1 /*
2 * Copyright (c) 2016-2021 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/cpu/kernels/CpuGemmTranspose1xWKernel.h"
25
26 #include "arm_compute/core/ITensor.h"
27 #include "arm_compute/core/Validate.h"
28 #include "arm_compute/core/Window.h"
29 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
30 #include "src/core/helpers/AutoConfiguration.h"
31 #include "src/core/helpers/WindowHelpers.h"
32
33 #include <arm_neon.h>
34
35 namespace arm_compute
36 {
37 namespace cpu
38 {
39 namespace kernels
40 {
41 using namespace arm_compute::misc::shape_calculator;
42
configure(const ITensorInfo * src,ITensorInfo * dst)43 void CpuGemmTranspose1xWKernel::configure(const ITensorInfo *src, ITensorInfo *dst)
44 {
45 ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
46
47 // Output tensor auto inizialitation if not yet initialized
48 auto_init_if_empty(*dst, src->clone()->set_tensor_shape(compute_transpose1xW_with_element_size_shape(*src)));
49
50 // Perform validate step
51 ARM_COMPUTE_ERROR_THROW_ON(CpuGemmTranspose1xWKernel::validate(src, dst));
52
53 const size_t vector_size = 16 / src->element_size();
54
55 // Configure kernel window
56 Window win = calculate_max_window(*src, Steps(vector_size));
57 ICPPKernel::configure(win);
58 }
59
validate(const ITensorInfo * src,const ITensorInfo * dst)60 Status CpuGemmTranspose1xWKernel::validate(const ITensorInfo *src, const ITensorInfo *dst)
61 {
62 ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src);
63 ARM_COMPUTE_RETURN_ERROR_ON(src->data_type() == DataType::UNKNOWN);
64 //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src) is not needed here as this kernel doesn't use CPU FP16 instructions.
65
66 if(dst->total_size() != 0)
67 {
68 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), compute_transpose1xW_with_element_size_shape(*src));
69 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
70 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(src, dst);
71 }
72
73 return Status{};
74 }
75
run_op(ITensorPack & tensors,const Window & window,const ThreadInfo & info)76 void CpuGemmTranspose1xWKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
77 {
78 ARM_COMPUTE_UNUSED(info);
79 ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
80 ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
81 ARM_COMPUTE_ERROR_ON(tensors.empty());
82
83 /*
84 * Following an example of how the transposition1xW works when the src data type is F32
85 *
86 * |a00 a01 a02 a03|
87 * |a10 a11 a12 a13|
88 * |a20 a21 a22 a23| = | a00 a01 a02 a03 || a10 a11 a12 a13 || a20 a21 a22 a23 || a30 a31 a32 a33 |
89 * |a30 a31 a32 a33|
90 *
91 * The dst matrix will have the following shape: [ height * W, ceil(width / W) ], where W = (16 / element size of the tensor)
92 */
93
94 // Set window for dst tensor. Set to 0 the X and Y dimensions in order to allow multi-threading implementation and future batched matrix multiplications
95 Window win_out(window);
96 win_out.set(Window::DimX, Window::Dimension(0, 0, 0));
97 win_out.set(Window::DimY, Window::Dimension(0, 0, 0));
98
99 const ITensor *src = tensors.get_const_tensor(TensorType::ACL_SRC);
100 ITensor *dst = tensors.get_tensor(TensorType::ACL_DST);
101
102 Iterator in(src, window);
103 Iterator out(dst, win_out);
104
105 const size_t in_width = src->info()->dimension(0);
106 const size_t element_size = src->info()->element_size();
107 const size_t out_stride = dst->info()->strides_in_bytes()[1];
108 const size_t vector_size = 16 / element_size;
109
110 execute_window_loop(window, [&](const Coordinates & id)
111 {
112 const uint8_t *in_ptr = in.ptr();
113 uint8_t *const out_ptr = out.ptr() + (id.y() * vector_size) * element_size + (id.x() / vector_size) * out_stride;
114
115 for(size_t k = 0; k < vector_size; ++k)
116 {
117 // If the src width is not multiple of W, we fill the reference with 0s
118 if((id.x() + k) >= in_width)
119 {
120 std::memset(out_ptr + k * element_size, 0, element_size);
121 }
122 else
123 {
124 std::memcpy(out_ptr + k * element_size, in_ptr + k * element_size, element_size);
125 }
126 }
127 },
128 in, out);
129 }
130
name() const131 const char *CpuGemmTranspose1xWKernel::name() const
132 {
133 return "CpuGemmTranspose1xWKernel";
134 }
135 } // namespace kernels
136 } // namespace cpu
137 } // namespace arm_compute
138