Compute Library
 22.02
ClSoftmaxKernel.cpp
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26 #include "arm_compute/core/Utils.h"
29 #include "src/core/CL/CLValidate.h"
32 #include "support/Cast.h"
33 #include "support/StringSupport.h"
34 
35 namespace arm_compute
36 {
37 namespace opencl
38 {
39 namespace kernels
40 {
41 namespace
42 {
43 /** Calculates softmax parameters from the quantized input scale and scaling factor for the exponent and places them as build options.
44  *
45  * Prepares these build options:
46  * -INPUT_BETA_MULTIPLIER, INPUT_BETA_LEFT_SHIFT - quantized representation of beta multiplier.
47  * -DIFF_MIN - threshold difference between maximum value of input data and current processed value,
48  * it defines whether the value will be taken into account or not.
49  *
50  * @param[in] build_opts Build options to extend
51  * @param[in] input_scale Input scaling factor
52  * @param[in] beta Exponent scaling factor beta
53  */
54 CLBuildOptions prepare_quantized_softmax_build_options(float input_scale, float beta)
55 {
56  // Number of integer bits in temporary fixed-point representation of current-to-max difference
57  static const int scaled_diff_int_bits = 5;
58  // Number of integer bits used in temporary fixed-point representation of exponent accumulator
59  static const int exp_accumulation_in_bits = 12;
60 
61  const double beta_multiplier = std::min(
62  1.0 * beta * input_scale * (1 << (31 - scaled_diff_int_bits)),
63  (1LL << 31) - 1.0);
64  int input_beta_multiplier;
65  int input_beta_left_shift;
66  quantization::calculate_quantized_multiplier_greater_than_one(beta_multiplier, &input_beta_multiplier, &input_beta_left_shift);
67 
68  const double max_input_rescaled = 1.0 * ((1 << scaled_diff_int_bits) - 1) * (1LL << (31 - scaled_diff_int_bits)) / (1LL << input_beta_left_shift);
69  const int diff_min = -1.f * std::floor(max_input_rescaled);
70 
71  CLBuildOptions build_opts;
72  build_opts.add_option("-DSCALED_DIFF_INT_BITS=" + support::cpp11::to_string(scaled_diff_int_bits));
73  build_opts.add_option("-DEXP_ACCUMULATION_INT_BITS=" + support::cpp11::to_string(exp_accumulation_in_bits));
74  build_opts.add_option("-DINPUT_BETA_MULTIPLIER=" + support::cpp11::to_string(input_beta_multiplier));
75  build_opts.add_option("-DINPUT_BETA_LEFT_SHIFT=" + support::cpp11::to_string(input_beta_left_shift));
76  build_opts.add_option("-DDIFF_MIN=" + support::cpp11::to_string(diff_min));
77 
78  return build_opts;
79 }
80 
81 Status validate_arguments_1DMaxShiftExpSum(const ITensorInfo &src, const ITensorInfo &max, const ITensorInfo &dst, const ITensorInfo &sum)
82 {
86 
87  const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(src.data_type());
88 
89  // Checks performed when output is configured
90  if(dst.total_size() != 0)
91  {
92  if(is_quantized_asymmetric)
93  {
95  }
96  else
97  {
99  }
101  }
102 
103  // Checks performed when sum is configured
104  if(sum.total_size() != 0)
105  {
106  if(is_quantized_asymmetric)
107  {
109  }
110  else
111  {
113  }
115  }
116 
117  return Status{};
118 }
119 
120 Status validate_arguments_1DNorm(const ITensorInfo &src, const ITensorInfo &sum, const ITensorInfo &dst, const SoftmaxKernelInfo &info)
121 {
125  ARM_COMPUTE_RETURN_ERROR_ON(info.is_log && !is_data_type_float(info.input_data_type));
126 
127  // Note: output should always have a scale of 1/256 and offset 0
128  const QuantizationInfo allowed_quantization_info = get_softmax_output_quantization_info(info.input_data_type, info.is_log);
129  const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(info.input_data_type);
130 
131  // Checks performed when output is configured
132  if(dst.total_size() != 0)
133  {
135  if(!is_quantized_asymmetric)
136  {
138  }
139  else
140  {
142  ARM_COMPUTE_RETURN_ERROR_ON(dst.quantization_info() != allowed_quantization_info);
143  }
144  }
145 
146  return Status{};
147 }
148 } // namespace
149 
150 /**< Grid size (obtained through auto-tuning) */
151 const unsigned int ClLogits1DMaxShiftExpSumKernel::_grid_size = 64;
152 /**< Vector size in the serial case (obtained through auto-tuning) */
153 const unsigned int ClLogits1DMaxShiftExpSumKernel::_serial_vector_size = 8;
154 /**< Vector size in the parallel case (obtained through auto-tuning, enables the best memory access pattern for Bifrost) .*/
155 const unsigned int ClLogits1DMaxShiftExpSumKernel::_parallel_vector_size = 4;
156 
158 {
160 }
161 
163 {
164  auto padding_info = get_padding_info({ &src, &max, &dst, &sum });
165 
166  // Output auto initialization if not yet initialized
167  auto_init_if_empty(sum, src.clone()->set_tensor_shape(max.tensor_shape()));
168  auto_init_if_empty(dst, *src.clone());
169 
170  // Perform validation step
171  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DMaxShiftExpSum(src, max, dst, sum));
172 
173  const DataType dt = src.data_type();
175  const size_t reduction_dim_size = src.dimension(0);
176  const float beta = info.beta;
177  const auto is_signed_qasymm8 = is_data_type_quantized_asymmetric_signed(info.input_data_type);
178  const int min_value = is_signed_qasymm8 ? CL_SCHAR_MIN : 0;
179 
180  const unsigned int vector_size = adjust_vec_size(_serial_vector_size, reduction_dim_size);
181 
182  // Set build options
183  CLBuildOptions build_opts;
184  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(dt));
185  build_opts.add_option("-DMIN_VALUE=" + support::cpp11::to_string(min_value));
186  build_opts.add_option("-DVECTOR_SIZE=" + support::cpp11::to_string(vector_size));
187  build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(reduction_dim_size));
188  build_opts.add_option("-DVECTOR_SIZE_LEFTOVER=" + support::cpp11::to_string(reduction_dim_size % vector_size));
189  build_opts.add_option("-DLOG_VECTOR_SIZE=" + support::cpp11::to_string(lround(log2(vector_size))));
190  build_opts.add_option_if((reduction_dim_size % vector_size) != 0, "-DNON_MULTIPLE_OF_VECTOR_SIZE");
191  build_opts.add_option_if(is_signed_qasymm8, "-DQASYMM8_SIGNED");
192  build_opts.add_option_if(is_data_type_float(dt) && (beta != 1.0f), "-DBETA=" + float_to_string_with_full_precision(beta));
193  build_opts.add_option_if(is_data_type_float(dt) && info.is_log, "-DLOG_SOFTMAX");
194  build_opts.add_option_if(is_data_type_float(dt), "-DMINVAL=" + ((dt == DataType::F16) ? std::string("-HALF_MAX") : std::string("-FLT_MAX")));
197  build_opts.add_options_if(is_data_type_quantized_asymmetric(dt), prepare_quantized_softmax_build_options(qinfo.scale, beta).options());
198 
199  cl::NDRange lws_hint(cl::NullRange);
200  std::string kernel_name = std::string("softmax_layer_max_shift_exp_sum_") + (is_data_type_quantized_asymmetric(dt) ? "quantized_" : "") + "serial";
201 
202  // Create kernel.
203  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
204 
205  // Configure window
206  Window win = calculate_max_window(src, Steps(reduction_dim_size));
207  IClKernel::configure_internal(win, lws_hint);
208 
210 }
211 
213 {
214  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_1DMaxShiftExpSum(src, max, dst, sum));
215  return Status{};
216 }
217 
219 {
220  bool is_parallel_reduction = (size >= (_grid_size * _serial_vector_size)) && (_grid_size > 1);
221  unsigned int vector_size = is_parallel_reduction ? _parallel_vector_size : _serial_vector_size;
222  return std::make_tuple(is_parallel_reduction, vector_size);
223 }
224 
225 void ClLogits1DMaxShiftExpSumKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue)
226 {
229 
230  auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
231  auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
232  auto max = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_INT_0));
233  auto sum = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_INT_1));
234 
235  ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst, max, sum);
236 
237  // Collapse window in Z dimension
238  Window window_collapsed = window.collapse_if_possible(IClKernel::window(), Window::DimZ);
239 
240  // Reconfigure window in case of parallel reduction
241  ParallelReductionInfo parallel_reduction_info = is_parallel_reduction(src->info()->dimension(0));
242  if(std::get<0>(parallel_reduction_info))
243  {
244  // Launch grid_size parallel work items
245  window_collapsed.set(Window::DimX, Window::Dimension(0, _grid_size, 1));
246  }
247 
248  // Get slices
249  Window slice = window_collapsed.first_slice_window_3D();
250  do
251  {
252  unsigned int idx = 0;
253  // Set inputs
254  add_3D_tensor_argument(idx, src, slice);
255  add_3D_tensor_argument(idx, max, slice);
256  add_3D_tensor_argument(idx, dst, slice);
257  add_3D_tensor_argument(idx, sum, slice);
258  enqueue(queue, *this, slice, lws_hint());
259  }
260  while(window_collapsed.slide_window_slice_3D(slice));
261 }
262 
264 {
266 }
267 
268 void ClLogits1DNormKernel::configure(const CLCompileContext &compile_context, const ITensorInfo &src, const ITensorInfo &sum, ITensorInfo &dst, const SoftmaxKernelInfo &info)
269 {
270  auto padding_info = get_padding_info({ &src, &dst, &sum });
271 
272  // Note: output should always have a scale of 1/256 and offset 0
273  const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(info.input_data_type);
274  const DataType output_data_type = info.input_data_type;
275  const QuantizationInfo allowed_quantization_info = get_softmax_output_quantization_info(info.input_data_type, info.is_log);
277 
278  // Output auto initialization if not yet initialized
279  auto_init_if_empty(dst, src.clone()->set_data_type(output_data_type).set_quantization_info(allowed_quantization_info));
280 
281  // Perform validation step
282  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DNorm(src, sum, dst, info));
283 
284  const auto is_signed_qasymm8 = is_data_type_quantized_asymmetric_signed(info.input_data_type);
285  const int min_value = is_signed_qasymm8 ? CL_SCHAR_MIN : 0;
286  const unsigned int vector_size = adjust_vec_size(16, src.dimension(0));
287 
288  // Set build options
289  CLBuildOptions build_opts;
290  build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(info.input_data_type));
291  build_opts.add_option("-DMIN_VALUE=" + support::cpp11::to_string(min_value));
292  build_opts.add_option("-DVECTOR_SIZE=" + support::cpp11::to_string(vector_size));
293  build_opts.add_option("-DVECTOR_SIZE_LEFTOVER=" + support::cpp11::to_string(src.dimension(0) % vector_size));
294  build_opts.add_option_if(is_data_type_quantized_asymmetric_signed(info.input_data_type), "-DQASYMM8_SIGNED");
295  build_opts.add_options_if(is_quantized_asymmetric,
296  prepare_quantized_softmax_build_options(qinfo.scale, info.beta).options());
297  build_opts.add_option_if(info.is_log, "-DLOG_SOFTMAX");
298  build_opts.add_option_if(is_quantized_asymmetric, "-DSCALE=" + float_to_string_with_full_precision(qinfo.scale));
299  build_opts.add_option_if(is_quantized_asymmetric, "-DBETA=" + float_to_string_with_full_precision(info.beta));
300 
301  // Create kernel
302  std::string kernel_name = std::string("softmax_layer_norm") + (is_quantized_asymmetric ? "_quantized" : "");
303  _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
304 
305  // Configure window
306  auto win = calculate_max_window(src, Steps(vector_size));
307  ICLKernel::configure_internal(win);
308 
310 }
311 
313 {
314  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_1DNorm(src, sum, dst, info));
315 
316  return Status{};
317 }
318 
319 void ClLogits1DNormKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue)
320 {
323 
324  auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
325  auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
326  auto sum = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_INT_0));
327 
328  ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst, sum);
329 
330  Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
331  Window slice = window_collapsed.first_slice_window_3D();
332 
333  do
334  {
335  Window sum_slice = slice;
336  sum_slice.set(Window::DimX, Window::Dimension(0, 1, 1));
337 
338  unsigned int idx = 0;
339  // Set inputs
340  add_3D_tensor_argument(idx, src, slice);
341  add_3D_tensor_argument(idx, sum, sum_slice);
342  add_3D_tensor_argument(idx, dst, slice);
343  enqueue(queue, *this, slice, lws_hint());
344  }
345  while(window_collapsed.slide_window_slice_3D(slice));
346 }
347 } // namespace kernels
348 } // namespace opencl
349 } // namespace arm_compute
void configure(const CLCompileContext &compile_context, const ITensorInfo &src, ITensorInfo &max, ITensorInfo &dst, ITensorInfo &sum, const SoftmaxKernelInfo &info)
Configure the kernel using the given information about tensors.
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
#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
void run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue) override
static Status validate(const ITensorInfo &src, const ITensorInfo &sum, const ITensorInfo &dst, const SoftmaxKernelInfo &info)
Static function to check if given info will lead to a valid configuration.
void run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue) override
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.
float beta
A scaling factor for the exponent with default value 1.0.
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:353
#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.
1 channel, 1 F32 per channel
static ParallelReductionInfo is_parallel_reduction(size_t size)
Checks if the given size is eligible for parallel reduction.
#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
QuantizationInfo get_softmax_output_quantization_info(DataType input_type, bool is_log)
Returns output quantization information for softmax layer.
Definition: Utils.cpp:486
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
Quantization info when assuming per layer quantization.
Describe one of the image&#39;s dimensions with a start, end and step.
Definition: Window.h:77
Status class.
Definition: Error.h:52
Status calculate_quantized_multiplier_greater_than_one(float multiplier, int32_t *quantized_multiplier, int32_t *left_shift)
Calculate quantized representation of multiplier having value greater than one.
std::tuple< bool, unsigned int > ParallelReductionInfo
Info for whether a parallel reduction will be run and the vector size of the execution.
#define ARM_COMPUTE_RETURN_ERROR_ON(cond)
If the condition is true, an error is returned.
Definition: Error.h:296
void add_3D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 3D tensor&#39;s parameters to the object&#39;s kernel&#39;s arguments starting from the index idx...
Definition: ICLKernel.h:214
SimpleTensor< float > src
Definition: DFT.cpp:155
Copyright (c) 2017-2021 Arm Limited.
1 channel, 1 F16 per channel
static Status validate(const ITensorInfo &src, const ITensorInfo &max, const ITensorInfo &dst, const ITensorInfo &sum)
Static function to check if given info will lead to a valid configuration.
1 channel, 1 S32 per channel
void add_option(std::string option)
Adds option to the existing build option list.
const ITensor * get_const_tensor(int id) const
Get constant tensor of a given id.
Definition: ITensorPack.cpp:54
Quantization information.
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:391
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
Window collapse_if_possible(const Window &full_window, size_t first, size_t last, bool *has_collapsed=nullptr) const
Collapse the dimensions between first and last if possible.
Definition: Window.inl:68
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1090
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
quantized, asymmetric fixed-point 8-bit number unsigned
Class to describe a number of elements in each dimension.
Definition: Steps.h:40
DataType input_data_type
Input tensor data type.
UniformQuantizationInfo uniform() const
Return per layer quantization info.
bool is_log
Flag used to perform Log Softmax operation.
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp:39
bool is_data_type_quantized_asymmetric_signed(DataType dt)
Check if a given data type is of asymmetric quantized signed type.
Definition: Utils.h:1037
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.
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
Elementeise CL kernel type.
Definition: CLTypes.h:84
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:335
virtual QuantizationInfo quantization_info() const =0
Get the quantization settings (scale and offset) of the tensor.
#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:552
CLCompileContext class.
bool is_data_type_quantized_asymmetric(DataType dt)
Check if a given data type is of asymmetric quantized type.
Definition: Utils.h:1018
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
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)
Definition: Validate.h:439
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
const QuantizationInfo qinfo
Definition: Im2Col.cpp:155
#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
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:537
Tensor packing service.
Definition: ITensorPack.h:39
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
long lround(T value)
Round floating-point value with half value rounding away from zero and cast to long.
unsigned int adjust_vec_size(unsigned int vec_size, size_t dim0)
Returns the adjusted vector size in case it is less than the input&#39;s first dimension, getting rounded down to its closest valid vector size.
Definition: Utils.h:1186
void configure(const CLCompileContext &compile_context, const ITensorInfo &src, const ITensorInfo &sum, ITensorInfo &dst, const SoftmaxKernelInfo &info)
Set the input and output tensors.
quantized, asymmetric fixed-point 8-bit number signed
Descriptor used by the softmax kernels.
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:291
std::string kernel_name
DataType
Available data types.
Definition: Types.h:79
Describe a multidimensional execution window.
Definition: Window.h:39
bool is_data_type_float(DataType dt)
Check if a given data type is of floating point type.
Definition: Utils.h:976
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:201
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)
void add_options_if(bool cond, const StringSet &options)
Appends given build options to the current&#39;s objects options if a given condition is true...