Compute Library
 22.02
CpuConcatenateBatchKernel.cpp
Go to the documentation of this file.
1 /*
2  * Copyright (c) 2019-2021 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  */
25 
26 #include "arm_compute/core/Error.h"
30 #include "arm_compute/core/Utils.h"
33 #include "src/core/NEON/NEAsymm.h"
37 
38 namespace arm_compute
39 {
40 namespace cpu
41 {
42 namespace kernels
43 {
44 namespace
45 {
46 template <typename T>
47 void batch_concat(const ITensor *src, ITensor *dst, unsigned int batch_offset, const Window &window)
48 {
49  // Offset src
50  uint8_t *src_ptr = src->buffer() + src->info()->offset_first_element_in_bytes();
51 
52  // Offset dst
53  uint8_t *dst_ptr = dst->buffer() + dst->info()->offset_first_element_in_bytes() + batch_offset * dst->info()->strides_in_bytes()[3];
54 
55  const auto window_start_x = static_cast<int>(window.x().start());
56  const auto window_end_x = static_cast<int>(window.x().end());
57  const int window_step_x = 16 / dst->info()->element_size();
58 
59  Window win{ window };
60  win.set(Window::DimX, Window::Dimension(0, 1, 1));
61  win.set(3, Window::Dimension(0, src->info()->tensor_shape()[3], 1));
62 
63  Iterator src_it(src, win);
64  Iterator dst_it(dst, win);
65 
66  const DataType dt = src->info()->data_type();
67  const UniformQuantizationInfo src_qinfo = src->info()->quantization_info().uniform();
68  const UniformQuantizationInfo dst_qinfo = dst->info()->quantization_info().uniform();
69  if(dt == DataType::QASYMM8 && src_qinfo != dst_qinfo)
70  {
71  execute_window_loop(win, [&](const Coordinates &)
72  {
73  const auto in_ptr = reinterpret_cast<const uint8_t *>(src_ptr + src_it.offset());
74  const auto out_ptr = reinterpret_cast<uint8_t *>(dst_ptr + dst_it.offset());
75 
76  int x = window_start_x;
77  for(; x <= (window_end_x - window_step_x); x += window_step_x)
78  {
79  wrapper::vstore(out_ptr, vquantize(vdequantize(wrapper::vloadq(in_ptr), src_qinfo), dst_qinfo));
80  }
81 
82  // Compute left-over elements
83  for(; x < window_end_x; ++x)
84  {
85  *(out_ptr + x) = quantize_qasymm8(dequantize_qasymm8(*(in_ptr + x), src_qinfo), dst_qinfo);
86  }
87  },
88  src_it, dst_it);
89  }
90  else if(dt == DataType::QASYMM8_SIGNED && src_qinfo != dst_qinfo)
91  {
92  execute_window_loop(win, [&](const Coordinates &)
93  {
94  const auto in_ptr = reinterpret_cast<const int8_t *>(src_ptr + src_it.offset());
95  const auto out_ptr = reinterpret_cast<int8_t *>(dst_ptr + dst_it.offset());
96  int x = window_start_x;
97  for(; x <= (window_end_x - window_step_x); x += window_step_x)
98  {
99  wrapper::vstore(out_ptr, vquantize_signed(vdequantize(wrapper::vloadq(in_ptr), src_qinfo), dst_qinfo));
100  }
101  // Compute left-over elements
102  for(; x < window_end_x; ++x)
103  {
104  *(out_ptr + x) = quantize_qasymm8_signed(dequantize_qasymm8_signed(*(in_ptr + x), src_qinfo), dst_qinfo);
105  }
106  },
107  src_it, dst_it);
108  }
109  else
110  {
111  execute_window_loop(win, [&](const Coordinates &)
112  {
113  const auto in_ptr = reinterpret_cast<const T *>(src_ptr + src_it.offset());
114  const auto out_ptr = reinterpret_cast<T *>(dst_ptr + dst_it.offset());
115 
116  int x = window_start_x;
117  for(; x <= (window_end_x - window_step_x); x += window_step_x)
118  {
119  wrapper::vstore(out_ptr + x, wrapper::vloadq(in_ptr + x));
120  }
121 
122  // Compute left-over elements
123  for(; x < window_end_x; ++x)
124  {
125  *(out_ptr + x) = *(in_ptr + x);
126  }
127  },
128  src_it, dst_it);
129  }
130 }
131 
132 Status validate_arguments(const ITensorInfo *src, unsigned int batch_offset, const ITensorInfo *dst)
133 {
135  //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src) is not needed here as this kernel doesn't use CPU FP16 instructions.
136  ARM_COMPUTE_RETURN_ERROR_ON(src->data_type() == DataType::UNKNOWN);
138 
139  ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(Window::DimX) != dst->dimension(Window::DimX));
140  ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(Window::DimY) != dst->dimension(Window::DimY));
141  ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(Window::DimZ) != dst->dimension(Window::DimZ));
142  ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(3) + batch_offset > dst->dimension(3));
144 
145  return Status{};
146 }
147 } // namespace
148 
149 void CpuConcatenateBatchKernel::configure(const ITensorInfo *src, unsigned int batch_offset, ITensorInfo *dst)
150 {
152  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, batch_offset, dst));
153 
154  _func = nullptr;
155  _batch_offset = batch_offset;
156 
157  switch(src->data_type())
158  {
159  case DataType::S8:
160  case DataType::U8:
161  case DataType::QASYMM8:
163  _func = &batch_concat<uint8_t>;
164  break;
165  case DataType::S16:
166  case DataType::U16:
167  case DataType::F16:
168  _func = &batch_concat<uint16_t>;
169  break;
170  case DataType::S32:
171  case DataType::U32:
172  case DataType::F32:
173  _func = &batch_concat<uint32_t>;
174  break;
175  default:
176  ARM_COMPUTE_ERROR("Unsupported data type.");
177  }
178 
179  // Configure kernel window
180  Window win = calculate_max_window(*dst, Steps());
181  ICpuKernel::configure(win);
182 }
183 
185  unsigned int batch_offset,
186  const arm_compute::ITensorInfo *dst)
187 {
188  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, batch_offset, dst));
189  return Status{};
190 }
191 
193 {
194  ARM_COMPUTE_UNUSED(info);
197  ARM_COMPUTE_ERROR_ON(_func == nullptr);
198 
199  (*_func)(tensors.get_const_tensor(TensorType::ACL_SRC),
201  _batch_offset,
202  window);
203 }
204 
206 {
207  return "CpuConcatenateBatchKernel";
208 }
209 } // namespace kernels
210 } // namespace cpu
211 } // namespace arm_compute
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
float dequantize_qasymm8(uint8_t value, const INFO_TYPE &qinfo)
Dequantize a value given an unsigned 8-bit asymmetric quantization scheme.
uint8_t quantize_qasymm8(float value, const INFO_TYPE &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
Quantize a value given an unsigned 8-bit asymmetric quantization scheme.
#define ARM_COMPUTE_ERROR(msg)
Print the given message then throw an std::runtime_error.
Definition: Error.h:352
float32x4x2_t vdequantize(const uint8x8_t &qv, const UniformQuantizationInfo &qi)
Dequantize a neon vector holding 8 quantized values.
Definition: NEAsymm.h:415
1 channel, 1 U8 per channel
uint8x16_t vloadq(const uint8_t *ptr)
Definition: load.h:58
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
virtual DataType data_type() const =0
Data type used for each element of the tensor.
1 channel, 1 F32 per channel
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
Definition: Error.h:466
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
1 channel, 1 U16 per channel
Status class.
Definition: Error.h:52
#define ARM_COMPUTE_RETURN_ERROR_ON(cond)
If the condition is true, an error is returned.
Definition: Error.h:296
SimpleTensor< float > src
Definition: DFT.cpp:155
Copyright (c) 2017-2021 Arm Limited.
1 channel, 1 F16 per channel
#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)
Definition: Validate.h:159
1 channel, 1 S32 per channel
const ITensor * get_const_tensor(int id) const
Get constant tensor of a given id.
Definition: ITensorPack.cpp:54
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
1 channel, 1 U32 per channel
const char * name() const override
Name of the kernel.
int8_t quantize_qasymm8_signed(float value, const INFO_TYPE &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
Quantize a value given a signed 8-bit asymmetric quantization scheme.
quantized, asymmetric fixed-point 8-bit number unsigned
Class to describe a number of elements in each dimension.
Definition: Steps.h:40
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
1 channel, 1 S16 per channel
void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override
Execute the kernel on the passed window.
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
ITensor * get_tensor(int id)
Get tensor of a given id from the pac.
Definition: ITensorPack.cpp:64
Information about executing thread and CPU.
Definition: CPPTypes.h:169
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)
Definition: Validate.h:439
static Status validate(const ITensorInfo *src, unsigned int batch_offset, const ITensorInfo *dst)
Static function to check if given info will lead to a valid configuration.
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)
Definition: Validate.h:541
uint8x8_t vquantize(const float32x4x2_t &qv, const UniformQuantizationInfo &qi)
Quantize a neon vector holding 8 floating point values.
Definition: NEAsymm.h:602
void vstore(uint8_t *ptr, uint8x8_t val)
Definition: store.h:39
float dequantize_qasymm8_signed(int8_t value, const INFO_TYPE &qinfo)
Dequantize a value given a signed 8-bit asymmetric quantization scheme.
Tensor packing service.
Definition: ITensorPack.h:39
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators)
Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...
Definition: Helpers.inl:77
quantized, asymmetric fixed-point 8-bit number signed
Includes all wrapper headers at once.
int8x8_t vquantize_signed(const float32x4x2_t &qv, const UniformQuantizationInfo &qi)
Quantize a neon vector holding 8 floating point values.
Definition: NEAsymm.h:630
DataType
Available data types.
Definition: Types.h:79
signed 8-bit number
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:201
void configure(const ITensorInfo *src, unsigned int batch_offset, ITensorInfo *dst)
Configure kernel for a given list of arguments.