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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 <string.h>
16 #include <vector>
17 
18 #include "tensorflow/lite/c/builtin_op_data.h"
19 #include "tensorflow/lite/c/c_api_internal.h"
20 #include "tensorflow/lite/kernels/internal/optimized/optimized_ops.h"
21 #include "tensorflow/lite/kernels/internal/reference/integer_ops/dequantize.h"
22 #include "tensorflow/lite/kernels/internal/tensor.h"
23 #include "tensorflow/lite/kernels/kernel_util.h"
24 #include "tensorflow/lite/kernels/op_macros.h"
25 
26 namespace tflite {
27 namespace ops {
28 namespace builtin {
29 namespace dequantize {
30 
31 struct OpContext {
OpContexttflite::ops::builtin::dequantize::OpContext32   OpContext(TfLiteContext* context, TfLiteNode* node) {
33     input = GetInput(context, node, 0);
34     output = GetOutput(context, node, 0);
35   }
36   const TfLiteTensor* input;
37   TfLiteTensor* output;
38 };
39 
40 struct OpData {
41   // This boolean value is only used when the input tensor is constant.
42   bool float_dequantized_weights_initialized;
43 };
44 
Init(TfLiteContext * context,const char * buffer,size_t length)45 void* Init(TfLiteContext* context, const char* buffer, size_t length) {
46   auto* op_data = new OpData();
47   op_data->float_dequantized_weights_initialized = false;
48   return op_data;
49 }
50 
Free(TfLiteContext * context,void * buffer)51 void Free(TfLiteContext* context, void* buffer) {
52   delete reinterpret_cast<OpData*>(buffer);
53 }
54 
Prepare(TfLiteContext * context,TfLiteNode * node)55 TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
56   TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
57   TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
58 
59   OpContext op_context(context, node);
60 
61   TF_LITE_ENSURE(context, op_context.input->type == kTfLiteUInt8 ||
62                               op_context.input->type == kTfLiteInt8);
63 
64   op_context.output->type = kTfLiteFloat32;
65   // If the input tensor is constant, we can persist the dequantized value in
66   // the output tensor. Otherwise we run dequantize upon each eval.
67   if (IsConstantTensor(op_context.input)) {
68     op_context.output->allocation_type = kTfLiteArenaRwPersistent;
69   }
70   return context->ResizeTensor(context, op_context.output,
71                                TfLiteIntArrayCopy(op_context.input->dims));
72 }
73 
Eval(TfLiteContext * context,TfLiteNode * node)74 TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
75   OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
76   OpContext op_context(context, node);
77   if (IsConstantTensor(op_context.input) &&
78       op_data->float_dequantized_weights_initialized) {
79     return kTfLiteOk;
80   }
81 
82   tflite::DequantizationParams op_params;
83   op_params.zero_point = op_context.input->params.zero_point;
84   op_params.scale = op_context.input->params.scale;
85   switch (op_context.input->type) {
86     case kTfLiteUInt8:
87       optimized_ops::Dequantize(op_params, GetTensorShape(op_context.input),
88                                 GetTensorData<uint8_t>(op_context.input),
89                                 GetTensorShape(op_context.output),
90                                 GetTensorData<float>(op_context.output));
91       break;
92     case kTfLiteInt8:
93       reference_integer_ops::Dequantize(
94           op_params, GetTensorShape(op_context.input),
95           GetTensorData<int8_t>(op_context.input),
96           GetTensorShape(op_context.output),
97           GetTensorData<float>(op_context.output));
98       break;
99     default:
100       context->ReportError(context, "Type %d not supported.",
101                            op_context.input->type);
102       return kTfLiteError;
103   }
104 
105   if (IsConstantTensor(op_context.input)) {
106     op_data->float_dequantized_weights_initialized = true;
107   }
108 
109   return kTfLiteOk;
110 }
111 
112 }  // namespace dequantize
113 
Register_DEQUANTIZE_OPT()114 TfLiteRegistration* Register_DEQUANTIZE_OPT() {
115   static TfLiteRegistration r = {dequantize::Init, dequantize::Free,
116                                  dequantize::Prepare, dequantize::Eval};
117   return &r;
118 }
119 
Register_DEQUANTIZE()120 TfLiteRegistration* Register_DEQUANTIZE() { return Register_DEQUANTIZE_OPT(); }
121 
122 }  // namespace builtin
123 }  // namespace ops
124 }  // namespace tflite
125