1 /*
2 * Copyright (c) 2018-2021 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 "src/core/CL/kernels/CLFuseBatchNormalizationKernel.h"
25
26 #include "arm_compute/core/CL/CLHelpers.h"
27 #include "arm_compute/core/CL/CLKernelLibrary.h"
28 #include "arm_compute/core/CL/ICLTensor.h"
29 #include "arm_compute/core/Helpers.h"
30 #include "arm_compute/core/TensorInfo.h"
31 #include "arm_compute/core/Utils.h"
32 #include "src/core/CL/CLValidate.h"
33 #include "src/core/helpers/AutoConfiguration.h"
34 #include "src/core/helpers/WindowHelpers.h"
35
36 #include "support/StringSupport.h"
37
38 namespace arm_compute
39 {
40 namespace
41 {
validate_arguments(const ITensorInfo * input_weights,const ITensorInfo * bn_mean,const ITensorInfo * bn_var,const ITensorInfo * fused_weights,const ITensorInfo * fused_bias,const ITensorInfo * input_bias,const ITensorInfo * bn_beta,const ITensorInfo * bn_gamma,float epsilon,FuseBatchNormalizationType fbn_type)42 Status validate_arguments(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var,
43 const ITensorInfo *fused_weights, const ITensorInfo *fused_bias,
44 const ITensorInfo *input_bias, const ITensorInfo *bn_beta, const ITensorInfo *bn_gamma,
45 float epsilon, FuseBatchNormalizationType fbn_type)
46 {
47 ARM_COMPUTE_UNUSED(epsilon);
48 ARM_COMPUTE_ERROR_ON_NULLPTR(input_weights, bn_mean, bn_var);
49 ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input_weights);
50 ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_weights, 1, DataType::F16, DataType::F32);
51 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(bn_mean, bn_var);
52 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input_weights, bn_mean, bn_var);
53 ARM_COMPUTE_RETURN_ERROR_ON(input_bias == nullptr && fused_bias == nullptr);
54 ARM_COMPUTE_RETURN_ERROR_ON(bn_mean->num_dimensions() > 1);
55
56 if(fbn_type == FuseBatchNormalizationType::CONVOLUTION)
57 {
58 ARM_COMPUTE_RETURN_ERROR_ON(input_weights->dimension(3) != bn_mean->dimension(0));
59 }
60 else
61 {
62 const size_t channel_idx = get_data_layout_dimension_index(input_weights->data_layout(), DataLayoutDimension::CHANNEL);
63 ARM_COMPUTE_RETURN_ERROR_ON(input_weights->dimension(channel_idx) != bn_mean->dimension(0));
64 }
65
66 // Validate bias
67 if(input_bias != nullptr)
68 {
69 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(bn_mean, input_bias);
70 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input_weights, input_bias);
71 }
72 // Validate beta
73 if(bn_beta != nullptr)
74 {
75 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(bn_mean, bn_beta);
76 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input_weights, bn_beta);
77 }
78 // Validate gamma
79 if(bn_gamma != nullptr)
80 {
81 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(bn_mean, bn_gamma);
82 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input_weights, bn_gamma);
83 }
84 // Validate output weights
85 if(fused_weights != nullptr && fused_weights->total_size() != 0)
86 {
87 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input_weights, fused_weights);
88 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input_weights, fused_weights);
89 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input_weights, fused_weights);
90 }
91 // Validate output bias
92 if(fused_bias != nullptr && fused_bias->total_size() != 0)
93 {
94 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(bn_mean, fused_bias);
95 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input_weights, fused_bias);
96 }
97
98 return Status{};
99 }
100 } // namespace
101
CLFuseBatchNormalizationKernel()102 CLFuseBatchNormalizationKernel::CLFuseBatchNormalizationKernel()
103 : _input_weights(nullptr), _input_bias(nullptr), _bn_mean(nullptr), _bn_var(nullptr), _bn_gamma(nullptr), _bn_beta(nullptr), _fused_weights(nullptr), _fused_bias(nullptr), _epsilon(),
104 _run_in_place_weights(false), _run_in_place_bias(false)
105 {
106 _type = CLKernelType::ELEMENTWISE;
107 }
108
configure(const ICLTensor * input_weights,const ICLTensor * bn_mean,const ICLTensor * bn_var,ICLTensor * fused_weights,ICLTensor * fused_bias,const ICLTensor * input_bias,const ICLTensor * bn_beta,const ICLTensor * bn_gamma,float epsilon,FuseBatchNormalizationType fbn_type)109 void CLFuseBatchNormalizationKernel::configure(const ICLTensor *input_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var,
110 ICLTensor *fused_weights, ICLTensor *fused_bias,
111 const ICLTensor *input_bias, const ICLTensor *bn_beta, const ICLTensor *bn_gamma,
112 float epsilon, FuseBatchNormalizationType fbn_type)
113 {
114 configure(CLKernelLibrary::get().get_compile_context(), input_weights, bn_mean, bn_var, fused_weights, fused_bias, input_bias, bn_beta, bn_gamma, epsilon, fbn_type);
115 }
116
configure(const CLCompileContext & compile_context,const ICLTensor * input_weights,const ICLTensor * bn_mean,const ICLTensor * bn_var,ICLTensor * fused_weights,ICLTensor * fused_bias,const ICLTensor * input_bias,const ICLTensor * bn_beta,const ICLTensor * bn_gamma,float epsilon,FuseBatchNormalizationType fbn_type)117 void CLFuseBatchNormalizationKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var,
118 ICLTensor *fused_weights, ICLTensor *fused_bias,
119 const ICLTensor *input_bias, const ICLTensor *bn_beta, const ICLTensor *bn_gamma,
120 float epsilon, FuseBatchNormalizationType fbn_type)
121 {
122 ARM_COMPUTE_ERROR_ON_NULLPTR(input_weights, bn_mean, bn_var);
123
124 auto padding_info = get_padding_info({ input_weights, bn_mean, bn_var, fused_weights, fused_bias, input_bias, bn_beta, bn_gamma });
125
126 _input_weights = input_weights;
127 _input_bias = input_bias;
128 _bn_mean = bn_mean;
129 _bn_var = bn_var;
130 _bn_beta = bn_beta;
131 _bn_gamma = bn_gamma;
132 _fused_weights = fused_weights;
133 _fused_bias = fused_bias;
134 _epsilon = epsilon;
135
136 _run_in_place_weights = (fused_weights == nullptr) || (fused_weights == input_weights);
137 _run_in_place_bias = (input_bias != nullptr && fused_bias == nullptr) || (input_bias != nullptr && fused_bias == input_bias);
138
139 // Auto initialize outputs
140 if(_fused_weights != nullptr)
141 {
142 // Output tensor auto initialization if not yet initialized
143 auto_init_if_empty(*_fused_weights->info(), *_input_weights->info()->clone());
144 }
145 if(_fused_bias != nullptr)
146 {
147 // Output tensor auto initialization if not yet initialized
148 auto_init_if_empty(*_fused_bias->info(), *_bn_mean->info()->clone());
149 }
150
151 // Validate arguments
152 ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input_weights->info(), bn_mean->info(), bn_var->info(),
153 (fused_weights != nullptr) ? fused_weights->info() : nullptr,
154 (fused_bias != nullptr) ? fused_bias->info() : nullptr,
155 (input_bias != nullptr) ? input_bias->info() : nullptr,
156 (bn_beta != nullptr) ? bn_beta->info() : nullptr,
157 (bn_gamma != nullptr) ? bn_gamma->info() : nullptr,
158 epsilon, fbn_type));
159
160 // Configure kernel window
161 Window win = calculate_max_window(*input_weights->info());
162 ICLKernel::configure_internal(win);
163
164 // Set build options
165 CLBuildOptions build_opts;
166 build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input_weights->info()->data_type()));
167 build_opts.add_option_if(fbn_type == FuseBatchNormalizationType::CONVOLUTION, "-DDIM2=" + support::cpp11::to_string(input_weights->info()->dimension(2)));
168 build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(epsilon));
169 build_opts.add_option_if(_input_weights->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
170 build_opts.add_option_if(_run_in_place_weights, "-DIN_PLACE_W");
171 build_opts.add_option_if(_run_in_place_bias, "-DIN_PLACE_B");
172 build_opts.add_option_if(input_bias != nullptr, "-DBIAS");
173 build_opts.add_option_if(bn_beta != nullptr, "-DBETA");
174 build_opts.add_option_if(bn_gamma != nullptr, "-DGAMMA");
175
176 // Create kernel
177 _kernel = create_kernel(compile_context, "fuse_batchnormalization_layer", build_opts.options());
178
179 ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
180 }
181
validate(const ITensorInfo * input_weights,const ITensorInfo * bn_mean,const ITensorInfo * bn_var,const ITensorInfo * fused_weights,const ITensorInfo * fused_bias,const ITensorInfo * input_bias,const ITensorInfo * bn_beta,const ITensorInfo * bn_gamma,float epsilon,FuseBatchNormalizationType fbn_type)182 Status CLFuseBatchNormalizationKernel::validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var,
183 const ITensorInfo *fused_weights, const ITensorInfo *fused_bias,
184 const ITensorInfo *input_bias, const ITensorInfo *bn_beta, const ITensorInfo *bn_gamma,
185 float epsilon, FuseBatchNormalizationType fbn_type)
186 {
187 ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input_weights, bn_mean, bn_var, fused_weights, fused_bias, input_bias, bn_beta, bn_gamma, epsilon, fbn_type));
188 return Status{};
189 }
190
run(const arm_compute::Window & window,cl::CommandQueue & queue)191 void CLFuseBatchNormalizationKernel::run(const arm_compute::Window &window, cl::CommandQueue &queue)
192 {
193 ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
194 ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
195
196 // Create window slice
197 Window collapsed_window = window.collapse(window, Window::DimZ);
198 Window slice_1d = window.first_slice_window_1D();
199 Window slice_3d = collapsed_window.first_slice_window_3D();
200
201 // Add kernel arguments
202 unsigned int idx = 0;
203 add_3D_tensor_argument(idx, _input_weights, slice_3d);
204 if(_input_bias != nullptr)
205 {
206 add_1D_tensor_argument(idx, _input_bias, slice_1d);
207 }
208 add_1D_tensor_argument(idx, _bn_mean, slice_1d);
209 add_1D_tensor_argument(idx, _bn_var, slice_1d);
210 if(!_run_in_place_weights)
211 {
212 add_3D_tensor_argument(idx, _fused_weights, slice_3d);
213 }
214 if(!_run_in_place_bias)
215 {
216 add_1D_tensor_argument(idx, _fused_bias, slice_1d);
217 }
218 if(_bn_beta != nullptr)
219 {
220 add_1D_tensor_argument(idx, _bn_beta, slice_1d);
221 }
222 if(_bn_gamma != nullptr)
223 {
224 add_1D_tensor_argument(idx, _bn_gamma, slice_1d);
225 }
226 enqueue(queue, *this, slice_3d, lws_hint());
227 }
228 } // namespace arm_compute
229