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 | #ifndef TENSORFLOW_CORE_FRAMEWORK_OP_REQUIRES_H_ |
17 | #define TENSORFLOW_CORE_FRAMEWORK_OP_REQUIRES_H_ |
18 | |
19 | #include "tensorflow/core/platform/macros.h" |
20 | |
21 | namespace tensorflow { |
22 | |
23 | // Convenience macros for asserting and handling exceptional conditions. |
24 | // Analogous to the CHECK* macros provided by logging.h. |
25 | // |
26 | // Example use: |
27 | // void Compute(OperationContext* context) { |
28 | // OP_REQUIRES(context, context->num_inputs() == 2, |
29 | // errors::InvalidArgument("FooOp requires 2 arguments")); |
30 | // ... |
31 | // Status status = SomeUncertainMethod(); |
32 | // OP_REQUIRES_OK(context, status); |
33 | // ... |
34 | // } |
35 | // |
36 | // These macros depend on CheckNotInComputeAsync, which must be defined before |
37 | // invoking the macro. We specifically don't include op_kernel.h from this |
38 | // header to reduce this header's dependencies. These macros may be used with |
39 | // alternative implementations of OpKernelContext with fewer dependencies. |
40 | |
41 | #define OP_REQUIRES(CTX, EXP, STATUS) \ |
42 | do { \ |
43 | if (!TF_PREDICT_TRUE(EXP)) { \ |
44 | CheckNotInComputeAsync((CTX), "OP_REQUIRES_ASYNC"); \ |
45 | (CTX)->CtxFailure(__FILE__, __LINE__, (STATUS)); \ |
46 | return; \ |
47 | } \ |
48 | } while (0) |
49 | |
50 | #define OP_REQUIRES_OK(CTX, ...) \ |
51 | do { \ |
52 | ::tensorflow::Status _s(__VA_ARGS__); \ |
53 | if (!TF_PREDICT_TRUE(_s.ok())) { \ |
54 | CheckNotInComputeAsync((CTX), "OP_REQUIRES_OK_ASYNC"); \ |
55 | (CTX)->CtxFailureWithWarning(__FILE__, __LINE__, _s); \ |
56 | return; \ |
57 | } \ |
58 | } while (0) |
59 | |
60 | #define OP_REQUIRES_OK_OR_SET_PAYLOAD(CTX, PAYLOAD_KEY, PAYLOAD_VALUE, STATUS) \ |
61 | do { \ |
62 | if (!TF_PREDICT_TRUE(STATUS.ok())) { \ |
63 | CheckNotInComputeAsync((CTX), "OP_REQUIRES_OK_ASYNC"); \ |
64 | if (!PAYLOAD_VALUE.empty()) { \ |
65 | STATUS.SetPayload(PAYLOAD_KEY, PAYLOAD_VALUE); \ |
66 | } \ |
67 | (CTX)->CtxFailureWithWarning(__FILE__, __LINE__, STATUS); \ |
68 | return; \ |
69 | } \ |
70 | } while (0) |
71 | |
72 | #define OP_REQUIRES_ASYNC(CTX, EXP, STATUS, CALLBACK) \ |
73 | do { \ |
74 | if (!TF_PREDICT_TRUE(EXP)) { \ |
75 | (CTX)->CtxFailure(__FILE__, __LINE__, (STATUS)); \ |
76 | (CALLBACK)(); \ |
77 | return; \ |
78 | } \ |
79 | } while (0) |
80 | |
81 | #define OP_REQUIRES_OK_ASYNC(CTX, STATUS, CALLBACK) \ |
82 | do { \ |
83 | const ::tensorflow::Status& _s(STATUS); \ |
84 | if (!TF_PREDICT_TRUE(_s.ok())) { \ |
85 | (CTX)->CtxFailureWithWarning(__FILE__, __LINE__, _s); \ |
86 | (CALLBACK)(); \ |
87 | return; \ |
88 | } \ |
89 | } while (0) |
90 | |
91 | #define OP_REQUIRES_VALUE(lhs, ctx, rexpr) \ |
92 | OP_REQUIRES_VALUE_IMPL( \ |
93 | TF_STATUS_MACROS_CONCAT_NAME(_status_or_value, __COUNTER__), lhs, ctx, \ |
94 | rexpr) |
95 | |
96 | #define OP_REQUIRES_VALUE_IMPL(statusor, lhs, ctx, rexpr) \ |
97 | auto statusor = (rexpr); \ |
98 | OP_REQUIRES_OK(ctx, statusor.status()); \ |
99 | lhs = std::move(statusor.value()) |
100 | |
101 | } // namespace tensorflow |
102 | |
103 | #endif // TENSORFLOW_CORE_FRAMEWORK_OP_REQUIRES_H_ |
104 | |