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Searched refs:param_ (Results 1 – 25 of 151) sorted by relevance

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/third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/mkldnn/
Dmatmul_cpu_kernel.cc50 const size_t size = param_.batch * param_.row_align_ * param_.deep_; in InitMatrixA()
65 for (int i = 0; i < param_.batch; i++) { in InitMatrixA()
66 const float *src = src_ptr + i * param_.row_ * param_.deep_; in InitMatrixA()
67 float *dst = a_pack_ptr_ + i * param_.row_align_ * param_.deep_; in InitMatrixA()
69 if (param_.a_transpose_) { in InitMatrixA()
70 RowMajor2Row6Major(src, dst, param_.deep_, param_.row_); in InitMatrixA()
72 RowMajor2Col6Major(src, dst, param_.row_, param_.deep_); in InitMatrixA()
75 if (param_.a_transpose_) { in InitMatrixA()
76 RowMajor2Row4Major(src, dst, param_.deep_, param_.row_); in InitMatrixA()
78 RowMajor2Col4Major(src, dst, param_.row_, param_.deep_); in InitMatrixA()
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/third_party/mindspore/mindspore/lite/micro/coder/opcoders/nnacl/int8/
Dtranspose_int8_coder.cc31 param_ = reinterpret_cast<TransposeParameter *>(parameter_); in Prepare()
32 param_->data_num_ = in_tensor->ElementsNum(); in Prepare()
37 param_->num_axes_ = perm_tensor->ElementsNum(); in Prepare()
38 for (int i = 0; i < param_->num_axes_; ++i) { in Prepare()
39 param_->perm_[i] = perm_data[i]; in Prepare()
41 param_->strides_[param_->num_axes_ - 1] = 1; in Prepare()
42 param_->out_strides_[param_->num_axes_ - 1] = 1; in Prepare()
43 for (int i = param_->num_axes_ - 2; i >= 0; i--) { in Prepare()
44 param_->strides_[i] = in_shape.at(i + 1) * param_->strides_[i + 1]; in Prepare()
45 param_->out_strides_[i] = out_shape.at(i + 1) * param_->out_strides_[i + 1]; in Prepare()
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Dsub_int8_coder.cc37 param_.in0_args_.scale_ = input0->quant_params().front().scale; in Prepare()
38 param_.in0_args_.zp_ = -input0->quant_params().front().zeroPoint; in Prepare()
39 param_.in1_args_.scale_ = input1->quant_params().front().scale; in Prepare()
40 param_.in1_args_.zp_ = -input1->quant_params().front().zeroPoint; in Prepare()
41 param_.out_args_.scale_ = output_tensor_->quant_params().front().scale; in Prepare()
42 param_.out_args_.zp_ = output_tensor_->quant_params().front().zeroPoint; in Prepare()
45 …const double twice_max_input_scale = 2 * std::max(param_.in0_args_.scale_, param_.in1_args_.scale_… in Prepare()
46 const double real_input0_multiplier = param_.in0_args_.scale_ / twice_max_input_scale; in Prepare()
47 const double real_input1_multiplier = param_.in1_args_.scale_ / twice_max_input_scale; in Prepare()
48 …const double real_output_multiplier = twice_max_input_scale / ((1 << left_shift) * param_.out_args… in Prepare()
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Dmatmul_base_int8_coder.cc34 a_pack_ptr_size_ = param_->row_align_ * param_->deep_16_ * sizeof(int8_t); in InitTmpBuffer()
37 b_pack_ptr_size_ = param_->batch * param_->col_align_ * param_->deep_16_ * sizeof(int8_t); in InitTmpBuffer()
38 if (param_->b_const_) { in InitTmpBuffer()
44 input_sums_size_ = static_cast<size_t>(param_->row_align_ * sizeof(int)); in InitTmpBuffer()
47 weight_bias_sums_size_ = static_cast<size_t>(param_->batch * param_->col_align_ * sizeof(int)); in InitTmpBuffer()
48 if (param_->b_const_) { in InitTmpBuffer()
61 param_->row_align_ = UP_ROUND(param_->row_, row_tile_); in ResizeParameter()
62 param_->col_align_ = UP_ROUND(param_->col_, col_tile_); in ResizeParameter()
63 param_->deep_16_ = UP_ROUND(param_->deep_, C16NUM); in ResizeParameter()
65 thread_count_ = MSMIN(kDefaultThreadNum, UP_DIV(param_->col_align_, col_tile_)); in ResizeParameter()
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Ddiv_int8_coder.cc35 param_.in0_args_.scale_ = input0->quant_params().front().scale; in Prepare()
36 param_.in0_args_.zp_ = -input0->quant_params().front().zeroPoint; in Prepare()
37 param_.in1_args_.scale_ = input1->quant_params().front().scale; in Prepare()
38 param_.in1_args_.zp_ = -input1->quant_params().front().zeroPoint; in Prepare()
39 param_.out_args_.scale_ = output_tensor_->quant_params().front().scale; in Prepare()
40 param_.out_args_.zp_ = output_tensor_->quant_params().front().zeroPoint; in Prepare()
42 …const double real_multiplier = param_.in0_args_.scale_ / (param_.in1_args_.scale_ * param_.out_arg… in Prepare()
44 QuantizeMultiplier(real_multiplier, &param_.output_multiplier_, &param_.output_shift_); in Prepare()
46 param_.output_activation_min_ = std::numeric_limits<int8_t>::min(); in Prepare()
47 param_.output_activation_max_ = std::numeric_limits<int8_t>::max(); in Prepare()
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/int8/
Dmatmul_base_int8.cc38 int res_stride = param_->col_ - cur_stride; in RunImpl()
50 …ulInt8Opt(pack_a_ptr_, batch_b_ptr_ + cur_stride * param_->deep_16_, batch_c_ptr_ + cur_stride, pa… in RunImpl()
51 … cur_oc, param_->deep_16_, input_sums_, weight_bias_sums_ + cur_stride, quant_param_->out_act_min_, in RunImpl()
52 … quant_param_->out_act_max_, quant_param_->output_.zp_, cur_mul, cur_left, cur_right, param_->col_, in RunImpl()
159 …CalculateActivationRangeQuantized(param_->act_type_ == ActType_Relu, param_->act_type_ == ActType_… in InitQuantParam()
165 param_->a_const_ = (in_tensors_[0]->data() != nullptr); in InitParameter()
166 param_->b_const_ = (in_tensors_[1]->data() != nullptr); in InitParameter()
178 param_->row_align_ = UP_ROUND(param_->row_, row_tile_); in ResizeParameter()
179 param_->col_align_ = UP_ROUND(param_->col_, col_tile_); in ResizeParameter()
180 param_->deep_16_ = UP_ROUND(param_->deep_, C16NUM); in ResizeParameter()
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Dlayer_norm_int8.cc99 CHECK_NULL_RETURN(param_); in Init()
110 param_->begin_norm_axis_ = in ReSize()
111 … param_->begin_norm_axis_ > 0 ? param_->begin_norm_axis_ : param_->begin_norm_axis_ + shape.size(); in ReSize()
112 param_->begin_params_axis_ = in ReSize()
113 …param_->begin_params_axis_ > 0 ? param_->begin_params_axis_ : param_->begin_params_axis_ + shape.s… in ReSize()
115 param_->norm_outer_size_ = 1; in ReSize()
116 for (int i = 0; i < param_->begin_norm_axis_; ++i) { in ReSize()
117 param_->norm_outer_size_ *= shape.at(i); in ReSize()
119 param_->norm_inner_size_ = 1; in ReSize()
120 for (size_t i = param_->begin_norm_axis_; i < shape.size(); ++i) { in ReSize()
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/fp32/
Darithmetic_fp32.cc30 auto primitive_type = param_->op_parameter_.type_; in Init()
32 switch (param_->eltwise_mode_) { in Init()
43 MS_LOG(ERROR) << "Eltwise mode not support, mode:" << param_->eltwise_mode_; in Init()
55 CalcMultiplesAndStrides(param_); in ReSize()
56 if (param_->broadcasting_) { in ReSize()
58 …for (int i = static_cast<int>(param_->ndim_) - 1; i >= 0 && i < ARITHMETIC_SUPPORT_DIMS_NUM; --i) { in ReSize()
59 if (param_->in_shape0_[i] != param_->in_shape1_[i]) { in ReSize()
63 outside_ *= param_->out_shape_[i]; in ReSize()
89 …if ((param_->in_elements_num0_ == 1 || param_->in_elements_num1_ == 1) && (arithmetic_opt_run_ != … in IsScalarClac()
101 for (size_t i = 0; i < param_->ndim_; i++) { in IsBatchScalarCalc()
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Dlayer_norm_fp32.cc32 CHECK_NULL_RETURN(param_); in Init()
43 param_->begin_norm_axis_ = in ReSize()
44 … param_->begin_norm_axis_ > 0 ? param_->begin_norm_axis_ : param_->begin_norm_axis_ + shape.size(); in ReSize()
45 param_->begin_params_axis_ = in ReSize()
46 …param_->begin_params_axis_ > 0 ? param_->begin_params_axis_ : param_->begin_params_axis_ + shape.s… in ReSize()
48 param_->norm_outer_size_ = 1; in ReSize()
49 for (int i = 0; i < param_->begin_norm_axis_; ++i) { in ReSize()
50 param_->norm_outer_size_ *= shape.at(i); in ReSize()
52 param_->norm_inner_size_ = 1; in ReSize()
53 for (size_t i = param_->begin_norm_axis_; i < shape.size(); ++i) { in ReSize()
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Dtranspose_fp32.cc40 param_->num_axes_ = in_tensors_.at(1)->ElementsNum(); in ReSize()
45 if (input_tensor->shape().size() != static_cast<size_t>(param_->num_axes_)) { in ReSize()
46 if (input_tensor->shape().size() == 3 && param_->num_axes_ == 4) { in ReSize()
47 param_->num_axes_ = 3; in ReSize()
58 if (param_->num_axes_ > MAX_TRANSPOSE_DIM_SIZE || param_->num_axes_ < 0) { in ReSize()
59 MS_LOG(ERROR) << "num_axes_ " << param_->num_axes_ << "is invalid."; in ReSize()
62 for (int i = 0; i < param_->num_axes_; ++i) { in ReSize()
63 param_->perm_[i] = perm_data[i]; in ReSize()
69 param_->strides_[param_->num_axes_ - 1] = 1; in ReSize()
70 param_->out_strides_[param_->num_axes_ - 1] = 1; in ReSize()
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Drelative_position_attention_fp32.cc166 param_->use_bias_ = true; in CheckBiases()
168 if (!param_->use_bias_) { in CheckBiases()
221 param_->row_tile_ = C6NUM; in PrepareParam()
222 param_->col_tile_ = C16NUM; in PrepareParam()
223 param_->bias_tile_ = C16NUM; in PrepareParam()
225 param_->row_tile_ = C12NUM; in PrepareParam()
226 param_->col_tile_ = C4NUM; in PrepareParam()
227 param_->bias_tile_ = C4NUM; in PrepareParam()
229 param_->row_tile_ = C4NUM; in PrepareParam()
230 param_->col_tile_ = C8NUM; in PrepareParam()
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Droi_pooling_fp32.cc59 param_->ndim_ = ndims; in ReSize()
60 param_->input_n_ = in_shape.at(0); in ReSize()
61 param_->input_h_ = in_shape.at(1); in ReSize()
62 param_->input_w_ = in_shape.at(2); in ReSize()
63 param_->input_c_ = in_shape.at(3); in ReSize()
64 param_->output_n_ = out_shape.at(0); in ReSize()
65 param_->output_h_ = out_shape.at(1); in ReSize()
66 param_->output_w_ = out_shape.at(2); in ReSize()
67 param_->output_c_ = out_shape.at(3); in ReSize()
68 param_->in_strides_[ndims - 1] = 1; in ReSize()
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Dspace_to_batch_fp32.cc32 param_->input_shape_[i] = input_tensor->shape().at(i); in ProcessInput()
33 param_->output_shape_[i] = output_tensor->shape().at(i); in ProcessInput()
35 ComputeStrides(param_->input_shape_, param_->in_stride_, DIMENSION_4D); in ProcessInput()
36 ComputeStrides(param_->output_shape_, param_->out_stride_, DIMENSION_4D); in ProcessInput()
41 param_->block_sizes_[i] = block_shape[i]; in ProcessInput()
47 param_->paddings_[i] = padding[i]; in ProcessInput()
76 param_->input_shape_[i] = input_tensor->shape().at(i); in ReSize()
77 param_->output_shape_[i] = output_tensor->shape().at(i); in ReSize()
80 ComputeStrides(param_->input_shape_, param_->in_stride_, DIMENSION_4D); in ReSize()
81 ComputeStrides(param_->output_shape_, param_->out_stride_, DIMENSION_4D); in ReSize()
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Dexp_fp32.cc30 float log_base = (param_->base_ == -1) ? 1 : logf(param_->base_); in Init()
31 param_->in_scale_ = param_->scale_ * log_base; in Init()
32 if (param_->shift_ == 0) { in Init()
33 param_->out_scale_ = 1; in Init()
36 param_->out_scale_ = expf(param_->shift_); in Init()
38 param_->out_scale_ = powf(param_->base_, param_->shift_); in Init()
41 param_->op_parameter_.thread_num_ = ms_context_->thread_num_; in Init()
49 param_->element_num_ = in_tensors_.front()->ElementsNum(); in ReSize()
55 …(reinterpret_cast<float *>(input_addr_), reinterpret_cast<float *>(output_addr_), param_, task_id); in DoExcute()
Dembedding_lookup_fp32.cc30 CHECK_NULL_RETURN(param_); in Init()
38 param_->ids_size_ = in_tensors_.back()->ElementsNum(); in ReSize()
39 param_->layer_size_ = 1; in ReSize()
42 param_->layer_size_ *= in_shape[i]; in ReSize()
45 param_->layer_num_ = 0; in ReSize()
48 param_->layer_num_ += in_tensors_[i]->shape()[0]; in ReSize()
58 int error_code = EmbeddingLookup(input_addr_, ids_addr, output_addr, param_, task_id); in DoExcute()
79 …_cast<float *>(ms_context_->allocator->Malloc(sizeof(float) * param_->layer_size_ * param_->layer_… in Run()
80 …param_->is_regulated_ = reinterpret_cast<bool *>(ms_context_->allocator->Malloc(sizeof(bool) * par… in Run()
81 if (input_addr_ == nullptr || param_->is_regulated_ == nullptr) { in Run()
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/fp32_grad/
Dstrided_slice_grad.cc37 param_ = reinterpret_cast<StridedSliceParameter *>(op_parameter_); in Init()
38 CHECK_NULL_RETURN(param_); in Init()
47 param_->data_type = kDataTypeFloat; in Init()
64 for (i = 0; i < param_->num_axes_; ++i) { in FillEmptyDims()
65 begins[i] = param_->begins_[i]; in FillEmptyDims()
66 ends[i] = MSMIN(param_->ends_[i], param_->in_shape_[i]); in FillEmptyDims()
67 strides[i] = param_->strides_[i]; in FillEmptyDims()
68 input_shape[i] = param_->in_shape_[i]; in FillEmptyDims()
70 for (i = param_->num_axes_; i < param_->in_shape_length_; ++i) { in FillEmptyDims()
71 input_shape[i] = param_->in_shape_[i]; in FillEmptyDims()
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Dsoftmax_cross_entropy_with_logits.cc36 for (int i = 0; i < param_->batch_size_; ++i) { in ForwardPostExecute()
38 for (size_t j = 0; j < param_->number_of_classes_; ++j) { in ForwardPostExecute()
40 …-logf(logits[i * param_->number_of_classes_ + j] <= 0.0 ? eps : logits[i * param_->number_of_class… in ForwardPostExecute()
41 grads[i * param_->number_of_classes_ + j] = in ForwardPostExecute()
42 (logits[i * param_->number_of_classes_ + j] - labels[i * param_->number_of_classes_ + j]); in ForwardPostExecute()
43 loss += labels[i * param_->number_of_classes_ + j] * logit; in ForwardPostExecute()
48 for (int i = 0; i < param_->batch_size_; ++i) { in ForwardPostExecute()
50 for (size_t j = 0; j < param_->number_of_classes_; ++j) { in ForwardPostExecute()
52 …-logf(logits[i * param_->number_of_classes_ + j] <= 0.0 ? eps : logits[i * param_->number_of_class… in ForwardPostExecute()
53 loss += labels[i * param_->number_of_classes_ + j] * logit; in ForwardPostExecute()
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/fp16_grad/
Dstrided_slice_fp16_grad.cc39 param_ = reinterpret_cast<StridedSliceParameter *>(op_parameter_); in Init()
40 CHECK_NULL_RETURN(param_); in Init()
46 param_->data_type = kDataTypeFloat16; in Init()
63 for (i = 0; i < param_->num_axes_; ++i) { in FillEmptyDims()
64 begins[i] = param_->begins_[i]; in FillEmptyDims()
65 ends[i] = MSMIN(param_->ends_[i], param_->in_shape_[i]); in FillEmptyDims()
66 strides[i] = param_->strides_[i]; in FillEmptyDims()
67 input_shape[i] = param_->in_shape_[i]; in FillEmptyDims()
69 for (i = param_->num_axes_; i < param_->in_shape_length_; ++i) { in FillEmptyDims()
70 input_shape[i] = param_->in_shape_[i]; in FillEmptyDims()
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/fp16/
Darithmetic_compare_fp16.cc78 param_->in_elements_num0_ = in_tensors_.at(0)->ElementsNum(); in ReSize()
79 param_->in_elements_num1_ = in_tensors_.at(1)->ElementsNum(); in ReSize()
80 param_->out_elements_num_ = out_tensors_.at(0)->ElementsNum(); in ReSize()
82 if (param_->in_elements_num0_ == 1 || param_->in_elements_num1_ == 1) { in ReSize()
83 param_->broadcasting_ = false; in ReSize()
84 …arithmetic_opt_func_ = GetOptimizedArithmeticCompareFun(param_->op_parameter_.type_, param_->activ… in ReSize()
86 … arithmetic_func_ = GetArithmeticCompareFun(param_->op_parameter_.type_, param_->activation_type_); in ReSize()
92 if (param_->broadcasting_) { in ReSize()
94 for (int i = param_->ndim_ - 1; i >= 0; --i) { in ReSize()
95 if (param_->in_shape0_[i] != param_->in_shape1_[i]) { in ReSize()
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Dlayer_norm_fp16.cc33 CHECK_NULL_RETURN(param_); in Init()
44 param_->begin_norm_axis_ = in ReSize()
45 … param_->begin_norm_axis_ > 0 ? param_->begin_norm_axis_ : param_->begin_norm_axis_ + shape.size(); in ReSize()
46 param_->begin_params_axis_ = in ReSize()
47 …param_->begin_params_axis_ > 0 ? param_->begin_params_axis_ : param_->begin_params_axis_ + shape.s… in ReSize()
49 param_->norm_outer_size_ = 1; in ReSize()
50 for (int i = 0; i < param_->begin_norm_axis_; ++i) { in ReSize()
51 param_->norm_outer_size_ *= shape.at(i); in ReSize()
53 param_->norm_inner_size_ = 1; in ReSize()
54 for (size_t i = param_->begin_norm_axis_; i < shape.size(); ++i) { in ReSize()
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/third_party/mindspore/mindspore/lite/micro/coder/opcoders/nnacl/fp32/
Dtranspose_fp32_coder.cc27 param_->num_axes_ = input_tensors_.at(1)->ElementsNum(); in Resize()
29 if (input_tensors_.at(kInputIndex)->shape().size() != static_cast<size_t>(param_->num_axes_)) { in Resize()
37 for (int i = 0; i < param_->num_axes_; ++i) { in Resize()
38 param_->perm_[i] = perm_data[i]; in Resize()
42 param_->strides_[param_->num_axes_ - 1] = 1; in Resize()
43 param_->out_strides_[param_->num_axes_ - 1] = 1; in Resize()
44 param_->data_num_ = input_tensor_->ElementsNum(); in Resize()
45 for (int i = param_->num_axes_ - 2; i >= 0; i--) { in Resize()
46 param_->strides_[i] = in_shape.at(i + 1) * param_->strides_[i + 1]; in Resize()
47 param_->out_strides_[i] = out_shape.at(i + 1) * param_->out_strides_[i + 1]; in Resize()
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/base/
Dsplit_with_over_lap_base.cc34 CHECK_LESS_RETURN(SPLIT_MAX_SLICE_NUM, param_->num_split_ + 1); in CalculateSplitedShapes()
35 for (auto i = 0; i < param_->num_split_; i++) { in CalculateSplitedShapes()
36 total_block_count += param_->ratio_[i]; in CalculateSplitedShapes()
38 CHECK_LESS_RETURN(static_cast<int>(shape.size()), param_->split_dim_ + 1); in CalculateSplitedShapes()
39 auto split_dim_size = shape[param_->split_dim_]; in CalculateSplitedShapes()
44 for (auto i = 0; i < param_->num_split_ - 1; i++) { in CalculateSplitedShapes()
45 visited_block += param_->ratio_[i]; in CalculateSplitedShapes()
52 for (auto i = 0; i < param_->num_split_; i++) { in CalculateSplitedShapes()
57 start_indices_[i] -= param_->extend_top_[i]; in CalculateSplitedShapes()
58 end_indices_[i] += param_->extend_bottom_[i]; in CalculateSplitedShapes()
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Dslice_base.cc55 param_->param_length_ = in_tensor->shape().size(); in ReSize()
56 if (param_->param_length_ > DIMENSION_8D) { in ReSize()
60 for (int i = 0; i < param_->param_length_; ++i) { in ReSize()
61 param_->shape_[i] = in_tensor->DimensionSize(i); in ReSize()
62 param_->begin_[i] = begin[i]; in ReSize()
63 param_->size_[i] = size[i] < 0 ? param_->shape_[i] - param_->begin_[i] : size[i]; in ReSize()
64 param_->end_[i] = param_->begin_[i] + param_->size_[i]; in ReSize()
66 if (param_->param_length_ < DIMENSION_8D) { in ReSize()
67 PadSliceParameterTo8D(param_); in ReSize()
87 DoSlice(in_tensors_.at(0)->data(), out_tensors_.at(0)->data(), param_, thread_id, in SliceParallelRun()
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/string/
Dlsh_projection.cc63 param_->hash_buff_size_ = sizeof(float) + sizeof(int32_t); in Run()
64 param_->feature_num_ = input1_tensor->ElementsNum(); in Run()
65 param_->hash_shape_[0] = input0_tensor->DimensionSize(0); in Run()
66 param_->hash_shape_[1] = input0_tensor->DimensionSize(1); in Run()
67 …param_->thread_stride_ = op_parameter_->thread_num_ > 1 ? UP_DIV(param_->hash_shape_[0], op_parame… in Run()
68 : param_->hash_shape_[0]; in Run()
82 param_->hash_buffs_ = in MallocKeys()
84 if (param_->hash_buffs_ == nullptr) { in MallocKeys()
89 …param_->hash_buffs_[i] = static_cast<char *>(ms_context_->allocator->Malloc(param_->hash_buff_size… in MallocKeys()
90 if (param_->hash_buffs_[i] == nullptr) { in MallocKeys()
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/third_party/openh264/test/api/
Dencode_options_test.cpp45 param_.iPicWidth = WelsClip3 ((((rand() % MAX_WIDTH) >> 1) + 1) << 1, 2, MAX_WIDTH); in RandomParamExtCombination()
46 param_.iPicHeight = WelsClip3 ((((rand() % MAX_HEIGHT) >> 1) + 1) << 1, 2, MAX_HEIGHT); in RandomParamExtCombination()
48 param_.fMaxFrameRate = rand() % FRAME_RATE_RANGE + 0.5f; in RandomParamExtCombination()
49 param_.iUsageType = static_cast<EUsageType> (rand() % 2); in RandomParamExtCombination()
50 param_.iTemporalLayerNum = rand() % TEMPORAL_LAYER_NUM_RANGE; in RandomParamExtCombination()
51 param_.iSpatialLayerNum = rand() % SPATIAL_LAYER_NUM_RANGE; in RandomParamExtCombination()
53 param_.uiIntraPeriod = rand() - 1; in RandomParamExtCombination()
54 param_.iNumRefFrame = AUTO_REF_PIC_COUNT; in RandomParamExtCombination()
55 param_.iMultipleThreadIdc = rand(); in RandomParamExtCombination()
60 param_.eSpsPpsIdStrategy = CONSTANT_ID; in RandomParamExtCombination()
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