1 /*
2 * Copyright (C) 2018 The Android Open Source Project
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17 #define LOG_TAG "Operations"
18
19 #include "Tile.h"
20 #include "Tracing.h"
21
22 namespace android {
23 namespace nn {
24 namespace tile {
25
26 namespace {
27
28 template <typename T>
CopyMultipleTimes(const T * in_data,int32_t in_size,int32_t multiplier,T * out_data)29 void CopyMultipleTimes(const T* in_data, int32_t in_size, int32_t multiplier, T* out_data) {
30 for (int i = 0; i < multiplier; ++i) {
31 const T* in_end = in_data + in_size;
32 T* new_out_data = std::copy(in_data, in_end, out_data);
33 in_data = out_data;
34 out_data = new_out_data;
35 }
36 }
37
38 template <typename T, typename M>
TileOneDimension(const Shape & input_shape,const T * in_data,const M * multipliers,T * out_data,int dimension)39 std::pair<int, int> TileOneDimension(const Shape& input_shape, const T* in_data,
40 const M* multipliers, T* out_data, int dimension) {
41 const int dimension_size = input_shape.dimensions[dimension];
42 if (dimension == input_shape.dimensions.size() - 1) {
43 CopyMultipleTimes(in_data, dimension_size, multipliers[dimension], out_data);
44 return std::make_pair(dimension_size,
45 dimension_size * static_cast<int>(multipliers[dimension]));
46 }
47 int total_stride_size = 0, total_tiled_stride_size = 0;
48 const T* copy_from_data = in_data;
49 T* copy_to_data = out_data;
50 for (int i = 0; i < dimension_size; ++i) {
51 int stride_size = 0, tiled_stride_size = 0;
52 std::tie(stride_size, tiled_stride_size) = TileOneDimension(
53 input_shape, copy_from_data, multipliers, copy_to_data, dimension + 1);
54 copy_from_data += stride_size;
55 copy_to_data += tiled_stride_size;
56 total_stride_size += stride_size;
57 total_tiled_stride_size += tiled_stride_size;
58 }
59 CopyMultipleTimes(out_data, total_tiled_stride_size, multipliers[dimension] - 1,
60 out_data + total_tiled_stride_size);
61 return std::make_pair(total_stride_size, total_tiled_stride_size * multipliers[dimension]);
62 }
63
64 template <typename T>
tileImpl(const T * inputData,const Shape & inputShape,const int32_t * multiples,T * outputData,const Shape & outputShape)65 void tileImpl(const T* inputData, const Shape& inputShape, const int32_t* multiples, T* outputData,
66 const Shape& outputShape) {
67 TileOneDimension(inputShape, inputData, multiples, outputData, 0);
68 }
69
70 } // namespace
71
prepare(const Shape & input,const int32_t * multiples,const Shape & multiplesShape,Shape * output)72 bool prepare(const Shape& input, const int32_t* multiples, const Shape& multiplesShape,
73 Shape* output) {
74 output->type = input.type;
75 output->offset = input.offset;
76 output->scale = input.scale;
77
78 output->dimensions.assign(input.dimensions.begin(), input.dimensions.end());
79 for (size_t i = 0; i < output->dimensions.size(); ++i) {
80 output->dimensions[i] *= multiples[i];
81 }
82
83 return true;
84 }
85
eval(const uint8_t * inputData,const Shape & inputShape,const int32_t * multiples,uint8_t * outputData,const Shape & outputShape)86 bool eval(const uint8_t* inputData, const Shape& inputShape, const int32_t* multiples,
87 uint8_t* outputData, const Shape& outputShape) {
88 NNTRACE_TRANS("tile::eval");
89 #define ANDROID_NN_IMPL_TILE(operandType, dataType) \
90 case operandType: { \
91 NNTRACE_COMP_SWITCH("tileImpl::" #dataType); \
92 tileImpl(reinterpret_cast<const dataType*>(inputData), inputShape, multiples, \
93 reinterpret_cast<dataType*>(outputData), outputShape); \
94 return true; \
95 }
96
97 switch (inputShape.type) {
98 ANDROID_NN_IMPL_TILE(OperandType::TENSOR_FLOAT16, _Float16);
99 ANDROID_NN_IMPL_TILE(OperandType::TENSOR_FLOAT32, float);
100 ANDROID_NN_IMPL_TILE(OperandType::TENSOR_INT32, int32_t);
101 ANDROID_NN_IMPL_TILE(OperandType::TENSOR_QUANT8_ASYMM, uint8_t);
102 default:
103 LOG(ERROR) << "Unsupported data type";
104 return false;
105 }
106 #undef ANDROID_NN_IMPL_TILE
107 }
108
109 } // namespace tile
110 } // namespace nn
111 } // namespace android
112