1 /*
2 * Copyright (c) 2017-2021 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/runtime/CL/functions/CLGEMMConvolutionLayer.h"
25
26 #include "arm_compute/core/CL/CLKernelLibrary.h"
27 #include "arm_compute/core/PixelValue.h"
28 #include "arm_compute/core/Size2D.h"
29 #include "arm_compute/core/Utils.h"
30 #include "arm_compute/core/Validate.h"
31 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
32 #include "arm_compute/core/utils/quantization/AsymmHelpers.h"
33 #include "arm_compute/runtime/CL/CLScheduler.h"
34 #include "src/core/experimental/PostOpUtils.h"
35 #include "src/core/helpers/MemoryHelpers.h"
36 #include "src/gpu/cl/operators/ClGemmConv2d.h"
37 #include "support/Cast.h"
38
39 #include <cmath>
40 #include <memory>
41 #include <tuple>
42
43 namespace arm_compute
44 {
45 using namespace arm_compute::misc::shape_calculator;
46 using namespace arm_compute::utils::cast;
47 using namespace arm_compute::experimental;
48
49 struct CLGEMMConvolutionLayer::Impl
50 {
51 const ITensor *weights{ nullptr };
52 std::unique_ptr<opencl::ClGemmConv2d> op{ nullptr };
53 ITensorPack run_pack{};
54 ITensorPack prep_pack{};
55 MemoryGroup memory_group{};
56 IWeightsManager *weights_manager{ nullptr };
57 MemoryRequirements aux_mem_req{};
58 WorkspaceData<CLTensor> workspace_tensors{};
59 bool is_prepared{ false };
60 };
61
CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager,IWeightsManager * weights_manager)62 CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
63 : _impl(std::make_unique<Impl>())
64 {
65 _impl->memory_group = MemoryGroup(memory_manager);
66 _impl->weights_manager = weights_manager;
67 }
68
69 CLGEMMConvolutionLayer::~CLGEMMConvolutionLayer() = default;
70
configure(const ICLTensor * input,const ICLTensor * weights,const ICLTensor * biases,ICLTensor * output,const PadStrideInfo & conv_info,const WeightsInfo & weights_info,const Size2D & dilation,const ActivationLayerInfo & act_info,unsigned int num_groups,const experimental::PostOpList<ICLTensor * > & post_ops)71 void CLGEMMConvolutionLayer::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info,
72 const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ICLTensor *> &post_ops)
73 {
74 configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, num_groups, post_ops);
75 }
76
configure(const CLCompileContext & compile_context,const ICLTensor * input,const ICLTensor * weights,const ICLTensor * biases,ICLTensor * output,const PadStrideInfo & conv_info,const WeightsInfo & weights_info,const Size2D & dilation,const ActivationLayerInfo & act_info,unsigned int num_groups,const experimental::PostOpList<ICLTensor * > & post_ops)77 void CLGEMMConvolutionLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
78 const PadStrideInfo &conv_info,
79 const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ICLTensor *> &post_ops)
80 {
81 ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
82 _impl->weights = weights;
83 _impl->op = std::make_unique<opencl::ClGemmConv2d>();
84 // Convert post op arguments to ITensorInfo
85 auto transformed_post_ops = experimental::transform_post_op_list_arguments<ICLTensor *, ITensorInfo *>(post_ops, [](auto tensor)
86 {
87 return tensor->info();
88 });
89 const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups, transformed_post_ops);
90 _impl->op->configure(compile_context, input->info(), weights->info(), (biases != nullptr ? biases->info() : nullptr), output->info(), conv2d_info, weights_info);
91
92 _impl->run_pack =
93 {
94 { TensorType::ACL_SRC_0, input },
95 { TensorType::ACL_SRC_1, weights },
96 { TensorType::ACL_SRC_2, biases },
97 { TensorType::ACL_DST, output }
98 };
99 // Add post op tensors
100 size_t post_op_tensor_index = 0;
101 for(const auto &op : post_ops.get_list())
102 {
103 for(auto &tensor : op->arguments())
104 {
105 _impl->run_pack.add_const_tensor(experimental::get_post_op_arg_type(post_op_tensor_index++), *tensor);
106 }
107 }
108 _impl->prep_pack =
109 {
110 { TensorType::ACL_SRC_1, weights },
111 { TensorType::ACL_SRC_2, biases },
112 };
113 _impl->aux_mem_req = _impl->op->workspace();
114 _impl->workspace_tensors = manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack);
115 }
116
validate(const ITensorInfo * input,const ITensorInfo * weights,const ITensorInfo * biases,const ITensorInfo * output,const PadStrideInfo & conv_info,const WeightsInfo & weights_info,const Size2D & dilation,const ActivationLayerInfo & act_info,unsigned int num_groups,const experimental::PostOpList<ITensorInfo * > & post_ops)117 Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
118 const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ITensorInfo *> &post_ops)
119 {
120 const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups, post_ops);
121 return opencl::ClGemmConv2d::validate(input, weights, biases, output, conv2d_info, weights_info);
122 }
123
run()124 void CLGEMMConvolutionLayer::run()
125 {
126 prepare();
127 MemoryGroupResourceScope scope_mg(_impl->memory_group);
128 _impl->op->run(_impl->run_pack);
129 }
130
prepare()131 void CLGEMMConvolutionLayer::prepare()
132 {
133 if(!_impl->is_prepared)
134 {
135 _impl->op->prepare(_impl->prep_pack);
136 auto has_reshape = std::find_if(_impl->aux_mem_req.begin(),
137 _impl->aux_mem_req.end(),
138 [](const MemoryInfo & m) -> bool { return m.lifetime == MemoryLifetime::Persistent; });
139
140 if(has_reshape != std::end(_impl->aux_mem_req))
141 {
142 _impl->weights->mark_as_unused();
143 }
144 else
145 {
146 // Pack the B matrix to be used as the underlying GEMM performs no reshapes
147 _impl->run_pack.add_const_tensor(ACL_SRC_1, _impl->weights);
148 }
149 release_temporaries(_impl->aux_mem_req, _impl->workspace_tensors);
150 _impl->is_prepared = true;
151 }
152 }
153 } // namespace arm_compute
154