1/* Copyright 2017 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/contrib/lite/builtin_op_data.h"
16#include "tensorflow/contrib/lite/context.h"
17#include "tensorflow/contrib/lite/kernels/internal/optimized/optimized_ops.h"
18#include "tensorflow/contrib/lite/kernels/internal/reference/reference_ops.h"
19#include "tensorflow/contrib/lite/kernels/internal/tensor.h"
20#include "tensorflow/contrib/lite/kernels/kernel_util.h"
21#include "tensorflow/contrib/lite/kernels/op_macros.h"
22
23namespace tflite {
24namespace ops {
25namespace builtin {
26namespace l2norm {
27
28// This file has two implementation of L2Norm.
29enum KernelType {
30  kReference,
31  kGenericOptimized,
32};
33
34constexpr int kInputTensor = 0;
35constexpr int kOutputTensor = 0;
36
37TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
38  auto* params = reinterpret_cast<TfLiteL2NormParams*>(node->builtin_data);
39
40  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
41  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
42
43  TfLiteTensor* input = GetInput(context, node, kInputTensor);
44  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
45
46  TF_LITE_ENSURE(context, NumDimensions(input) <= 4);
47
48  // TODO(ahentz): Our current implementations only support float32.
49  TF_LITE_ENSURE_EQ(context, output->type, kTfLiteFloat32);
50  TF_LITE_ENSURE_EQ(context, input->type, output->type);
51
52  // TODO(ahentz): For some reason our implementations don't support
53  // activations.
54  TF_LITE_ENSURE_EQ(context, params->activation, kTfLiteActNone);
55
56  TfLiteIntArray* output_size = TfLiteIntArrayCopy(input->dims);
57  return context->ResizeTensor(context, output, output_size);
58}
59
60template <KernelType kernel_type>
61TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
62  TfLiteTensor* input = GetInput(context, node, kInputTensor);
63  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
64
65  if (output->type == kTfLiteFloat32) {
66#define TF_LITE_L2NORM(type)                                 \
67  type::L2Normalization<FusedActivationFunctionType::kNone>( \
68      GetTensorData<float>(input), GetTensorDims(input),     \
69      GetTensorData<float>(output), GetTensorDims(output))
70
71    if (kernel_type == kReference) {
72      TF_LITE_L2NORM(reference_ops);
73    }
74    if (kernel_type == kGenericOptimized) {
75      TF_LITE_L2NORM(optimized_ops);
76    }
77#undef TF_LITE_L2NORM
78  } else {
79    context->ReportError(context, "Inputs and outputs not all float types.");
80    return kTfLiteError;
81  }
82
83  return kTfLiteOk;
84}
85
86}  // namespace l2norm
87
88TfLiteRegistration* Register_L2NORM_REF() {
89  static TfLiteRegistration r = {nullptr, nullptr, l2norm::Prepare,
90                                 l2norm::Eval<l2norm::kReference>};
91  return &r;
92}
93
94TfLiteRegistration* Register_L2NORM_GENERIC_OPT() {
95  static TfLiteRegistration r = {nullptr, nullptr, l2norm::Prepare,
96                                 l2norm::Eval<l2norm::kGenericOptimized>};
97  return &r;
98}
99
100TfLiteRegistration* Register_L2_NORMALIZATION() {
101  return Register_L2NORM_GENERIC_OPT();
102}
103
104}  // namespace builtin
105}  // namespace ops
106}  // namespace tflite
107