1 /* Copyright 2021 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 "tensorflow/lite/kernels/internal/reference/broadcast_args.h"
16
17 #include <algorithm>
18 #include <cstdint>
19 #include <memory>
20
21 #include "tensorflow/lite/c/common.h"
22 #include "tensorflow/lite/kernels/internal/tensor.h"
23 #include "tensorflow/lite/kernels/kernel_util.h"
24
25 namespace tflite {
26 namespace ops {
27 namespace builtin {
28 namespace broadcast_args {
29
30 constexpr int kShape1Tensor = 0;
31 constexpr int kShape2Tensor = 1;
32 constexpr int kOutputTensor = 0;
33
34 struct BroadcastArgsContext {
BroadcastArgsContexttflite::ops::builtin::broadcast_args::BroadcastArgsContext35 BroadcastArgsContext(TfLiteContext* context, TfLiteNode* node) {
36 shape1 = GetInput(context, node, kShape1Tensor);
37 shape2 = GetInput(context, node, kShape2Tensor);
38 output = GetOutput(context, node, kOutputTensor);
39 }
40 const TfLiteTensor* shape1;
41 const TfLiteTensor* shape2;
42 TfLiteTensor* output;
43 };
44
Prepare(TfLiteContext * context,TfLiteNode * node)45 TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
46 TF_LITE_ENSURE(context, NumInputs(node) == 2);
47 TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
48
49 BroadcastArgsContext op_context(context, node);
50 TF_LITE_ENSURE(context, op_context.shape1->type == kTfLiteInt32 ||
51 op_context.shape1->type == kTfLiteInt64);
52 TF_LITE_ENSURE_EQ(context, op_context.shape1->type, op_context.shape2->type);
53 TF_LITE_ENSURE_EQ(context, op_context.shape1->type, op_context.output->type);
54
55 // Ensures the shapes are 1D tensor.
56 TF_LITE_ENSURE_EQ(context, NumDimensions(op_context.shape1), 1);
57 TF_LITE_ENSURE_EQ(context, NumDimensions(op_context.shape2), 1);
58
59 // Resizing the shape of the output tensor.
60 TfLiteIntArray* output_shape = TfLiteIntArrayCreate(1);
61 output_shape->data[0] = std::max(SizeOfDimension(op_context.shape1, 0),
62 SizeOfDimension(op_context.shape2, 0));
63 return context->ResizeTensor(context, op_context.output, output_shape);
64 }
65
Eval(TfLiteContext * context,TfLiteNode * node)66 TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
67 BroadcastArgsContext op_context(context, node);
68
69 #define TF_LITE_BROADCAST_ARG(data_type) \
70 reference_ops::BroadcastArgs(GetTensorShape(op_context.shape1), \
71 GetTensorData<data_type>(op_context.shape1), \
72 GetTensorShape(op_context.shape2), \
73 GetTensorData<data_type>(op_context.shape2), \
74 GetTensorShape(op_context.output), \
75 GetTensorData<data_type>(op_context.output))
76
77 if (op_context.output->type == kTfLiteInt32) {
78 TF_LITE_BROADCAST_ARG(int32_t);
79 } else {
80 TF_LITE_BROADCAST_ARG(int64_t);
81 }
82 #undef TF_LITE_BROADCAST_ARG
83
84 return kTfLiteOk;
85 }
86
87 } // namespace broadcast_args
88
Register_BROADCAST_ARGS()89 TfLiteRegistration* Register_BROADCAST_ARGS() {
90 static TfLiteRegistration r = {nullptr, nullptr, broadcast_args::Prepare,
91 broadcast_args::Eval};
92 return &r;
93 }
94
95 } // namespace builtin
96 } // namespace ops
97 } // namespace tflite
98