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1 /*
2  * Copyright (c) 2019-2020 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 "src/core/NEON/kernels/NECropKernel.h"
25 
26 #include "arm_compute/core/IAccessWindow.h"
27 #include "arm_compute/core/ITensor.h"
28 #include "arm_compute/core/TensorInfo.h"
29 #include "arm_compute/core/Types.h"
30 #include "arm_compute/core/Window.h"
31 #include "arm_compute/core/utils/helpers/tensor_transform.h"
32 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
33 #include "src/core/CPP/Validate.h"
34 #include "src/core/NEON/wrapper/wrapper.h"
35 #include "src/core/helpers/AutoConfiguration.h"
36 #include "src/core/helpers/WindowHelpers.h"
37 #include "src/core/utils/helpers/bit_ops.h"
38 
39 namespace arm_compute
40 {
41 namespace
42 {
43 template <typename T>
load_as_f32(T * ptr)44 inline float32x4_t load_as_f32(T *ptr)
45 {
46     ARM_COMPUTE_UNUSED(ptr);
47     ARM_COMPUTE_ERROR("Type not supported.");
48 }
49 
50 template <>
load_as_f32(float * ptr)51 inline float32x4_t load_as_f32(float *ptr)
52 {
53     return wrapper::vloadq(ptr);
54 }
55 
56 template <>
load_as_f32(int32_t * ptr)57 inline float32x4_t load_as_f32(int32_t *ptr)
58 {
59     return vcvtq_f32_s32(wrapper::vloadq(ptr));
60 }
61 
62 template <>
load_as_f32(uint32_t * ptr)63 inline float32x4_t load_as_f32(uint32_t *ptr)
64 {
65     return vcvtq_f32_u32(wrapper::vloadq(ptr));
66 }
67 
68 template <>
load_as_f32(int16_t * ptr)69 inline float32x4_t load_as_f32(int16_t *ptr)
70 {
71     return vcvtq_f32_s32(vmovl_s16(wrapper::vload(ptr)));
72 }
73 
74 template <>
load_as_f32(uint16_t * ptr)75 inline float32x4_t load_as_f32(uint16_t *ptr)
76 {
77     return vcvtq_f32_u32(vmovl_u16(wrapper::vload(ptr)));
78 }
79 
80 template <>
load_as_f32(uint8_t * ptr)81 inline float32x4_t load_as_f32(uint8_t *ptr)
82 {
83     return vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(wrapper::vload(ptr)))));
84 }
85 
86 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
87 template <>
load_as_f32(float16_t * ptr)88 inline float32x4_t load_as_f32(float16_t *ptr)
89 {
90     return vcvt_f32_f16(wrapper::vload(ptr));
91 }
92 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
93 
94 template <typename T>
in_bounds_crop_window(const ITensor * input,const ITensor * output,float * output_ptr,Coordinates input_offset,int32_t window_step_x,int32_t output_width_start,int32_t output_width_limit,bool input_has_single_channel,bool is_width_flipped)95 inline void in_bounds_crop_window(const ITensor *input, const ITensor *output, float *output_ptr, Coordinates input_offset,
96                                   int32_t window_step_x, int32_t output_width_start, int32_t output_width_limit, bool input_has_single_channel, bool is_width_flipped)
97 {
98     // Reverse elements if width flipped.
99     if(is_width_flipped)
100     {
101         // Collapse first dimension if possible.
102         if(input_has_single_channel)
103         {
104             int32_t     x = output_width_start;
105             Coordinates negative_offset(input_offset);
106             negative_offset.set(1, negative_offset[1] - window_step_x + 1);
107             for(; x <= output_width_limit - window_step_x; x += window_step_x, negative_offset[1] -= window_step_x)
108             {
109                 auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(negative_offset)));
110 
111                 in = wrapper::vrev64(in);
112                 in = wrapper::vcombine(wrapper::vgethigh(in), wrapper::vgetlow(in));
113 
114                 wrapper::vstore(output_ptr + x, in);
115             }
116             input_offset[1] = negative_offset[1] + window_step_x - 1;
117             for(; x < output_width_limit; ++x, --input_offset[1])
118             {
119                 *(output_ptr + x) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
120             }
121         }
122         else
123         {
124             for(int32_t x = output_width_start; x < output_width_limit; ++x, --input_offset[1])
125             {
126                 input_offset.set(0, 0);
127                 int32_t c = 0;
128                 for(; c <= static_cast<int32_t>(input->info()->dimension(0)) - window_step_x; c += window_step_x, input_offset[0] += window_step_x)
129                 {
130                     auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
131                     wrapper::vstore(output_ptr + x * output->info()->dimension(0) + c, in);
132                 }
133                 for(; c < static_cast<int32_t>(input->info()->dimension(0)); ++c, ++input_offset[0])
134                 {
135                     *(output_ptr + x * output->info()->dimension(0) + c) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
136                 }
137             }
138         }
139     }
140     else
141     {
142         // Use memcpy if the elements don't need converting to float.
143         if(std::is_same<T, float>::value)
144         {
145             memcpy(static_cast<void *>(output_ptr + output_width_start * output->info()->dimension(0)),
146                    reinterpret_cast<const void *>(input->ptr_to_element(input_offset)),
147                    (output_width_limit - output_width_start) * output->info()->dimension(0) * output->info()->element_size());
148         }
149         else
150         {
151             int32_t x                = 0;
152             int32_t limit            = (output_width_limit - output_width_start) * static_cast<int32_t>(output->info()->dimension(0));
153             float *output_start_ptr = output_ptr + output_width_start * output->info()->dimension(0);
154             for(; x <= limit - window_step_x; x += window_step_x, input_offset[0] += window_step_x)
155             {
156                 auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
157                 wrapper::vstore(output_start_ptr + x, in);
158             }
159             for(; x < limit; ++x, ++input_offset[0])
160             {
161                 *(output_start_ptr + x) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
162             }
163         }
164     }
165 }
166 
out_of_bounds_crop_window(const ITensor * output,float * output_ptr,float extrapolation_value,int32_t window_step_x,int32_t output_width_start,int32_t output_width_limit)167 inline void out_of_bounds_crop_window(const ITensor *output, float *output_ptr, float extrapolation_value,
168                                       int32_t window_step_x, int32_t output_width_start, int32_t output_width_limit)
169 {
170     auto    in               = wrapper::vdup_n(extrapolation_value, wrapper::traits::vector_128_tag());
171     int32_t x                = 0;
172     int32_t limit            = (output_width_limit - output_width_start) * static_cast<int32_t>(output->info()->dimension(0));
173     float *output_start_ptr = output_ptr + output_width_start * output->info()->dimension(0);
174     for(; x <= limit - window_step_x; x += window_step_x)
175     {
176         wrapper::vstore(output_start_ptr + x, in);
177     }
178     for(; x < limit; ++x)
179     {
180         *(output_start_ptr + x) = extrapolation_value;
181     }
182 }
183 
execute_window(const ITensor * input,const ITensor * output,Coordinates input_offset,float extrapolation_value,const std::array<uint32_t,2> & rows_out_of_bounds,const std::array<uint32_t,2> & cols_out_of_bounds,NECropKernel::InBoundsCropFunction * in_bounds_crop_function,bool is_height_flipped,bool has_cols_in_bounds,bool has_cols_out_of_bounds_before,bool has_cols_out_of_bounds_after,bool input_has_single_channel,bool is_width_flipped)184 inline void execute_window(const ITensor *input, const ITensor *output, Coordinates input_offset, float extrapolation_value,
185                            const std::array<uint32_t, 2> &rows_out_of_bounds, const std::array<uint32_t, 2> &cols_out_of_bounds, NECropKernel::InBoundsCropFunction *in_bounds_crop_function,
186                            bool is_height_flipped, bool has_cols_in_bounds, bool has_cols_out_of_bounds_before, bool has_cols_out_of_bounds_after, bool input_has_single_channel, bool is_width_flipped)
187 {
188     // Output is always float.
189     const int window_step_x = 16 / sizeof(float);
190     auto     *output_ptr    = reinterpret_cast<float *>(output->buffer());
191     //  Output window:
192     //  --------------------------------
193     //  |          Out of bounds       |
194     //  |          rows before         |
195     //  |------------------------------|
196     //  | Out of | In         | Out of |
197     //  | bounds | bounds     | bounds |
198     //  | cols   | elements   | cols   |
199     //  | before | copied     | after  |
200     //  |        | from input |        |
201     //  --------------------------------
202     //  |        Out of bounds         |
203     //  |        rows after            |
204     //  |------------------------------|
205     // Fill all output rows that have no elements that are within the input bounds with the extrapolation value.
206     // First for the rows before the in bounds rows.
207     out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, rows_out_of_bounds[0] * output->info()->dimension(1));
208     output_ptr += rows_out_of_bounds[0] * output->info()->dimension(1) * output->info()->dimension(0);
209     // Iterate through each row that has any elements within the input bounds.
210     for(uint32_t row = rows_out_of_bounds[0]; static_cast<int32_t>(row) < static_cast<int32_t>(output->info()->dimension(2) - rows_out_of_bounds[1]);
211         ++row, is_height_flipped ? --input_offset[2] : ++input_offset[2])
212     {
213         // Fill all elements in the row that are out of bounds with the extrapolation value.
214         // First for the elements before the in bounds elements.
215         if(has_cols_out_of_bounds_before)
216         {
217             out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, cols_out_of_bounds[0]);
218         }
219         // Copy all elements within the input bounds from the input tensor.
220         if(has_cols_in_bounds)
221         {
222             (*in_bounds_crop_function)(input, output, output_ptr, input_offset, window_step_x, cols_out_of_bounds[0],
223                                        output->info()->dimension(1) - cols_out_of_bounds[1], input_has_single_channel, is_width_flipped);
224         }
225         // Fill all elements after the in bounds elements with the extrapolation value.
226         if(has_cols_out_of_bounds_after)
227         {
228             out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, output->info()->dimension(1) - cols_out_of_bounds[1], output->info()->dimension(1));
229         }
230         output_ptr += output->info()->dimension(1) * output->info()->dimension(0);
231     }
232     // Fill all rows after the in bounds elements with the extrapolation value.
233     out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, rows_out_of_bounds[1] * output->info()->dimension(1));
234 }
235 } // namespace
236 
NECropKernel()237 NECropKernel::NECropKernel()
238     : _input(nullptr), _crop_boxes(nullptr), _box_ind(nullptr), _output(nullptr), _start(), _end(), _crop_box_ind(0), _extrapolation_value(0), _rows_out_of_bounds(), _cols_out_of_bounds(),
239       _in_bounds_crop_function(nullptr)
240 {
241 }
242 
configure(const ITensor * input,const ITensor * crop_boxes,const ITensor * box_ind,ITensor * output,uint32_t crop_box_ind,float extrapolation_value)243 void NECropKernel::configure(const ITensor *input, const ITensor *crop_boxes, const ITensor *box_ind, ITensor *output, uint32_t crop_box_ind, float extrapolation_value)
244 {
245     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
246     ARM_COMPUTE_ERROR_THROW_ON(validate(input->info(), crop_boxes->info(), box_ind->info(), output->info(), crop_box_ind, extrapolation_value));
247 
248     _input               = input;
249     _crop_boxes          = crop_boxes;
250     _box_ind             = box_ind;
251     _output              = output;
252     _crop_box_ind        = crop_box_ind;
253     _extrapolation_value = extrapolation_value;
254 
255     switch(input->info()->data_type())
256     {
257         case DataType::F32:
258             _in_bounds_crop_function = &in_bounds_crop_window<float>;
259             break;
260 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
261         case DataType::F16:
262             _in_bounds_crop_function = &in_bounds_crop_window<float16_t>;
263             break;
264 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
265         case DataType::U32:
266             _in_bounds_crop_function = &in_bounds_crop_window<uint32_t>;
267             break;
268         case DataType::S32:
269             _in_bounds_crop_function = &in_bounds_crop_window<int32_t>;
270             break;
271         case DataType::U16:
272             _in_bounds_crop_function = &in_bounds_crop_window<uint16_t>;
273             break;
274         case DataType::S16:
275             _in_bounds_crop_function = &in_bounds_crop_window<int16_t>;
276             break;
277         case DataType::U8:
278             _in_bounds_crop_function = &in_bounds_crop_window<uint8_t>;
279             break;
280         default:
281             ARM_COMPUTE_ERROR("Datatype not supported");
282     }
283 }
284 
validate(const ITensorInfo * input,const ITensorInfo * crop_boxes,const ITensorInfo * box_ind,const ITensorInfo * output,uint32_t crop_box_ind,float extrapolation_value)285 Status NECropKernel::validate(const ITensorInfo *input, const ITensorInfo *crop_boxes, const ITensorInfo *box_ind, const ITensorInfo *output, uint32_t crop_box_ind, float extrapolation_value)
286 {
287     ARM_COMPUTE_UNUSED(extrapolation_value);
288     ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
289     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::U16, DataType::S16, DataType::F16, DataType::U32, DataType::S32, DataType::F32);
290     ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC);
291     ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().num_dimensions() > 4);
292     ARM_COMPUTE_RETURN_ERROR_ON(crop_boxes->tensor_shape()[0] != 4);
293     ARM_COMPUTE_RETURN_ERROR_ON(crop_boxes->tensor_shape()[1] != box_ind->tensor_shape()[0]);
294     ARM_COMPUTE_RETURN_ERROR_ON(crop_boxes->tensor_shape()[1] <= crop_box_ind);
295     ARM_COMPUTE_RETURN_ERROR_ON(box_ind->tensor_shape()[0] <= crop_box_ind);
296     if(output->total_size() > 0)
297     {
298         ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(output, DataType::F32);
299         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
300         ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() != 3);
301         ARM_COMPUTE_RETURN_ERROR_ON(output->has_padding());
302     }
303     return Status{};
304 }
305 
configure_output_shape()306 void NECropKernel::configure_output_shape()
307 {
308     // _crop_box_ind is used to index _crop_boxes and retrieve the appropriate crop box.
309     // The crop box is specified by normalized coordinates [y0, x0, y1, x1].
310     const float x0 = *reinterpret_cast<const float *>(_crop_boxes->ptr_to_element(Coordinates(1, _crop_box_ind)));
311     const float y0 = *reinterpret_cast<const float *>(_crop_boxes->ptr_to_element(Coordinates(0, _crop_box_ind)));
312     const float x1 = *reinterpret_cast<const float *>(_crop_boxes->ptr_to_element(Coordinates(3, _crop_box_ind)));
313     const float y1 = *reinterpret_cast<const float *>(_crop_boxes->ptr_to_element(Coordinates(2, _crop_box_ind)));
314     // The normalized coordiantes are scaled to retrieve the floating point image coordinates which are rounded to integers.
315     _start = Coordinates(std::floor(x0 * (_input->info()->tensor_shape()[1] - 1) + 0.5f),
316                          std::floor(y0 * (_input->info()->tensor_shape()[2] - 1) + 0.5f));
317     _end = Coordinates(std::floor(x1 * (_input->info()->tensor_shape()[1] - 1) + 0.5f),
318                        std::floor(y1 * (_input->info()->tensor_shape()[2] - 1) + 0.5f));
319     const TensorShape out_shape(_input->info()->tensor_shape()[0], abs(_end[0] - _start[0]) + 1, abs(_end[1] - _start[1]) + 1);
320     _output->info()->set_tensor_shape(out_shape);
321 
322     bool is_width_flipped  = _end[0] < _start[0];
323     bool is_height_flipped = _end[1] < _start[1];
324     if(is_height_flipped)
325     {
326         _rows_out_of_bounds[0] = _start[1] >= static_cast<int32_t>(_input->info()->dimension(2)) ? std::min(static_cast<uint32_t>(_start[1] - _input->info()->dimension(2) + 1),
327                                                                                                             static_cast<uint32_t>(_output->info()->dimension(2))) :
328                                  0;
329         _rows_out_of_bounds[1] = _end[1] < 0 ? std::min(static_cast<uint32_t>(-_end[1]),
330                                                         static_cast<uint32_t>(_output->info()->dimension(2))) :
331                                  0;
332     }
333     else
334     {
335         _rows_out_of_bounds[0] = _start[1] < 0 ? std::min(static_cast<uint32_t>(-_start[1]),
336                                                           static_cast<uint32_t>(_output->info()->dimension(2))) :
337                                  0;
338         _rows_out_of_bounds[1] = _end[1] >= static_cast<int32_t>(_input->info()->dimension(2)) ? std::min(static_cast<uint32_t>(_end[1] - _input->info()->dimension(2) + 1),
339                                                                                                           static_cast<uint32_t>(_output->info()->dimension(2))) :
340                                  0;
341     }
342     if(is_width_flipped)
343     {
344         _cols_out_of_bounds[0] = _start[0] >= static_cast<int32_t>(_input->info()->dimension(1)) ? std::min(static_cast<uint32_t>(_start[0] - _input->info()->dimension(1) + 1),
345                                                                                                             static_cast<uint32_t>(_output->info()->dimension(1))) :
346                                  0;
347         _cols_out_of_bounds[1] = _end[0] < 0 ? std::min(static_cast<uint32_t>(-_end[0]),
348                                                         static_cast<uint32_t>(_output->info()->dimension(1))) :
349                                  0;
350     }
351     else
352     {
353         _cols_out_of_bounds[0] = _start[0] < 0 ? std::min(static_cast<uint32_t>(-_start[0]),
354                                                           static_cast<uint32_t>(_output->info()->dimension(1))) :
355                                  0;
356         _cols_out_of_bounds[1] = _end[0] >= static_cast<int32_t>(_input->info()->dimension(1)) ? std::min(static_cast<uint32_t>(_end[0] - _input->info()->dimension(1) + 1),
357                                                                                                           static_cast<uint32_t>(_output->info()->dimension(1))) :
358                                  0;
359     }
360 
361     INEKernel::configure(calculate_max_window(*_output->info()));
362 }
363 
run(const Window & window,const ThreadInfo & info)364 void NECropKernel::run(const Window &window, const ThreadInfo &info)
365 {
366     ARM_COMPUTE_UNUSED(window, info);
367     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
368     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
369 
370     ARM_COMPUTE_ERROR_ON(_input->info()->has_padding());
371     ARM_COMPUTE_ERROR_ON(_output->info()->has_padding());
372 
373     uint32_t    batch_index = *(reinterpret_cast<int32_t *>(_box_ind->ptr_to_element(Coordinates(_crop_box_ind))));
374     Coordinates input_offset(0, _end[0] < _start[0] ? _start[0] - _cols_out_of_bounds[0] : _start[0] + _cols_out_of_bounds[0],
375                              _end[1] < _start[1] ? _start[1] - _rows_out_of_bounds[0] : _start[1] + _rows_out_of_bounds[0], batch_index);
376     execute_window(_input, _output, input_offset, _extrapolation_value, _rows_out_of_bounds, _cols_out_of_bounds, _in_bounds_crop_function, _end[1] < _start[1],
377                    _cols_out_of_bounds[0] + _cols_out_of_bounds[1] < _output->info()->dimension(1), _cols_out_of_bounds[0] > 0, _cols_out_of_bounds[1] > 0,
378                    _start[0] <= _end[0], _end[0] < _start[0]);
379 }
380 } // namespace arm_compute
381