blob: 63341e2760c32bc28d786063083f7e678f0f1567 [file] [log] [blame]
Sheri Zhangfb228032021-11-02 10:45:07 +00001/*
2 * Copyright (c) 2021 Arm Limited.
3 *
4 * SPDX-License-Identifier: MIT
5 *
6 * Permission is hereby granted, free of charge, to any person obtaining a copy
7 * of this software and associated documentation files (the "Software"), to
8 * deal in the Software without restriction, including without limitation the
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10 * sell copies of the Software, and to permit persons to whom the Software is
11 * furnished to do so, subject to the following conditions:
12 *
13 * The above copyright notice and this permission notice shall be included in all
14 * copies or substantial portions of the Software.
15 *
16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22 * SOFTWARE.
23 */
24#include "arm_compute/graph/nodes/FusedConvolutionWithPostOpNode.h"
25
26#include "arm_compute/core/Utils.h"
27#include "arm_compute/graph/Graph.h"
28#include "arm_compute/graph/INodeVisitor.h"
29#include "arm_compute/graph/Utils.h"
30
31namespace arm_compute
32{
33namespace graph
34{
35FusedConvolutionWithPostOpNode::FusedConvolutionWithPostOpNode(PadStrideInfo info,
36 unsigned int num_groups,
37 ConvolutionMethod method,
38 FastMathHint fast_math_hint,
39 QuantizationInfo out_quant_info)
Sheri Zhangc65023e2021-11-03 21:24:00 +000040 : _info(std::move(info)), _num_groups(num_groups), _method(method), _fast_math_hint(fast_math_hint), _out_quant_info(std::move(out_quant_info)), _fused_activation()
Sheri Zhangfb228032021-11-02 10:45:07 +000041{
42 _input_edges.resize(4, EmptyEdgeID);
43 _outputs.resize(1, NullTensorID);
44}
45
46void FusedConvolutionWithPostOpNode::set_convolution_method(ConvolutionMethod method)
47{
48 _method = method;
49}
50
51ConvolutionMethod FusedConvolutionWithPostOpNode::convolution_method() const
52{
53 return _method;
54}
55
56void FusedConvolutionWithPostOpNode::set_fast_math_hint(FastMathHint hint)
57{
58 _fast_math_hint = hint;
59}
60
61FastMathHint FusedConvolutionWithPostOpNode::fast_math_hint() const
62{
63 return _fast_math_hint;
64}
65
Sheri Zhangfb228032021-11-02 10:45:07 +000066PadStrideInfo FusedConvolutionWithPostOpNode::convolution_info() const
67{
68 return _info;
69}
70
71unsigned int FusedConvolutionWithPostOpNode::num_groups() const
72{
73 return _num_groups;
74}
75
76ActivationLayerInfo FusedConvolutionWithPostOpNode::fused_activation() const
77{
78 return _fused_activation;
79}
80
81void FusedConvolutionWithPostOpNode::set_fused_activation(ActivationLayerInfo fused_activation)
82{
83 _fused_activation = fused_activation;
84}
85
86void FusedConvolutionWithPostOpNode::set_convolution_info(PadStrideInfo info)
87{
88 _info = info;
89}
90
91TensorDescriptor FusedConvolutionWithPostOpNode::compute_output_descriptor(const TensorDescriptor &input_descriptor,
92 const TensorDescriptor &weights_descriptor,
93 const PadStrideInfo &info)
94{
95 unsigned int output_width = 0;
96 unsigned int output_height = 0;
97
98 const unsigned int input_width = get_dimension_size(input_descriptor, DataLayoutDimension::WIDTH);
99 const unsigned int input_height = get_dimension_size(input_descriptor, DataLayoutDimension::HEIGHT);
100 const unsigned int kernel_width = get_dimension_size(weights_descriptor, DataLayoutDimension::WIDTH);
101 const unsigned int kernel_height = get_dimension_size(weights_descriptor, DataLayoutDimension::HEIGHT);
102
103 std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info);
104
105 const DataLayout data_layout = input_descriptor.layout;
106 TensorDescriptor output_descriptor = input_descriptor;
107 output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), output_width);
108 output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), output_height);
109 output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]);
110
111 return output_descriptor;
112}
113
114bool FusedConvolutionWithPostOpNode::forward_descriptors()
115{
116 if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (output_id(0) != NullTensorID))
117 {
118 Tensor *dst = output(0);
119 ARM_COMPUTE_ERROR_ON(dst == nullptr);
120 dst->desc() = configure_output(0);
121 return true;
122 }
123 return false;
124}
125
126TensorDescriptor FusedConvolutionWithPostOpNode::configure_output(size_t idx) const
127{
128 ARM_COMPUTE_UNUSED(idx);
129 const Tensor *src = input(0);
130 const Tensor *weights = input(1);
131
132 ARM_COMPUTE_ERROR_ON(src == nullptr || weights == nullptr);
133
134 TensorDescriptor output_info = compute_output_descriptor(src->desc(), weights->desc(), _info);
135 if(!_out_quant_info.empty())
136 {
137 output_info.quant_info = _out_quant_info;
138 }
139
140 return output_info;
141}
142
143NodeType FusedConvolutionWithPostOpNode::type() const
144{
145 return FusedConvolutionWithPostOpNode::node_type;
146}
147
148void FusedConvolutionWithPostOpNode::accept(INodeVisitor &v)
149{
150 v.visit(*this);
151}
152} // namespace graph
153} // namespace arm_compute