: |
57 | explicit CompositeTensorVariantToComponents(OpKernelConstruction* context) |
58 | : OpKernel(context) { |
59 | string type_spec_string; |
60 | OP_REQUIRES_OK(context, context->GetAttr("metadata" , &type_spec_string)); |
61 | OP_REQUIRES(context, metadata_.ParseFromString(type_spec_string), |
62 | errors::InvalidArgument("Error parsing `metadata`" )); |
63 | |
64 | OP_REQUIRES_OK(context, |
65 | context->GetAttr("Tcomponents" , &component_dtypes_)); |
66 | } |
67 | |
68 | void Compute(OpKernelContext* context) override { |
69 | Tensor encoded_t = context->input(0); |
70 | OP_REQUIRES( |
71 | context, encoded_t.flat<Variant>().size() > 0, |
72 | errors::InvalidArgument("Input `encoded` must not be an empty variant " |
73 | "tensor, but got " , |
74 | encoded_t.DebugString())); |
75 | auto* encoded = encoded_t.flat<Variant>()(0).get<CompositeTensorVariant>(); |
76 | OP_REQUIRES(context, encoded != nullptr, |
77 | errors::InvalidArgument("The input `encoded` is not a valid " |
78 | "CompositeTensorVariant tensor, got " , |
79 | encoded_t.DebugString())); |
80 | |
81 | // Check that the encoded TypeSpec is compatible with the expected TypeSpec. |
82 | // For now, we just check that the class matches. |
83 | // |
84 | // TODO(b/173744905): Update this to do a generic compatibility check. This |
85 | // would require replacing the current design, where Python subclasses of |
86 | // TypeSpec can override is_compatible, with a design where compatibility |
87 | // can be deterministically determined from the metadata. |
88 | auto expected_class = metadata_.type_spec_proto().type_spec_class(); |
89 | auto actual_class = encoded->metadata().type_spec_proto().type_spec_class(); |
90 | OP_REQUIRES( |
91 | context, expected_class == actual_class, |
92 | errors::InvalidArgument( |
93 | "Expected a " , TypeSpecProto::TypeSpecClass_Name(expected_class), |
94 | " (based on `type_spec`), but `encoded` contains a " , |
95 | TypeSpecProto::TypeSpecClass_Name(actual_class))); |
96 | |
97 | // Extract the component tensors. |
98 | OpOutputList components; |
99 | OP_REQUIRES_OK(context, context->output_list("components" , &components)); |
100 | int num_components = encoded->flat_components().size(); |
101 | |
102 | OP_REQUIRES(context, component_dtypes_.size() == num_components, |
103 | errors::InvalidArgument("Encoded value has " , num_components, |
104 | " tensor components; expected " , |
105 | component_dtypes_.size(), |
106 | " components based on type_spec" )); |
107 | |
108 | for (int i = 0; i < component_dtypes_.size(); i++) { |
109 | const Tensor& component = encoded->flat_components()[i]; |
110 | OP_REQUIRES(context, component_dtypes_[i] == component.dtype(), |
111 | errors::InvalidArgument("Tensor component " , i, " had dtype " , |
112 | DataType_Name(component.dtype()), |
113 | "; expected dtype " , |
114 | DataType_Name(component_dtypes_[i]))); |
115 | components.set(i, component); |
116 | } |
117 | } |
118 | |
119 | private: |
120 | CompositeTensorVariantMetadata metadata_; |
121 | std::vector<DataType> component_dtypes_; |
122 | }; |
123 | |
124 | REGISTER_KERNEL_BUILDER( |
125 | Name("CompositeTensorVariantToComponents" ).Device(DEVICE_CPU), |
126 | CompositeTensorVariantToComponents); |
127 | REGISTER_KERNEL_BUILDER( |
128 | Name("CompositeTensorVariantFromComponents" ).Device(DEVICE_CPU), |
129 | CompositeTensorVariantFromComponents); |
130 | |
131 | } // namespace tensorflow |
132 | |