1 /* Copyright 2018 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 #include <stddef.h>
16
17 #include "tensorflow/lite/c/common.h"
18 #include "tensorflow/lite/kernels/internal/reference/binary_function.h"
19 #include "tensorflow/lite/kernels/internal/reference/reference_ops.h"
20 #include "tensorflow/lite/kernels/internal/tensor.h"
21 #include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
22 #include "tensorflow/lite/kernels/kernel_util.h"
23
24 namespace tflite {
25 namespace ops {
26 namespace builtin {
27 namespace logical {
28 namespace {
29
30 // Input/output tensor index.
31 constexpr int kInputTensor1 = 0;
32 constexpr int kInputTensor2 = 1;
33 constexpr int kOutputTensor = 0;
34
35 // Op data for logical op.
36 struct OpData {
37 bool requires_broadcast;
38 };
39
Init(TfLiteContext * context,const char * buffer,size_t length)40 void* Init(TfLiteContext* context, const char* buffer, size_t length) {
41 auto* data = new OpData;
42 data->requires_broadcast = false;
43 return data;
44 }
45
Free(TfLiteContext * context,void * buffer)46 void Free(TfLiteContext* context, void* buffer) {
47 delete reinterpret_cast<OpData*>(buffer);
48 }
49
Prepare(TfLiteContext * context,TfLiteNode * node)50 TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
51 TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
52 TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
53
54 // Reinterprete the opaque data provided by user.
55 OpData* data = reinterpret_cast<OpData*>(node->user_data);
56
57 const TfLiteTensor* input1;
58 TF_LITE_ENSURE_OK(context,
59 GetInputSafe(context, node, kInputTensor1, &input1));
60 const TfLiteTensor* input2;
61 TF_LITE_ENSURE_OK(context,
62 GetInputSafe(context, node, kInputTensor2, &input2));
63 TfLiteTensor* output;
64 TF_LITE_ENSURE_OK(context,
65 GetOutputSafe(context, node, kOutputTensor, &output));
66
67 TF_LITE_ENSURE_TYPES_EQ(context, input1->type, input2->type);
68
69 const TfLiteType type = input1->type;
70 if (type != kTfLiteBool) {
71 TF_LITE_KERNEL_LOG(context, "Logical ops only support bool type.");
72 return kTfLiteError;
73 }
74 output->type = type;
75
76 data->requires_broadcast = !HaveSameShapes(input1, input2);
77
78 TfLiteIntArray* output_size = nullptr;
79 if (data->requires_broadcast) {
80 TF_LITE_ENSURE_OK(context, CalculateShapeForBroadcast(
81 context, input1, input2, &output_size));
82 } else {
83 output_size = TfLiteIntArrayCopy(input1->dims);
84 }
85
86 return context->ResizeTensor(context, output, output_size);
87 }
88
LogicalImpl(TfLiteContext * context,TfLiteNode * node,bool (* func)(bool,bool))89 TfLiteStatus LogicalImpl(TfLiteContext* context, TfLiteNode* node,
90 bool (*func)(bool, bool)) {
91 OpData* data = reinterpret_cast<OpData*>(node->user_data);
92
93 const TfLiteTensor* input1;
94 TF_LITE_ENSURE_OK(context,
95 GetInputSafe(context, node, kInputTensor1, &input1));
96 const TfLiteTensor* input2;
97 TF_LITE_ENSURE_OK(context,
98 GetInputSafe(context, node, kInputTensor2, &input2));
99 TfLiteTensor* output;
100 TF_LITE_ENSURE_OK(context,
101 GetOutputSafe(context, node, kOutputTensor, &output));
102
103 if (data->requires_broadcast) {
104 reference_ops::BroadcastBinaryFunction4DSlow<bool, bool, bool>(
105 GetTensorShape(input1), GetTensorData<bool>(input1),
106 GetTensorShape(input2), GetTensorData<bool>(input2),
107 GetTensorShape(output), GetTensorData<bool>(output), func);
108 } else {
109 reference_ops::BinaryFunction<bool, bool, bool>(
110 GetTensorShape(input1), GetTensorData<bool>(input1),
111 GetTensorShape(input2), GetTensorData<bool>(input2),
112 GetTensorShape(output), GetTensorData<bool>(output), func);
113 }
114
115 return kTfLiteOk;
116 }
117
LogicalOr(bool x,bool y)118 bool LogicalOr(bool x, bool y) { return x || y; }
119
LogicalOrEval(TfLiteContext * context,TfLiteNode * node)120 TfLiteStatus LogicalOrEval(TfLiteContext* context, TfLiteNode* node) {
121 return LogicalImpl(context, node, LogicalOr);
122 }
123
LogicalAnd(bool x,bool y)124 bool LogicalAnd(bool x, bool y) { return x && y; }
125
LogicalAndEval(TfLiteContext * context,TfLiteNode * node)126 TfLiteStatus LogicalAndEval(TfLiteContext* context, TfLiteNode* node) {
127 return LogicalImpl(context, node, LogicalAnd);
128 }
129
130 } // namespace
131 } // namespace logical
132
Register_LOGICAL_OR()133 TfLiteRegistration* Register_LOGICAL_OR() {
134 // Init, Free, Prepare, Eval are satisfying the Interface required by
135 // TfLiteRegistration.
136 static TfLiteRegistration r = {logical::Init, logical::Free, logical::Prepare,
137 logical::LogicalOrEval};
138 return &r;
139 }
140
Register_LOGICAL_AND()141 TfLiteRegistration* Register_LOGICAL_AND() {
142 // Init, Free, Prepare, Eval are satisfying the Interface required by
143 // TfLiteRegistration.
144 static TfLiteRegistration r = {logical::Init, logical::Free, logical::Prepare,
145 logical::LogicalAndEval};
146 return &r;
147 }
148
149 } // namespace builtin
150 } // namespace ops
151 } // namespace tflite
152