Compute Library
 21.02
NEFFTDigitReverseKernel.cpp
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25 
28 #include "arm_compute/core/Types.h"
33 
34 #include <set>
35 
36 namespace arm_compute
37 {
38 namespace
39 {
40 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *idx, const FFTDigitReverseKernelInfo &config)
41 {
42  ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() != DataType::F32);
43  ARM_COMPUTE_RETURN_ERROR_ON(input->num_channels() > 2);
45  ARM_COMPUTE_RETURN_ERROR_ON(std::set<unsigned int>({ 0, 1 }).count(config.axis) == 0);
46  ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[config.axis] != idx->tensor_shape().x());
47 
48  // Checks performed when output is configured
49  if((output != nullptr) && (output->total_size() != 0))
50  {
51  ARM_COMPUTE_RETURN_ERROR_ON(output->num_channels() != 2);
54  }
55 
56  return Status{};
57 }
58 
59 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, ITensorInfo *idx, const FFTDigitReverseKernelInfo &config)
60 {
61  ARM_COMPUTE_UNUSED(idx, config);
62 
63  auto_init_if_empty(*output, input->clone()->set_num_channels(2));
64 
65  Window win = calculate_max_window(*input, Steps());
66  input->set_valid_region(ValidRegion(Coordinates(), input->tensor_shape()));
67 
68  return std::make_pair(Status{}, win);
69 }
70 } // namespace
71 
73  : _func(nullptr), _input(nullptr), _output(nullptr), _idx(nullptr)
74 {
75 }
76 
77 void NEFFTDigitReverseKernel::configure(const ITensor *input, ITensor *output, const ITensor *idx, const FFTDigitReverseKernelInfo &config)
78 {
79  ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, idx);
80  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), idx->info(), config));
81 
82  _input = input;
83  _output = output;
84  _idx = idx;
85 
86  const size_t axis = config.axis;
87  const bool is_conj = config.conjugate;
88  const bool is_input_complex = (input->info()->num_channels() == 2);
89 
90  // Configure kernel window
91  auto win_config = validate_and_configure_window(input->info(), output->info(), idx->info(), config);
92  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
93  INEKernel::configure(win_config.second);
94 
95  if(axis == 0)
96  {
97  if(is_input_complex)
98  {
99  if(is_conj)
100  {
101  _func = &NEFFTDigitReverseKernel::digit_reverse_kernel_axis_0<true, true>;
102  }
103  else
104  {
105  _func = &NEFFTDigitReverseKernel::digit_reverse_kernel_axis_0<true, false>;
106  }
107  }
108  else
109  {
110  _func = &NEFFTDigitReverseKernel::digit_reverse_kernel_axis_0<false, false>;
111  }
112  }
113  else if(axis == 1)
114  {
115  if(is_input_complex)
116  {
117  if(is_conj)
118  {
119  _func = &NEFFTDigitReverseKernel::digit_reverse_kernel_axis_1<true, true>;
120  }
121  else
122  {
123  _func = &NEFFTDigitReverseKernel::digit_reverse_kernel_axis_1<true, false>;
124  }
125  }
126  else
127  {
128  _func = &NEFFTDigitReverseKernel::digit_reverse_kernel_axis_1<false, false>;
129  }
130  }
131  else
132  {
133  ARM_COMPUTE_ERROR("Not supported");
134  }
135 }
136 
138 {
139  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, idx, config));
140  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), idx->clone().get(), config).first);
141  return Status{};
142 }
143 
144 template <bool is_input_complex, bool is_conj>
145 void NEFFTDigitReverseKernel::digit_reverse_kernel_axis_0(const Window &window)
146 {
147  const size_t N = _input->info()->dimension(0);
148 
149  // Copy the look-up buffer to a local array
150  std::vector<unsigned int> buffer_idx(N);
151  std::copy_n(reinterpret_cast<unsigned int *>(_idx->buffer()), N, buffer_idx.data());
152 
153  // Input/output iterators
154  Window slice = window;
155  slice.set(0, Window::DimX);
156  Iterator in(_input, slice);
157  Iterator out(_output, slice);
158 
159  // Row buffers
160  std::vector<float> buffer_row_out(2 * N);
161  std::vector<float> buffer_row_in(2 * N);
162 
163  execute_window_loop(slice, [&](const Coordinates &)
164  {
165  if(is_input_complex)
166  {
167  // Load
168  memcpy(buffer_row_in.data(), reinterpret_cast<float *>(in.ptr()), 2 * N * sizeof(float));
169 
170  // Shuffle
171  for(size_t x = 0; x < 2 * N; x += 2)
172  {
173  size_t idx = buffer_idx[x / 2];
174  buffer_row_out[x] = buffer_row_in[2 * idx];
175  buffer_row_out[x + 1] = (is_conj ? -buffer_row_in[2 * idx + 1] : buffer_row_in[2 * idx + 1]);
176  }
177  }
178  else
179  {
180  // Load
181  memcpy(buffer_row_in.data(), reinterpret_cast<float *>(in.ptr()), N * sizeof(float));
182 
183  // Shuffle
184  for(size_t x = 0; x < N; ++x)
185  {
186  size_t idx = buffer_idx[x];
187  buffer_row_out[2 * x] = buffer_row_in[idx];
188  }
189  }
190 
191  // Copy back
192  memcpy(reinterpret_cast<float *>(out.ptr()), buffer_row_out.data(), 2 * N * sizeof(float));
193  },
194  in, out);
195 }
196 
197 template <bool is_input_complex, bool is_conj>
198 void NEFFTDigitReverseKernel::digit_reverse_kernel_axis_1(const Window &window)
199 {
200  const size_t Nx = _input->info()->dimension(0);
201  const size_t Ny = _input->info()->dimension(1);
202 
203  // Copy the look-up buffer to a local array
204  std::vector<unsigned int> buffer_idx(Ny);
205  std::copy_n(reinterpret_cast<unsigned int *>(_idx->buffer()), Ny, buffer_idx.data());
206 
207  // Output iterator
208  Window slice = window;
209  slice.set(0, Window::DimX);
210  Iterator out(_output, slice);
211 
212  // Row buffer
213  std::vector<float> buffer_row(Nx);
214 
215  // Strides
216  const size_t stride_z = _input->info()->strides_in_bytes()[2];
217  const size_t stride_w = _input->info()->strides_in_bytes()[3];
218 
219  execute_window_loop(slice, [&](const Coordinates & id)
220  {
221  auto *out_ptr = reinterpret_cast<float *>(out.ptr());
222  auto *in_ptr = reinterpret_cast<float *>(_input->buffer() + id.z() * stride_z + id[3] * stride_w);
223  const size_t y_shuffled = buffer_idx[id.y()];
224 
225  if(is_input_complex)
226  {
227  // Shuffle the entire row into the output
228  memcpy(out_ptr, in_ptr + 2 * Nx * y_shuffled, 2 * Nx * sizeof(float));
229 
230  // Conjugate if necessary
231  if(is_conj)
232  {
233  for(size_t x = 0; x < 2 * Nx; x += 2)
234  {
235  out_ptr[x + 1] = -out_ptr[x + 1];
236  }
237  }
238  }
239  else
240  {
241  // Shuffle the entire row into the buffer
242  memcpy(buffer_row.data(), in_ptr + Nx * y_shuffled, Nx * sizeof(float));
243 
244  // Copy the buffer to the output, with a zero imaginary part
245  for(size_t x = 0; x < 2 * Nx; x += 2)
246  {
247  out_ptr[x] = buffer_row[x / 2];
248  }
249  }
250  },
251  out);
252 }
253 
255 {
258  ARM_COMPUTE_UNUSED(info);
259  (this->*_func)(window);
260 }
261 
262 } // namespace arm_compute
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
void run(const Window &window, const ThreadInfo &info) override
Execute the kernel on the passed window.
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
#define ARM_COMPUTE_ERROR(msg)
Print the given message then throw an std::runtime_error.
Definition: Error.h:352
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
1 channel, 1 F32 per channel
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *idx, const FFTDigitReverseKernelInfo &config)
Static function to check if given info will lead to a valid configuration of NEFFTDigitReverseKernel...
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
Interface for Neon tensor.
Definition: ITensor.h:36
unsigned int N
Copyright (c) 2017-2021 Arm Limited.
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
Coordinates of an item.
Definition: Coordinates.h:37
virtual uint8_t * buffer() const =0
Interface to be implemented by the child class to return a pointer to CPU memory. ...
bool conjugate
Flag to conjugate the output/.
bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())
Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...
virtual std::unique_ptr< T > clone() const =0
Provide a clone of the current object of class T.
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
constexpr uint8_t * ptr() const
Return a pointer to the current pixel.
Definition: Helpers.inl:139
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
unsigned int axis
Axis to perform the kernel on.
void configure(const ITensor *input, ITensor *output, const ITensor *idx, const FFTDigitReverseKernelInfo &config)
Set the input and output tensors.
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
Information about executing thread and CPU.
Definition: CPPTypes.h:235
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)
Definition: Validate.h:443
Descriptor for FFT digit reverse kernels.
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)
Definition: Validate.h:545
#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:792
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
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
virtual const Strides & strides_in_bytes() const =0
The strides in bytes for accessing each dimension of the tensor.
Iterator updated by execute_window_loop for each window element.
Definition: Helpers.h:46
Describe a multidimensional execution window.
Definition: Window.h:39
virtual size_t num_channels() const =0
The number of channels for each tensor element.
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)