1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
|
/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef __ONERT_GRAPH_SHAPE_INFERENCE_H__
#define __ONERT_GRAPH_SHAPE_INFERENCE_H__
#include "Utils.h"
#include "ir/operation/AvgPool2D.h"
#include "ir/operation/Concat.h"
#include "ir/operation/MaxPool2D.h"
#include "ir/operation/Conv2D.h"
#include "ir/operation/DepthwiseConv2D.h"
#include "ir/operation/Reshape.h"
#include "ir/operation/RSQRT.h"
#include "ir/operation/StridedSlice.h"
#include "ir/LoweredGraph.h"
#include "ir/Index.h"
#include "ir/Layout.h"
#include "ir/OperationVisitor.h"
#include "backend/IDynamicTensorManager.h"
#include "backend/ITensor.h"
#include "backend/ITensorRegistry.h"
namespace onert
{
namespace shape_inference
{
using Shapes = std::vector<ir::Shape>;
// Define shape calculation for operations. List them in alphabetic order.
ir::Shape inferArgMaxShape(const ir::Shape &input_shape, int axis, int rank);
ir::Shape inferAvgPoolShape(const ir::Shape &in_shape, const ir::operation::AvgPool2D::Param ¶m,
ir::Layout layout = ir::Layout::NHWC);
ir::Shape inferBatchMatMulShape(const ir::Shape &lhs_shape, const ir::Shape &rhs_shape,
const ir::operation::BatchMatMul::Param ¶m);
ir::Shape inferBroadcastToShape(const ir::Shape wshape, const int32_t *shape_buffer);
ir::Shape inferConcatShape(const Shapes &in_shapes, const ir::operation::Concat::Param ¶m);
ir::Shape inferConv2DShape(const ir::Shape &in_shape, const ir::Shape &ker_shape,
const ir::operation::Conv2D::Param ¶m,
ir::Layout layout = ir::Layout::NHWC);
ir::Shape inferDepthwiseConv2DShape(const ir::Shape &in_shape, const ir::Shape &ker_shape,
const ir::operation::DepthwiseConv2D::Param ¶m,
ir::Layout layout = ir::Layout::NHWC);
ir::Shape inferEltwiseShape(const ir::Shape &lhs_shape, const ir::Shape &rhs_shape);
ir::Shape inferExpandDimsShape(const ir::Shape &in_shape, int32_t axis);
ir::Shape inferFillShape(const ir::Shape &in_shape, const int32_t *buf);
ir::Shape inferFullyConnectedShape(const ir::Shape &in_shape, const ir::Shape &ker_shape);
ir::Shape inferGatherShape(const ir::Shape &input_shape, const ir::Shape &indices_shape, int axis,
int rank);
ir::Shape inferMaxPoolShape(const ir::Shape &in_shape, const ir::operation::MaxPool2D::Param ¶m,
ir::Layout layout = ir::Layout::NHWC);
ir::Shape inferOnehotShape(const ir::Shape &input_shape, const int depth, int axis);
ir::Shape inferPackShape(const ir::Shape &input_shape, int axis, int rank, int num);
ir::Shape inferPadShape(const ir::Shape &in_shape, const int32_t *pad_buf, const size_t num_pads);
template <typename T> ir::Shape inferRangeShape(T start_val, T limit_val, T delta_val);
ir::Shape inferReshapeShape(const int32_t *shape_buf, const int32_t shape_num_elements,
const size_t total_num_elements);
ir::Shape inferReduceShape(const ir::Shape &input_shape, const std::vector<int> &axes,
bool keep_dims);
template <float *> ir::Shape inferRangeShape(float *start_val, float *limit_val, float *delta_val);
template <typename T> ir::Shape inferRangeShape(T start_val, T limit_val, T delta_val);
ir::Shape inferResizeBilinearShape(const ir::Shape &in_shape, const int32_t output_height,
const int32_t output_width);
ir::Shape inferSelectShape(const ir::Shape &input_cond_shape, const ir::Shape &input_true_shape,
const ir::Shape &input_false_shape);
ir::Shape inferSliceShape(const ir::Shape &input_shape, const int32_t *begins,
const int32_t *sizes);
ir::Shape inferSpaceToBatchNDShape(const ir::Shape &input_shape, const ir::Shape &block_shape_shape,
const ir::Shape &padding_shape, const int32_t *block_shape_data,
const int32_t *padding_data);
ir::Shape inferSplitShape(const ir::Shape input_shape, int axis_value, int num_splits);
ir::Shape inferSqueezeShape(const ir::Shape &in_shape, const ir::operation::Squeeze::Param ¶m);
struct StridedSliceParams
{
int8_t start_indices_count;
int16_t start_indices[4];
int8_t stop_indices_count;
int16_t stop_indices[4];
int8_t strides_count;
int16_t strides[4];
int16_t begin_mask;
int16_t ellipsis_mask;
int16_t end_mask;
int16_t new_axis_mask;
int16_t shrink_axis_mask;
};
template <typename T>
StridedSliceParams buildStridedSliceParams(const T *begin, const T *end, const T *strides,
const uint32_t begin_mask, const uint32_t end_mask,
const uint32_t shrink_axis_mask, const uint8_t rank);
ir::Shape inferStridedSliceShape(const ir::Shape &input_shape, const StridedSliceParams &op_params,
uint32_t rank);
ir::Shape inferTileShape(const ir::Shape &in_shape, const int32_t *multiplier);
ir::Shape inferTransposeShape(const ir::Shape &in_shape, const std::vector<int> &perm);
ir::Shape inferUnpackShape(const ir::Shape &input_shape, int axis, int rank);
} // namespace shape_inference
} // namespace onert
#endif // __ONERT_GRAPH_SHAPE_INFERENCE_H__
|
