1/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
2
3Licensed under the Apache License, Version 2.0 (the "License");
4you may not use this file except in compliance with the License.
5You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9Unless required by applicable law or agreed to in writing, software
10distributed under the License is distributed on an "AS IS" BASIS,
11WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12See the License for the specific language governing permissions and
13limitations under the License.
14==============================================================================*/
15#include "tensorflow/lite/c/common.h"
16#include "tensorflow/lite/kernels/internal/reference/reference_ops.h"
17#include "tensorflow/lite/kernels/internal/tensor.h"
18#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
19#include "tensorflow/lite/kernels/kernel_util.h"
20
21namespace tflite {
22namespace ops {
23namespace builtin {
24namespace exp {
25
26// This file has reference implementation of Exp.
27enum KernelType {
28 kReference,
29};
30
31struct ExpContext {
32 ExpContext(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
40TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
41 TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
42 TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
43
44 ExpContext op_context(context, node);
45 TfLiteIntArray* output_dims = TfLiteIntArrayCopy(op_context.input->dims);
46 op_context.output->type = op_context.input->type;
47 return context->ResizeTensor(context, op_context.output, output_dims);
48}
49
50template <KernelType kernel_type>
51TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
52 ExpContext op_context(context, node);
53
54#define TF_LITE_EXP(kernel_type, data_type) \
55 kernel_type::Exp<data_type>(GetTensorData<data_type>(op_context.input), \
56 NumElements(op_context.input), \
57 GetTensorData<data_type>(op_context.output))
58
59 // TODO(kanlig): supports half, bfloat16, float64, complex64, and complex128.
60 if (kernel_type == kReference) {
61 switch (op_context.input->type) {
62 case kTfLiteFloat32:
63 TF_LITE_EXP(reference_ops, float);
64 break;
65 default:
66 TF_LITE_KERNEL_LOG(context,
67 "Type %d is currently not supported by Exp.",
68 op_context.input->type);
69 return kTfLiteError;
70 }
71 }
72#undef TF_LITE_EXP
73 return kTfLiteOk;
74}
75
76} // namespace exp
77
78TfLiteRegistration* Register_EXP_REF() {
79 static TfLiteRegistration r = {nullptr, nullptr, exp::Prepare,
80 exp::Eval<exp::kReference>};
81 return &r;
82}
83
84// TODO(kanlig): add optimized implementation of Exp.
85TfLiteRegistration* Register_EXP() { return Register_EXP_REF(); }
86
87} // namespace builtin
88} // namespace ops
89} // namespace tflite
90