Compute Library
 21.05
CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
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25 
29 #include "arm_compute/core/Utils.h"
32 #include "src/core/CL/CLUtils.h"
33 #include "src/core/CL/CLValidate.h"
38 #include "support/StringSupport.h"
39 
40 #include <tuple>
41 
43 
44 namespace arm_compute
45 {
46 namespace
47 {
48 using ElementsProcessed = Steps;
49 
50 Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info,
51  const GEMMRHSMatrixInfo &rhs_info,
52  const GEMMKernelInfo &gemm_info)
53 {
54  ARM_COMPUTE_UNUSED(alpha);
55  ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input0, input1, output);
59  ARM_COMPUTE_RETURN_ERROR_ON_MSG(input0->num_dimensions() > 4, "The number of dimensions for the LHS matrix must be <= 4");
60  ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the RHS matrix must be <= 3");
61  ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_info.m0 < 1 || lhs_info.m0 > 8, "Only 1,2,3,4,5,6,7,8 are supported for m0");
62  ARM_COMPUTE_RETURN_ERROR_ON(rhs_info.k0 > 16 || rhs_info.k0 < 2);
63  ARM_COMPUTE_RETURN_ERROR_ON_MSG(((rhs_info.k0 & (rhs_info.k0 - 1)) && rhs_info.k0 != 3), "Only 2,3,4,8,16 are supported for k0");
64  ARM_COMPUTE_RETURN_ERROR_ON(rhs_info.n0 > 16 || rhs_info.n0 < 2);
65  ARM_COMPUTE_RETURN_ERROR_ON_MSG(((rhs_info.n0 & (rhs_info.n0 - 1)) && rhs_info.n0 != 3), "Only 2,3,4,8,16 are supported for n0");
66  ARM_COMPUTE_RETURN_ERROR_ON_MSG((gemm_info.reinterpret_input_as_3d || gemm_info.depth_output_gemm3d != 0) && (input2 != nullptr)
67  && (!gemm_info.broadcast_bias),
68  "Bias addition only supported with broadcast mode in case the input or output has to be reinterpreted as 3D");
69  ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.fp_mixed_precision, "Mixed precision not supported");
71 
72  const unsigned int m = gemm_info.m;
73  const unsigned int n = gemm_info.n;
74  const unsigned int k = gemm_info.k;
75 
76  TensorShape tensor_shape1{ input1->tensor_shape() };
77  tensor_shape1.set(0, n);
78  tensor_shape1.set(1, k);
79 
80  if(input2 != nullptr && !(helpers::float_ops::is_zero(beta)))
81  {
82  const unsigned int input2_dim0 = input2->dimension(0);
83  const unsigned int input2_dim1 = input2->dimension(1);
84 
86  if(gemm_info.broadcast_bias)
87  {
88  ARM_COMPUTE_RETURN_ERROR_ON_MSG((input2_dim1 != 1 || input2_dim0 != n), "Incorrect dimension of bias matrix which is to be broadcasted");
89  }
90  else
91  {
92  ARM_COMPUTE_RETURN_ERROR_ON_MSG((input2_dim0 != n || input2_dim1 != m), "Incorrect dimension of bias matrix");
93  }
94  }
95 
96  const TensorInfo tensor_info1 = input1->clone()->set_tensor_shape(tensor_shape1);
97 
98  const TensorInfo tensor_info_reshaped1 = input1->clone()->set_tensor_shape(compute_rhs_reshaped_shape(tensor_info1, rhs_info));
99 
100  ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != k);
101  if(gemm_info.reinterpret_input_as_3d)
102  {
103  ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) * input0->dimension(2) != m);
104  }
105  else
106  {
107  ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) != m);
108  }
109  ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, &tensor_info_reshaped1);
110 
111  if(output->total_size() != 0)
112  {
113  const TensorInfo tensor_info_output = output->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, gemm_info));
114  ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output);
116  }
117 
118  return Status{};
119 }
120 
121 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const GEMMLHSMatrixInfo &lhs_info,
122  const GEMMRHSMatrixInfo &rhs_info,
123  const GEMMKernelInfo &gemm_info, ElementsProcessed &num_elements_processed)
124 {
125  unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0];
126  unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1];
127  bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d;
128  bool reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0;
129 
130  Window win{};
131  Window win_out{};
132  bool window_changed = false;
133 
134  // In case both input and output have to be reinterpreted as 3D tensors,
135  // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
136  // This approach should only be used when the input/output tensors have pad on the y direction
137  if((reinterpret_input_as_3d == reinterpret_output_as_3d) && gemm_info.has_pad_y)
138  {
139  reinterpret_output_as_3d = false;
140  }
141 
142  // Output tensor auto initialization if not yet initialized
143  auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, gemm_info)));
144 
145  TensorInfo tmp_info(*output);
146 
147  if(reinterpret_output_as_3d)
148  {
149  // Since the output tensor has to be reinterpreted as 3D and the execute window is based on a 2D GEMM,
150  // the window needs to be constructed on the 2D collapsed version of the tensor
151  TensorShape tmp_shape(output->tensor_shape());
152  tmp_shape.collapse(2U, 1U);
153  tmp_info.set_tensor_shape(tmp_shape);
154  }
155 
156  // Configure kernel window
157  num_elems_processed_per_iteration_x = rhs_info.n0;
158  num_elems_processed_per_iteration_y = lhs_info.m0;
159 
160  win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
161  win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
162 
163  if(input2 != nullptr)
164  {
165  const int bias_processed_per_iteration_x = num_elems_processed_per_iteration_x;
166 
167  AccessWindowStatic input2_access(input2, 0, 0,
168  ceil_to_multiple(input2->dimension(0), bias_processed_per_iteration_x),
169  input2->dimension(1));
170 
171  window_changed = update_window_and_padding(win, input2_access);
172  }
173 
174  // Collapse along the Z direction
175  // This collapse needs to be here in order to tune the Z dimension of LWS
176  Window collapsed = win;
177  const unsigned int dimension_to_collapse = std::min(static_cast<unsigned int>(output->num_dimensions()), 2u);
178  collapsed = win.collapse(win, dimension_to_collapse);
179 
180  Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
181  return std::make_pair(err, collapsed);
182 }
183 } // namespace
184 
186  : _input0(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_input_as_3d(false), _reinterpret_output_as_3d(false), _use_dummy_work_items(false),
187  _add_bias(false), _broadcast_bias(false), _export_to_cl_image(false), _has_pad_y(false)
188 {
189 }
190 
191 void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
192  const GEMMLHSMatrixInfo &lhs_info,
193  const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
194 {
195  configure(CLKernelLibrary::get().get_compile_context(), input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info);
196 }
197 
198 void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output,
199  float alpha,
200  float beta,
201  const GEMMLHSMatrixInfo &lhs_info,
202  const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
203 {
204  ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
205 
206  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), (input2 != nullptr ? input2->info() : nullptr), output->info(), alpha, beta, lhs_info, rhs_info, gemm_info));
207 
208  _input0 = input0;
209  _input1 = input1;
210  _input2 = helpers::float_ops::is_zero(beta) ? nullptr : input2;
211  _output = output;
212  _reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d;
213  _reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0;
214  _use_dummy_work_items = preferred_dummy_work_items_support(CLKernelLibrary::get().get_device());
215  _add_bias = _input2 != nullptr;
216  _broadcast_bias = gemm_info.broadcast_bias;
217  _export_to_cl_image = rhs_info.export_to_cl_image;
218  _has_pad_y = gemm_info.has_pad_y;
219 
220  auto padding_info = get_padding_info({ input0, input1, output });
221 
222  // In case both input and output have to be reinterpreted as 3D tensors,
223  // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
224  if((_reinterpret_input_as_3d == _reinterpret_output_as_3d) && _has_pad_y)
225  {
226  _reinterpret_input_as_3d = false;
227  _reinterpret_output_as_3d = false;
228  }
229 
230  // Check if we need to slide the matrix B
231  const unsigned int num_dimensions_input0 = _input0->info()->num_dimensions();
232  _slide_matrix_b = (_input1->info()->num_dimensions() >= num_dimensions_input0);
233 
234  ElementsProcessed num_elements_processed{};
235 
236  // Configure kernel window
237  auto win_config = validate_and_configure_window(input0->info(), input1->info(), input2 != nullptr ? input2->info() : nullptr, output->info(), lhs_info, rhs_info, gemm_info, num_elements_processed);
238  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
239  ICLKernel::configure_internal(win_config.second);
240 
241  // If _reinterpret_input_as_3d = _reinterpret_output_as_3d = true,
242  // we will dispatch a batched-GEMM to reduce the complexity of the address calculation within the OpenCL kernel.
243  // This means that the actual m used by the kernel is given by output->info()->dimension(1) and not by gemm_info.m
244  const unsigned int internal_m = _reinterpret_output_as_3d ? gemm_info.m : output->info()->dimension(1);
245 
246  // These variables are used only if gemm_info.has_pad_y == true
247  const unsigned int h_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(1) : input0->info()->dimension(1);
248  const unsigned int d_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(2) : input0->info()->dimension(2);
249 
250  // Shrink M0 to be always <= M (internal_m) to prevent out-of-bounds reads.
251  // NOTE: This might have implications on heuristics and performance
252  const unsigned int internal_m0 = std::min(internal_m, lhs_info.m0);
253 
254  // Calculate partial (store instead of load) M0 and partial N0 for the partial blocks at the end of a row/column if any. This is to avoid padding.
255  const unsigned int partial_store_m0 = internal_m % internal_m0;
256  const unsigned int partial_store_n0 = gemm_info.n % rhs_info.n0;
257 
258  // Create build options
259  CLBuildOptions build_opts;
260  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()));
261  build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha));
262  build_opts.add_option_if(_input2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
263  build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
264  build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS");
265  build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
266  build_opts.add_option_if(rhs_info.interleave, "-DRHS_INTERLEAVE");
267  build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS");
268  build_opts.add_option_if(rhs_info.export_to_cl_image, "-DOPENCL_IMAGE_SUPPORT");
269  build_opts.add_option("-DRHS_HEIGHT=" + support::cpp11::to_string(input1->info()->dimension(1)));
270  build_opts.add_option("-DM=" + support::cpp11::to_string(internal_m));
271  build_opts.add_option("-DN=" + support::cpp11::to_string(gemm_info.n));
272  build_opts.add_option("-DK=" + support::cpp11::to_string(gemm_info.k));
273  build_opts.add_option("-DM0=" + support::cpp11::to_string(internal_m0));
274  build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0));
275  build_opts.add_option("-DK0=" + support::cpp11::to_string(rhs_info.k0));
276  build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0));
277  build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0));
278  build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0));
279  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
280  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
281  build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
282  if(_has_pad_y)
283  {
284  build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D");
285  build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
286  build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(h_gemm_3d));
287  build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(d_gemm_3d));
288  }
289 
290  std::string kernel_name("gemm_mm_reshaped_only_rhs_");
291  kernel_name += rhs_info.transpose ? "t" : "nt";
292  kernel_name += rhs_info.export_to_cl_image ? "_texture" : "";
293 
294  // Create kernel
295  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
296 
297  // Set config_id for enabling LWS tuning
298  _config_id = kernel_name;
299  _config_id += "_";
300  _config_id += (_has_pad_y ? "" : "no_pad_y_");
301  _config_id += (_add_bias ? "add_bias_" : "");
302  _config_id += (_broadcast_bias ? "broadcast_bias_" : "");
303  _config_id += (_reinterpret_input_as_3d ? "3di_" : "");
304  _config_id += (_reinterpret_output_as_3d ? "3do_" : "");
305  _config_id += (gemm_info.activation_info.enabled() ? "fused_activation_" : "");
306  _config_id += lower_string(string_from_data_type(input0->info()->data_type()));
307  _config_id += "_";
308  _config_id += support::cpp11::to_string(output->info()->dimension(1));
309  _config_id += "_";
310  _config_id += support::cpp11::to_string(output->info()->dimension(0));
311  _config_id += "_";
312  _config_id += support::cpp11::to_string(gemm_info.k);
313  _config_id += "_";
314  _config_id += support::cpp11::to_string(output->info()->dimension(2));
315  _config_id += "_";
316  _config_id += support::cpp11::to_string(lhs_info.m0);
317  _config_id += "_";
318  _config_id += support::cpp11::to_string(rhs_info.n0);
319  _config_id += "_";
320  _config_id += support::cpp11::to_string(rhs_info.k0);
321  _config_id += "_";
322  _config_id += support::cpp11::to_string(rhs_info.h0);
323  _config_id += "_";
324  _config_id += support::cpp11::to_string(rhs_info.interleave);
325 
327 }
328 
329 Status CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta,
330  const GEMMLHSMatrixInfo &lhs_info,
331  const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
332 {
333  ElementsProcessed num_elements_processed{};
334  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info));
335  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
336  input1->clone().get(),
337  input2 != nullptr ? input2->clone().get() : nullptr,
338  output->clone().get(),
339  lhs_info,
340  rhs_info,
341  gemm_info,
342  num_elements_processed)
343  .first);
344 
345  return Status{};
346 }
347 
348 void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::run(const Window &window, cl::CommandQueue &queue)
349 {
352 
353  if(_input1->info()->num_dimensions() < 3)
354  {
355  // The stride_z for matrix B must be zero if we do not slice
356  ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0);
357  }
358 
359  const size_t lhs_idx_batch_size = _reinterpret_input_as_3d && !_has_pad_y ? 3u : 2u;
360  const size_t rhs_idx_batch_size = 2u;
361  const size_t bia_idx_batch_size = 2u;
362  const size_t out_idx_batch_size = _reinterpret_output_as_3d && !_has_pad_y ? 3u : 2u;
363 
365  Window slice_matrix_b = slice;
366 
367  slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
368  slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
369 
370  // Get cross plane pads
371  const unsigned int total_cross_plane_pad_lhs = _input0->info()->padding().top + _input0->info()->padding().bottom;
372  const unsigned int total_cross_plane_pad_out = _output->info()->padding().top + _output->info()->padding().bottom;
373 
374  // The execution should fail if we try to run with has_pad_y = false but we have padding in either the LHS or DST tensor
375  ARM_COMPUTE_ERROR_ON(!_has_pad_y && ((total_cross_plane_pad_lhs != 0) || (total_cross_plane_pad_out != 0)));
376 
377  cl::Image2D input1_image2d;
378 
379  if(_export_to_cl_image)
380  {
381  const TensorShape shape2d(_input1->info()->dimension(0) / 4, _input1->info()->dimension(1) * _input1->info()->dimension(2));
382  const size_t image_row_pitch = _input1->info()->strides_in_bytes()[1];
383 
384  input1_image2d = create_image2d_from_buffer(CLKernelLibrary::get().context(), _input1->cl_buffer(), shape2d, _input1->info()->data_type(), image_row_pitch);
385  }
386 
387  do
388  {
389  Window slice_b = slice;
390  // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
391  // This scenario can happen when the matrix multiplication is used to perform a convolution operation
392  if(!_slide_matrix_b)
393  {
394  slice_b = slice_matrix_b;
395  }
396 
397  unsigned int idx = 0;
398 
399  // LHS buffer
400  add_2D_tensor_argument(idx, _input0, slice);
401 
402  // RHS buffer or RHS OpenCL image (_export_to_cl_image == true)
403  if(_export_to_cl_image)
404  {
405  _kernel.setArg(idx++, input1_image2d);
406  }
407  else
408  {
409  add_2D_tensor_argument(idx, _input1, slice_b);
410  }
411 
412  // Bias buffer (_add_bias == true)
413  add_2D_tensor_argument_if(_add_bias, idx, _input2, slice);
414 
415  // Output buffer
416  add_2D_tensor_argument(idx, _output, slice);
417 
418  // LHS stride_z
419  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[lhs_idx_batch_size]));
420 
421  // RHS stride_z (not used if _export_to_cl_image == true)
422  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[rhs_idx_batch_size]));
423 
424  // Bias stride_z (if _add_bias == true)
425  if(_add_bias)
426  {
427  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[bia_idx_batch_size]));
428  }
429 
430  // Output stride_z
431  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[out_idx_batch_size]));
432 
433  // Cross-plan padding (if _reinterpret_input_as_3d = true)
434  if(_reinterpret_input_as_3d && _has_pad_y)
435  {
436  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(total_cross_plane_pad_lhs));
437  }
438 
439  // Cross-plan padding (if _reinterpret_output_as_3d = true)
440  if(_reinterpret_output_as_3d && _has_pad_y)
441  {
442  _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(total_cross_plane_pad_out));
443  }
444 
445  enqueue(queue, *this, slice, lws_hint(), _use_dummy_work_items);
446  }
448 }
449 } // namespace arm_compute
unsigned int top
top of the border
Definition: Types.h:375
virtual size_t num_dimensions() const =0
The number of dimensions of the tensor (rank)
bool is_one(float a, float epsilon=0.00001f)
Checks if the input floating point number is 1.0f checking if the difference is within a range define...
Definition: float_ops.h:97
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
bool broadcast_bias
Flag used to broadcast the bias addition.
#define ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(tensor)
Definition: CLValidate.h:35
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
Shape of a tensor.
Definition: TensorShape.h:39
Descriptor used by the GEMM kernels.
void add_2D_tensor_argument_if(bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx ...
Definition: ICLKernel.h:159
std::unordered_map< const ITensorInfo *, PaddingSize > get_padding_info(std::initializer_list< const ITensorInfo * > infos)
Stores padding information before configuring a kernel.
Definition: Utils.cpp:489
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
void enqueue(cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)
Add the kernel to the command queue with the given window.
Definition: ICLKernel.cpp:32
const StringSet & options() const
Gets the current options list set.
static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
Static function to check if given info will lead to a valid configuration of CLGEMMMatrixMultiplyResh...
unsigned int depth_output_gemm3d
Depth of the output tensor in case is reinterpreted as 3D.
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:276
bool preferred_dummy_work_items_support(const cl::Device &device)
Helper function to check if "dummy work-items" are preferred to have a power of two NDRange In case d...
Definition: CLHelpers.cpp:361
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
std::string to_string(T &&value)
Convert integer and float values to string.
virtual DataType data_type() const =0
Data type used for each element of the tensor.
TensorShape compute_mm_shape(const ITensorInfo &input0, const ITensorInfo &input1, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info)
Calculate the matrix multiplication output shape of two tensors.
Status validate_image2d_support_on_rhs(const ITensorInfo &tensor_reshaped_info, const GEMMRHSMatrixInfo &rhs_info)
Utility function to validate the image2d OpenCL object support on the RHS reshaped matrix.
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
const std::string & string_from_activation_func(ActivationLayerInfo::ActivationFunction act)
Translates a given activation function to a string.
Definition: Utils.cpp:163
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
GEMM LHS (Left Hand Side) matrix information.
Definition: Types.h:1903
Store the tensor's metadata.
Definition: ITensorInfo.h:40
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
Describe one of the image's dimensions with a start, end and step.
Definition: Window.h:77
unsigned int bottom
bottom of the border
Definition: Types.h:377
Status class.
Definition: Error.h:52
std::string lower_string(const std::string &val)
Lower a given string.
Definition: Utils.cpp:326
#define ARM_COMPUTE_RETURN_ERROR_ON(cond)
If the condition is true, an error is returned.
Definition: Error.h:296
Copyright (c) 2017-2021 Arm Limited.
1 channel, 1 F16 per channel
#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)
Definition: Validate.h:159
void add_option(std::string option)
Adds option to the existing build option list.
cl::Kernel create_kernel(const CLCompileContext &ctx, const std::string &kernel_name, const std::set< std::string > &build_opts=std::set< std::string >())
Creates an opencl kernel using a compile context.
Definition: CLHelpers.cpp:403
const std::string & string_from_data_type(DataType dt)
Convert a data type identity into a string.
Definition: Utils.cpp:135
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
bool update_window_and_padding(Window &win, Ts &&... patterns)
Update window and padding size for each of the access patterns.
Definition: WindowHelpers.h:46
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
GEMM RHS (Right Hand Side) matrix information.
Definition: Types.h:1918
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1061
auto ceil_to_multiple(S value, T divisor) -> decltype(((value+divisor - 1)/divisor) *divisor)
Computes the smallest number larger or equal to value that is a multiple of divisor.
Definition: Utils.h:71
std::string kernel_name
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:37
TensorShape compute_rhs_reshaped_shape(const ITensorInfo &a, const GEMMRHSMatrixInfo &rhs_info)
Calculate the Right Hand Side matrix reshaped shape.
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...
bool reinterpret_input_as_3d
Flag used to reinterpret the input as 3D.
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's metadata.
void add_option_if(bool cond, std::string option)
Adds option if a given condition is true;.
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
virtual PaddingSize padding() const =0
Padding of tensor.
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:335
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
bool has_padding_changed(const std::unordered_map< const ITensorInfo *, PaddingSize > &padding_map)
Check if the previously stored padding info has changed after configuring a kernel.
Definition: Utils.cpp:504
CLCompileContext class.
void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
Initialise the kernel's input and output.
bool has_pad_y
Flag used to indicate if the input/output tensors have internal pad on the y direction.
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
void add_2D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx.
Definition: ICLKernel.h:148
Interface for OpenCL tensor.
Definition: ICLTensor.h:42
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)
Definition: Validate.h:439
#define ARM_COMPUTE_CREATE_ERROR(error_code, msg)
Creates an error with a given message.
Definition: Error.h:159
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)
Definition: Validate.h:541
#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:788
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
void run(const Window &window, cl::CommandQueue &queue) override
Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.
bool is_zero(float a, float epsilon=0.00001f)
Checks if the input floating point number is 0.0f checking if the difference is within a range define...
Definition: float_ops.h:109
#define ARM_COMPUTE_RETURN_ERROR_ON_MSG(cond, msg)
If the condition is true, an error is returned.
Definition: Error.h:244
virtual const cl::Buffer & cl_buffer() const =0
Interface to be implemented by the child class to return a reference to the OpenCL buffer containing ...
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
cl::Image2D create_image2d_from_buffer(const cl::Context &ctx, const cl::Buffer &buffer, const TensorShape &shape2d, DataType data_type, size_t image_row_pitch)
Create a cl::Image2D object from an OpenCL buffer.
Definition: CLUtils.cpp:29
virtual const Strides & strides_in_bytes() const =0
The strides in bytes for accessing each dimension of the tensor.
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:291
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:201
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)