| /third_party/mindspore/mindspore/ccsrc/frontend/parallel/ops_info/ |
| D | reluv2_info.cc | 92 outputs_tensor_map_.push_back(tensor_map_index); in InferTensorMap()
96 outputs_tensor_map_.push_back(tensor_map_mask); in InferTensorMap()
106 if (outputs_tensor_map_.empty()) { in InferAsLossDivisor()
111 if (outputs_tensor_map_[0].empty()) { in InferAsLossDivisor()
117 as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(dev_matrix_shape_, outputs_tensor_map_[0]); in InferAsLossDivisor()
119 … << ", the output tensor map is " << ShapeToString(outputs_tensor_map_[0]) << ", loss divisor is " in InferAsLossDivisor()
|
| D | loss_info.cc | 90 outputs_tensor_map_.push_back(first_output_tensor_map); // output-0 in InferTensorMap()
91 outputs_tensor_map_.push_back(tensor_map_index); // output-1 in InferTensorMap()
97 if (outputs_tensor_map_.size() != 2) { in InferAsLossDivisor()
98 …MS_LOG(ERROR) << name_ << " : The size of outputs tensor map " << outputs_tensor_map_.size() << " … in InferAsLossDivisor()
101 as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(dev_matrix_shape_, outputs_tensor_map_[1]); in InferAsLossDivisor()
103 …<< ", the output tensor map is " << ShapeToString(outputs_tensor_map_[1]) << ", as_loss_divisor_ i… in InferAsLossDivisor()
|
| D | topk_info.cc | 80 outputs_tensor_map_.push_back(tensor_map); // values in InferTensorMap()
81 outputs_tensor_map_.push_back(tensor_map); // indices in InferTensorMap()
86 if (outputs_tensor_map_.empty()) { in InferAsLossDivisor()
92 if (outputs_tensor_map_[0].empty()) { in InferAsLossDivisor()
98 as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(dev_matrix_shape_, outputs_tensor_map_[0]); in InferAsLossDivisor()
101 std::string output_tensor_map_str = ShapeToString(outputs_tensor_map_[0]); in InferAsLossDivisor()
|
| D | layer_norm_info.cc | 152 outputs_tensor_map_.push_back(first_output_tensor_map); in InferTensorMap()
153 outputs_tensor_map_.push_back(second_output_tensor_map); in InferTensorMap()
154 outputs_tensor_map_.push_back(third_output_tensor_map); in InferTensorMap()
159 if (outputs_tensor_map_.size() != LAYER_NORM_INPUT_SIZE) { in InferAsLossDivisor()
160 …MS_LOG(ERROR) << name_ << ": The size of outputs tensor map " << outputs_tensor_map_.size() << " i… in InferAsLossDivisor()
163 as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(dev_matrix_shape_, outputs_tensor_map_[0]); in InferAsLossDivisor()
165 << ", the output[0]'s tensor map is " << ShapeToString(outputs_tensor_map_[0]) in InferAsLossDivisor()
|
| D | split_info.cc | 130 outputs_tensor_map_.push_back(tensor_map); in InferTensorMap()
182 if (outputs_tensor_map_.empty()) { in InferAsLossDivisor()
187 if (outputs_tensor_map_[0].empty()) { in InferAsLossDivisor()
193 as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(dev_matrix_shape_, outputs_tensor_map_[0]); in InferAsLossDivisor()
195 … << ", the output tensor map is " << ShapeToString(outputs_tensor_map_[0]) << ", loss divisor is " in InferAsLossDivisor()
|
| D | batchnorm_info.cc | 136 outputs_tensor_map_ = inputs_tensor_map_; in InferTensorMap()
239 if (outputs_tensor_map_.size() != 5) { in InferAsLossDivisor()
240 …) << name_ << ": The size of outputs tensor map must be 5, but got " << outputs_tensor_map_.size(); in InferAsLossDivisor()
243 as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(dev_matrix_shape_, outputs_tensor_map_[0]); in InferAsLossDivisor()
245 << ", the output[0]'s tensor map is " << ShapeToString(outputs_tensor_map_[0]) in InferAsLossDivisor()
|
| D | reduce_method_info.cc | 131 outputs_tensor_map_.push_back(output_tensor_map); in InferTensorMap()
366 …(output_tensor_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_[0], output_shape) != S… in InferTensorInfo()
471 MS_ASSERT(outputs_tensor_map_.size() == 1); in InferTensorMap()
472 outputs_tensor_map_.push_back(outputs_tensor_map_[0]); in InferTensorMap()
495 …(output_tensor_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_[0], output_shape) != S… in InferTensorInfo()
511 if (outputs_tensor_map_.empty()) { in InferAsLossDivisor()
517 if (outputs_tensor_map_[0].empty()) { in InferAsLossDivisor()
523 as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(dev_matrix_shape_, outputs_tensor_map_[0]); in InferAsLossDivisor()
526 std::string output_tensor_map_str = ShapeToString(outputs_tensor_map_[0]); in InferAsLossDivisor()
|
| D | gatherd_info.cc | 108 outputs_tensor_map_.push_back(input_tensor_map); // output in InferTensorMap()
113 …_.empty() || outputs_shape_.empty() || inputs_tensor_map_.empty() || outputs_tensor_map_.empty()) { in InferTensorInfo()
131 for (size_t i = 0; i < outputs_tensor_map_.size(); ++i) { in InferTensorInfo()
133 …if (output_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_[i], outputs_shape_[i]) != … in InferTensorInfo()
|
| D | activation_info.cc | 254 outputs_tensor_map_.push_back(tensor_map_index); in InferTensorMap()
291 outputs_tensor_map_.push_back(tensor_map_in); in InferTensorMap()
292 outputs_tensor_map_.push_back(tensor_map_in); // the dropout has two outputs in InferTensorMap()
297 if (outputs_tensor_map_.empty()) { in InferAsLossDivisor()
301 as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(dev_matrix_shape_, outputs_tensor_map_[0]); in InferAsLossDivisor()
303 << ", the output[0]'s tensor map is " << ShapeToString(outputs_tensor_map_[0]) in InferAsLossDivisor()
437 outputs_tensor_map_.push_back(output_tensor_map); in InferTensorMap()
569 outputs_tensor_map_.push_back(output_tensor_map); in InferTensorMap()
|
| D | gather_v2_info.cc | 157 outputs_tensor_map_.emplace_back(std::move(tensor_map_out)); in InferTensorMap()
177 if (outputs_tensor_map_.size() != GATHER_V2_OUTPUTS_SIZE) { in InferTensorInfo()
179 << outputs_tensor_map_.size(); in InferTensorInfo()
190 …(output_tensor_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_.at(0), output_shape) !… in InferTensorInfo()
|
| D | uniform_candidate_sampler_info.cc | 135 outputs_tensor_map_.push_back(sampled_tensor_map); in InferTensorMap()
137 outputs_tensor_map_.push_back(tensor_map); in InferTensorMap()
139 outputs_tensor_map_.push_back(sampled_tensor_map); in InferTensorMap()
|
| D | tensordot_info.cc | 186 Shape forward_group_map = outputs_tensor_map_[0]; in InferForwardCommunication()
229 outputs_tensor_map_.push_back(output_tensor_map); in InferTensorMapAxesInt()
274 outputs_tensor_map_.push_back(output_tensor_map); in InferTensorMapAxesTuple()
|
| D | unique_info.cc | 50 outputs_tensor_map_.push_back(out_tensor_map); in InferTensorMap()
51 outputs_tensor_map_.push_back(out_tensor_map); in InferTensorMap()
|
| D | operator_info.cc | 140 outputs_tensor_map_.clear(); in ResetQueueMember()
203 …_.empty() || outputs_shape_.empty() || inputs_tensor_map_.empty() || outputs_tensor_map_.empty()) { in InferTensorInfo()
218 for (size_t i = 0; i < outputs_tensor_map_.size(); ++i) { in InferTensorInfo()
220 …if (output_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_[i], outputs_shape_[i]) != … in InferTensorInfo()
285 for (auto &tensor_map : outputs_tensor_map_) { in ResetTensorMapIfRepeatedCalc()
1597 if (outputs_tensor_map_.empty()) { in InferAsLossDivisor()
1602 if (outputs_tensor_map_.size() > 1) { in InferAsLossDivisor()
1603 MS_LOG(ERROR) << name_ << ": The output size is " << outputs_tensor_map_.size() in InferAsLossDivisor()
1608 if (outputs_tensor_map_[0].empty()) { in InferAsLossDivisor()
1617 …as_loss_divisor_ = ComputeRepeatDeviceNumByTensorMap(out_dev_matrix_shape_, outputs_tensor_map_[0]… in InferAsLossDivisor()
[all …]
|
| D | get_next_info.cc | 51 outputs_tensor_map_.push_back(tensor_map_index); in InferTensorMap()
63 …if (output_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_[i], outputs_shape_[i]) != … in InferTensorLayout()
|
| D | tmp_identity_info.cc | 47 outputs_tensor_map_.push_back(tensor_map_index); in InferTensorMap()
|
| D | reshape_info.cc | 174 outputs_tensor_map_.push_back(tensor_map_index_output); in InferTensorMap()
221 TensorMap tensor_map_array_out = outputs_tensor_map_.at(0); in InferTensorLayout()
345 outputs_tensor_map_.push_back(output_layout_.tensor_map().array()); in Init()
|
| D | matmul_dds_info.cc | 196 outputs_tensor_map_.push_back(output_tensor_map_local_prob); in InferTensorMap()
197 outputs_tensor_map_.push_back(output_tensor_map_global_prob); in InferTensorMap()
|
| D | range_info.cc | 82 outputs_tensor_map_.push_back(output_tensor_map); in InferTensorMap()
|
| D | prelu_info.cc | 82 outputs_tensor_map_.push_back(input_tensor_map); in InferTensorMap()
|
| D | resizebilinear_info.cc | 100 (void)outputs_tensor_map_.emplace_back(std::move(output_tensor_map)); in InferTensorMap()
|
| D | bias_add_info.cc | 71 outputs_tensor_map_.push_back(sub_a_tensor_map); in InferTensorMap()
|
| D | unsorted_segment_op_info.cc | 162 outputs_tensor_map_.emplace_back(std::move(tensor_map_out)); in InferTensorMap()
214 Shape tmp_group_tensor_map = outputs_tensor_map_.at(0); in InferForwardCommunication()
|
| D | select_info.cc | 90 outputs_tensor_map_.push_back(tensor_map); in InferTensorMap()
|
| D | transpose_info.cc | 107 outputs_tensor_map_.push_back(tensor_map_index_output); in InferTensorMap()
|