Compute Library
 20.05
CLDepthwiseConvolutionLayerNativeKernel.cpp
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1 /*
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25 
31 #include "arm_compute/core/Error.h"
35 #include "arm_compute/core/Types.h"
36 #include "arm_compute/core/Utils.h"
39 #include "support/StringSupport.h"
40 
41 namespace arm_compute
42 {
43 namespace
44 {
45 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info,
46  const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
47  const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts)
48 {
49  ARM_COMPUTE_UNUSED(dwc_info);
54  ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1 && dwc_weights_info.n0 != 1);
55  ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1);
56  ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().second < 1);
57  ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1));
58  const size_t idx_c = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL);
59  ARM_COMPUTE_UNUSED(idx_c);
60  ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_c) != (input->dimension(idx_c) * depth_multiplier));
61 
63 
64  const bool is_quantized = is_data_type_quantized(input->data_type());
65 
66  if(biases != nullptr)
67  {
68  ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != output_shape[idx_c]);
69  ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1);
70 
71  if(is_quantized)
72  {
74  }
75  else
76  {
78  }
79  }
80 
81  if(is_quantized)
82  {
83  ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts);
86  ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1);
87  ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1);
88 
90  {
92  ARM_COMPUTE_RETURN_ERROR_ON(output_shape[idx_c] != output_multipliers->dimension(0));
93  ARM_COMPUTE_RETURN_ERROR_ON(output_shape[idx_c] != output_shifts->dimension(0));
94  }
95  else
96  {
98  ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0));
99  ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0));
100  }
101  }
102  else
103  {
105  }
106 
107  if(output->total_size() != 0)
108  {
111  }
112 
113  if(is_data_type_quantized(input->data_type()))
114  {
115  const UniformQuantizationInfo iq_info = input->quantization_info().uniform();
116  const UniformQuantizationInfo wq_info = weights->quantization_info().uniform();
117  const UniformQuantizationInfo oq_info = (output->total_size() != 0) ? output->quantization_info().uniform() : iq_info;
118 
119  float multiplier = iq_info.scale * wq_info.scale / oq_info.scale;
120  int output_multiplier = 0;
121  int output_shift = 0;
122  ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift));
123  }
124 
125  return Status{};
126 }
127 
128 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info,
129  const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
130  ITensorInfo *output_multipliers, ITensorInfo *output_shifts)
131 {
132  ARM_COMPUTE_UNUSED(dwc_info);
133 
134  // Get convolved dimensions
136 
137  auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_quantization_info(output->quantization_info()));
138 
139  const unsigned int n0 = dwc_weights_info.n0;
140 
141  // Configure kernel window
142  Window win = calculate_max_window(*output, Steps(n0));
143 
144  // The following access windows are only valid in case of NHWC and because n0 must unit in case depth_multiplier > 1
145  AccessWindowHorizontal input_access(input, 0, n0);
146  AccessWindowHorizontal weights_access(weights, 0, n0);
147  AccessWindowHorizontal output_access(output, 0, n0);
148 
149  bool window_changed = false;
150 
151  if(bias != nullptr)
152  {
153  AccessWindowHorizontal bias_access(bias, 0, n0);
154  window_changed = update_window_and_padding(win, input_access, weights_access, bias_access, output_access);
155  }
156  else
157  {
158  window_changed = update_window_and_padding(win, input_access, weights_access, output_access);
159  }
160 
161  if(is_data_type_quantized(input->data_type()))
162  {
163  if((output_multipliers != nullptr) && (output_shifts != nullptr))
164  {
165  AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, n0);
166  AccessWindowHorizontal output_shifts_access(output_shifts, 0, n0);
167  window_changed = window_changed || update_window_and_padding(win, output_multipliers_access, output_shifts_access);
168  }
169  else
170  {
171  Status err = ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "output_multipliers and output_shifts must be non-nullptr for quantized input");
172  return std::make_pair(err, win);
173  }
174  }
175 
176  output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
177 
178  Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
179  return std::make_pair(err, win);
180 }
181 } // namespace
182 
184  : _input(nullptr),
185  _weights(nullptr),
186  _biases(nullptr),
187  _output(nullptr),
188  _depth_multiplier(1),
189  _output_multipliers(nullptr),
190  _output_shifts(nullptr),
191  _is_quantized(false)
192 {
193 }
194 
196  const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
197  const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
198 {
199  configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, output_multipliers, output_shifts);
200 }
201 
203  const DWCWeightsKernelInfo &dwc_weights_info,
204  const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
205  const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
206 {
208  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(),
209  dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation,
210  (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr));
211 
212  auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(),
213  dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation,
214  (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr);
215  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
216 
217  _input = input;
218  _output = output;
219  _weights = weights;
220  _biases = biases;
221  _depth_multiplier = depth_multiplier;
222  _output_multipliers = output_multipliers;
223  _output_shifts = output_shifts;
224  _is_quantized = is_data_type_quantized(input->info()->data_type());
225 
226  const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH);
227  const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT);
228  const size_t weights_width = weights->info()->dimension(idx_w);
229  const size_t weights_height = weights->info()->dimension(idx_h);
230 
231  CLBuildOptions build_opts;
232  build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS");
233  build_opts.add_option_if(_input->info()->tensor_shape().total_size_upper(3) > 1, "-DDST_DEPTH=" + support::cpp11::to_string(static_cast<int>(_output->info()->dimension(2))));
234  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type()));
235  build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(dwc_info.activation_info.activation())));
236  build_opts.add_option("-DDEPTH_MULTIPLIER=" + support::cpp11::to_string(depth_multiplier));
237  build_opts.add_option("-DN0=" + support::cpp11::to_string(dwc_weights_info.n0));
238  build_opts.add_option("-DSRC_DIM1=" + support::cpp11::to_string(_input->info()->dimension(1)));
239  build_opts.add_option("-DSRC_DIM2=" + support::cpp11::to_string(_input->info()->dimension(2)));
240  build_opts.add_option("-DKERNEL_WIDTH=" + support::cpp11::to_string(weights_width));
241  build_opts.add_option("-DKERNEL_HEIGHT=" + support::cpp11::to_string(weights_height));
242  build_opts.add_option("-DCONV_PAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
243  build_opts.add_option("-DCONV_PAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
244  build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(conv_info.stride().first));
245  build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(conv_info.stride().second));
246  build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
247  build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
248 
249  std::string kernel_name = (_is_quantized) ? "dwc_MxN_native_quantized8_nhwc" : "dwc_MxN_native_fp_nhwc";
250 
251  if(_is_quantized)
252  {
253  const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform();
254  const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform();
255  const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform();
256 
257  build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset));
258  build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset));
259  build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_info.offset));
260  build_opts.add_option_if(is_data_type_quantized_per_channel(weights->info()->data_type()), "-DPER_CHANNEL_QUANTIZATION");
261 
262  // Compute non-per-channel multiplier and shift anyway to make OpenCL kernel simpler
263  float multiplier = iq_info.scale * wq_info.scale / oq_info.scale;
264  int output_multiplier = 0;
265  int output_shift = 0;
266  quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
267  build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier));
268  build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift));
269 
270  if(dwc_info.activation_info.enabled())
271  {
272  const int a_val = quantize_qasymm8(dwc_info.activation_info.a(), oq_info);
273  const int b_val = quantize_qasymm8(dwc_info.activation_info.b(), oq_info);
274  const int o1 = oq_info.offset;
275 
276  build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val));
277  build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val));
278  build_opts.add_option("-DCONST_0=" + support::cpp11::to_string(o1));
279 
280  const float s1 = iq_info.scale;
281  build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1));
282  build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1));
283  }
284 
285  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
286  build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type()));
287  }
288  else
289  {
290  build_opts.add_option_if(dwc_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(dwc_info.activation_info.a()));
291  build_opts.add_option_if(dwc_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(dwc_info.activation_info.b()));
292  }
293 
294  ICLKernel::configure_internal(win_config.second);
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 += support::cpp11::to_string(input->info()->dimension(0));
301  _config_id += "_";
302  _config_id += support::cpp11::to_string(input->info()->dimension(1));
303  _config_id += "_";
304  _config_id += support::cpp11::to_string(input->info()->dimension(2));
305  _config_id += "_";
306  _config_id += support::cpp11::to_string(output->info()->dimension(0));
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(2));
311  _config_id += "_";
312  _config_id += string_from_data_type(input->info()->data_type());
313 }
314 
316  const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info,
317  unsigned int depth_multiplier, const Size2D &dilation, const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts)
318 {
319  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, output_multipliers, output_shifts));
320  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(),
321  biases != nullptr ? biases->clone().get() : nullptr,
322  output->clone().get(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation,
323  output_multipliers != nullptr ? output_multipliers->clone().get() : nullptr,
324  output_shifts != nullptr ? output_shifts->clone().get() : nullptr)
325  .first);
326 
327  return Status{};
328 }
329 
330 void CLDepthwiseConvolutionLayerNativeKernel::run(const Window &window, cl::CommandQueue &queue)
331 {
334 
335  // Collapse window
336  Window window_collapsed = window.collapse(ICLKernel::window(), Window::DimZ);
337  Window slice_in = window.first_slice_window_4D();
338  Window slice_out = window_collapsed.first_slice_window_4D();
339 
340  if(_depth_multiplier != 1)
341  {
342  ARM_COMPUTE_ERROR_ON(slice_out.x().step() != 1);
343  slice_out.set(Window::DimX, Window::Dimension(0, _input->info()->tensor_shape()[0], 1));
344  }
345 
346  unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor();
347 
348  // Set output multipliers in case of quantized data type
349  if(_is_quantized)
350  {
351  add_1D_tensor_argument(idx, _output_multipliers, slice_in);
352  add_1D_tensor_argument(idx, _output_shifts, slice_in);
353  }
354 
355  if(_biases != nullptr)
356  {
357  add_1D_tensor_argument(idx, _biases, slice_in);
358  }
359 
360  do
361  {
362  idx = 0;
363  add_4D_tensor_argument(idx, _input, slice_in);
364  add_4D_tensor_argument(idx, _output, slice_out);
365  add_3D_tensor_argument(idx, _weights, slice_out);
366  enqueue(queue, *this, slice_out, lws_hint());
367  }
368  while(window_collapsed.slide_window_slice_4D(slice_out) && window.slide_window_slice_4D(slice_in));
369 }
370 } // namespace arm_compute
bool is_data_type_quantized(DataType dt)
Check if a given data type is of quantized type.
Definition: Utils.h:1131
#define ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(tensor)
Definition: CLValidate.h:34
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info, unsigned int depth_multiplier, const Size2D &dilation=Size2D(1U, 1U))
Calculate the depthwise convolution output shape of a tensor.
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:39
const StringSet & options() const
Gets the current options list set.
unsigned int n0
Number of columns processed by each thread.
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)
Definition: Validate.h:545
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.
constexpr int step() const
Return the step of the dimension.
Definition: Window.h:102
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:247
#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.
#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:792
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
size_t total_size_upper(size_t dimension) const
Collapses given dimension and above.
Definition: TensorShape.h:181
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
Store the tensor's metadata.
Definition: ITensorInfo.h:40
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
Quantization info when assuming per layer quantization.
Describe one of the image's dimensions with a start, end and step.
Definition: Window.h:75
Status calculate_quantized_multiplier(float multiplier, int32_t *quant_multiplier, int32_t *shift, bool ignore_epsilon=false)
Calculate quantized representation of multiplier.
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
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps=Steps(), bool skip_border=false, BorderSize border_size=BorderSize())
Calculate the maximum window for a given tensor shape and border setting.
Definition: Helpers.cpp:28
void add_3D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx.
Definition: ICLKernel.h:158
Copyright (c) 2017-2020 ARM Limited.
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...
Definition: Helpers.inl:202
1 channel, 1 F16 per channel
ITensorInfo * info() const override
Interface to be implemented by the child class to return the tensor's metadata.
Definition: Tensor.cpp:33
1 channel, 1 S32 per channel
void run(const Window &window, cl::CommandQueue &queue) override
Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.
void add_option(std::string option)
Adds option to the existing build option list.
Window collapse(const Window &full_window, size_t first, size_t last=Coordinates::num_max_dimensions) const
Collapse the dimensions between first and last.
Definition: Window.inl:111
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:387
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: Helpers.h:437
static constexpr unsigned int num_arguments_per_3D_tensor()
Returns the number of arguments enqueued per 3D tensor object.
Definition: ICLKernel.h:200
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
bool is_data_type_quantized_per_channel(DataType dt)
Check if a given data type is of per channel type.
Definition: Utils.h:1208
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1225
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(...)
Definition: Validate.h:288
quantized, asymmetric fixed-point 8-bit number unsigned
std::string kernel_name
UniformQuantizationInfo uniform() const
Return per layer quantization info.
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
Descriptor used by the depthwise convolution kernels.
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;.
Padding and stride information class.
Definition: Types.h:689
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
static constexpr unsigned int num_arguments_per_4D_tensor()
Returns the number of arguments enqueued per 4D tensor object.
Definition: ICLKernel.h:208
void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier=1, const Size2D &dilation=Size2D(1U, 1U), const ICLTensor *output_multipliers=nullptr, const ICLTensor *output_shifts=nullptr)
Initialize the function's source, destination and parameters.
Descriptor used by the depthwise convolution kernels to retrieve the number of output elements proces...
virtual QuantizationInfo quantization_info() const =0
Get the quantization settings (scale and offset) of the tensor.
CLCompileContext class.
quantized, symmetric per channel fixed-point 8-bit number
#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)
Definition: Validate.h:163
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
Interface for OpenCL tensor.
Definition: ICLTensor.h:42
#define ARM_COMPUTE_CREATE_ERROR(error_code, msg)
Creates an error with a given message.
Definition: Error.h:159
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
Class for specifying the size of an image or rectangle.
Definition: Size2D.h:34
Num samples, height, width, channels.
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
Window first_slice_window_4D() const
First 4D slice of the window.
Definition: Window.h:297
bool slide_window_slice_4D(Window &slice) const
Slide the passed 4D window slice.
Definition: Window.h:345
quantized, asymmetric fixed-point 8-bit number signed
size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)
Get the index of the given dimension.
Definition: Helpers.inl:327
#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(t,...)
Definition: Validate.h:746
void add_1D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx.
Definition: ICLKernel.h:110
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
void add_4D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx.
Definition: ICLKernel.h:168
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier=1, const Size2D &dilation=Size2D(1U, 1U), const ITensorInfo *output_multipliers=nullptr, const ITensorInfo *output_shifts=nullptr)
Static function to check if given info will lead to a valid configuration of CLDepthwiseConvolutionLa...
constexpr const Dimension & x() const
Alias to access the first dimension of the window.
Definition: Window.h:143