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1 /*
2  * Copyright (c) 2018-2020 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/FullyConnectedLayerNode.h"
25 
26 #include "arm_compute/core/Utils.h"
27 #include "arm_compute/graph/Graph.h"
28 #include "arm_compute/graph/INodeVisitor.h"
29 
30 namespace arm_compute
31 {
32 namespace graph
33 {
FullyConnectedLayerNode(unsigned int num_outputs,QuantizationInfo out_quant_info,FullyConnectedLayerInfo fc_info)34 FullyConnectedLayerNode::FullyConnectedLayerNode(unsigned int num_outputs, QuantizationInfo out_quant_info, FullyConnectedLayerInfo fc_info)
35     : _num_outputs(num_outputs), _out_quant_info(std::move(out_quant_info)), _info(fc_info)
36 {
37     _input_edges.resize(3, EmptyEdgeID);
38     _outputs.resize(1, NullTensorID);
39 }
40 
set_fused_activation(ActivationLayerInfo fused_activation)41 void FullyConnectedLayerNode::set_fused_activation(ActivationLayerInfo fused_activation)
42 {
43     _info.activation_info = fused_activation;
44 }
45 
compute_weights_descriptor(const TensorDescriptor & input_descriptor,unsigned int num_outputs,FullyConnectedLayerInfo fc_info,const QuantizationInfo & weights_quant_info)46 TensorDescriptor FullyConnectedLayerNode::compute_weights_descriptor(const TensorDescriptor &input_descriptor,
47                                                                      unsigned int            num_outputs,
48                                                                      FullyConnectedLayerInfo fc_info,
49                                                                      const QuantizationInfo &weights_quant_info)
50 {
51     unsigned int num_weights    = 1;
52     unsigned int num_dimensions = input_descriptor.shape.num_dimensions();
53     // Ignore the batch dimension if there is one:
54     if(num_dimensions == 2 || num_dimensions == 4)
55     {
56         num_dimensions--;
57     }
58     for(unsigned int i = 0; i < num_dimensions; i++)
59     {
60         num_weights *= input_descriptor.shape[i];
61     }
62 
63     TensorDescriptor weights_descriptor = input_descriptor;
64     weights_descriptor.shape            = TensorShape(num_weights, num_outputs);
65 
66     // If weights are tranposed, use tranposed shape
67     if(!fc_info.transpose_weights)
68     {
69         weights_descriptor.shape = TensorShape(num_outputs, num_weights);
70     }
71 
72     // Set quantization info if present
73     if(!weights_quant_info.empty())
74     {
75         weights_descriptor.quant_info = weights_quant_info;
76     }
77 
78     return weights_descriptor;
79 }
80 
compute_output_descriptor(const TensorDescriptor & input_descriptor,unsigned int num_outputs,const QuantizationInfo & out_quant_info)81 TensorDescriptor FullyConnectedLayerNode::compute_output_descriptor(const TensorDescriptor &input_descriptor,
82                                                                     unsigned int            num_outputs,
83                                                                     const QuantizationInfo &out_quant_info)
84 {
85     // Note: Only 1D batch space is supported at the moment
86     unsigned int batches = input_descriptor.shape[1];
87     if(input_descriptor.shape.num_dimensions() > 2)
88     {
89         batches = input_descriptor.shape[3];
90     }
91 
92     // Set descriptor shape
93     TensorDescriptor output_descriptor = input_descriptor;
94     output_descriptor.shape            = TensorShape(num_outputs, batches);
95 
96     // Set quantization info if present
97     if(!out_quant_info.empty())
98     {
99         output_descriptor.quant_info = out_quant_info;
100     }
101 
102     return output_descriptor;
103 }
104 
info() const105 FullyConnectedLayerInfo FullyConnectedLayerNode::info() const
106 {
107     return _info;
108 }
109 
forward_descriptors()110 bool FullyConnectedLayerNode::forward_descriptors()
111 {
112     if((input_id(0) != NullTensorID) && (output_id(0) != NullTensorID))
113     {
114         Tensor *dst = output(0);
115         ARM_COMPUTE_ERROR_ON(dst == nullptr);
116         dst->desc() = configure_output(0);
117         return true;
118     }
119     return false;
120 }
121 
configure_output(size_t idx) const122 TensorDescriptor FullyConnectedLayerNode::configure_output(size_t idx) const
123 {
124     ARM_COMPUTE_UNUSED(idx);
125     const Tensor *src = input(0);
126     ARM_COMPUTE_ERROR_ON(src == nullptr);
127 
128     return compute_output_descriptor(src->desc(), _num_outputs, _out_quant_info);
129 }
130 
type() const131 NodeType FullyConnectedLayerNode::type() const
132 {
133     return NodeType::FullyConnectedLayer;
134 }
135 
accept(INodeVisitor & v)136 void FullyConnectedLayerNode::accept(INodeVisitor &v)
137 {
138     v.visit(*this);
139 }
140 } // namespace graph
141 } // namespace arm_compute