| /third_party/mindspore/mindspore/ccsrc/frontend/parallel/ops_info/ |
| D | gather_v2_info.cc | 38 if (outputs_shape_.size() != GATHER_V2_OUTPUTS_SIZE) { in GetAttrs()
39 MS_LOG(ERROR) << name_ << ": outputs shape size must be 1, but is " << outputs_shape_.size(); in GetAttrs()
79 if (outputs_shape_.size() != GATHER_V2_OUTPUTS_SIZE) { in CheckStrategy()
81 << outputs_shape_.size(); in CheckStrategy()
123 if (outputs_shape_.size() != GATHER_V2_OUTPUTS_SIZE) { in InferTensorMap()
125 << outputs_shape_.size(); in InferTensorMap()
142 if (tensor_map_out.size() != outputs_shape_.at(0).size()) { in InferTensorMap()
144 << " output size is " << outputs_shape_.at(0).size(); in InferTensorMap()
167 if (outputs_shape_.size() != GATHER_V2_OUTPUTS_SIZE) { in InferTensorInfo()
169 << outputs_shape_.size(); in InferTensorInfo()
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| D | reshape_info.cc | 97 if (elements.size() != outputs_shape_[0].size()) { in GetParameterInput()
158 if ((inputs_shape_.size() != 1) || (outputs_shape_.size() != 1)) { in InferTensorMap()
160 << inputs_shape_.size() << " and " << outputs_shape_.size(); in InferTensorMap()
171 for (size_t j = 0; j < outputs_shape_[0].size(); ++j) { in InferTensorMap()
185 for (size_t j = 0; j < outputs_shape_[0].size(); ++j) { in GetOutputsStrategy()
219 Shape shape_array_out = outputs_shape_.at(0); in InferTensorLayout()
270 Shape shape_array_out = outputs_shape_.at(0); in InferTensorInfo()
338 Status status = InferDefaultLayout(outputs_shape_.at(0), &output_layout_); in Init()
422 if ((inputs_shape_.size() != 1) || (outputs_shape_.size() != 1)) { in GenerateStrategies()
424 << outputs_shape_.size(); in GenerateStrategies()
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| D | get_next_info.cc | 61 for (size_t i = 0; i < outputs_shape_.size(); ++i) { in InferTensorLayout()
63 …if (output_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_[i], outputs_shape_[i]) != … in InferTensorLayout()
76 for (size_t i = 0; i < outputs_shape_.size(); ++i) { in InferTensorInfo()
127 for (size_t i = 0; i < outputs_shape_.size(); i++) { in CheckStrategy()
129 for (size_t j = 0; j < outputs_shape_[i].size(); j++) { in CheckStrategy()
172 shapes_ = outputs_shape_; in GetAttrShapes()
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| D | dsd_matmul_info.cc | 137 for (size_t i = 0; i < outputs_shape_[0].size(); ++i) { in InferTensorMap()
139 output_tensor_map.push_back((int64_t)(outputs_shape_[0].size() - i)); in InferTensorMap()
152 …if ((inputs_shape_.size() != DSD_MATMUL_INPUTS_SIZE) || (outputs_shape_.size() != DSD_MATMUL_OUTPU… in GetAttrs()
154 << outputs_shape_.size() << " is wrong."; in GetAttrs()
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| D | onehot_info.cc | 53 …if (CheckStrategyValue(strategy, {outputs_shape_.at(0), inputs_shape_.at(1), inputs_shape_.at(2)})… in CheckStrategy()
97 size_t size = outputs_shape_[0].size(); in InferTensorMap()
239 if (outputs_shape_.size() != 1) { in GenerateOpStrategies()
240 … MS_LOG(EXCEPTION) << name_ << ": outputs_shape_ size must be 1, but is " << outputs_shape_.size(); in GenerateOpStrategies()
242 …if (GenerateStrategiesForIndependentInputs(stage_id, {outputs_shape_.at(0), inputs_shape_.at(1), i… in GenerateOpStrategies()
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| D | unsorted_segment_op_info.cc | 38 if (outputs_shape_.size() != UNSORTEDSEGMENTOP_OUTPUTS_SIZE) { in GetAttrs()
39 MS_LOG(ERROR) << name_ << ": outputs shape size must be 1, but is " << outputs_shape_.size(); in GetAttrs()
67 if (outputs_shape_.size() != UNSORTEDSEGMENTOP_OUTPUTS_SIZE) { in CheckStrategy()
69 << outputs_shape_.size(); in CheckStrategy()
154 if (tensor_map_out.size() != outputs_shape_.at(0).size()) { in InferTensorMap()
156 << " output size is " << outputs_shape_.at(0).size(); in InferTensorMap()
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| D | gathernd_info.cc | 89 if (outputs_shape_.empty() || outputs_shape_[0].size() < (inputs_shape_[1].size() - 1)) { in InferTensorMap()
103 TensorMap output_tensor_map(outputs_shape_[0].size(), MAP_NONE); in InferTensorMap()
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| D | activation_info.cc | 43 …if ((inputs_shape_.size() != ACTIVATION_INPUTS_SIZE) || (outputs_shape_.size() != ACTIVATION_OUTPU… in GetAttrs()
45 << outputs_shape_.size() << "is wrong."; in GetAttrs()
68 …if ((inputs_shape_.size() != ACTIVATION_INPUTS_SIZE) || (outputs_shape_.size() != ACTIVATION_OUTPU… in GetAttrs()
70 << outputs_shape_.size() << "is wrong."; in GetAttrs()
78 …if ((inputs_shape_.size() != ACTIVATION_INPUTS_SIZE) || (outputs_shape_.size() != ACTIVATION_OUTPU… in GenerateOpStrategies()
80 << outputs_shape_.size() << "is wrong."; in GenerateOpStrategies()
164 …if ((inputs_shape_.size() != ACTIVATION_INPUTS_SIZE) || (outputs_shape_.size() != ACTIVATION_OUTPU… in GetAttrs()
184 …if ((inputs_shape_.size() != ACTIVATION_INPUTS_SIZE) || (outputs_shape_.size() != ACTIVATION_OUTPU… in GenerateOpStrategies()
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| D | tmp_identity_info.cc | 74 if ((inputs_shape_.size() != 1) || (outputs_shape_.size() != 1)) { in GenerateOpStrategies()
76 << outputs_shape_.size(); in GenerateOpStrategies()
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| D | tile_info.cc | 49 if (elements.size() != outputs_shape_[0].size()) { in GetAttrs()
111 if (inputs_shape_.empty() || outputs_shape_.empty()) { in InferTensorMap()
127 int64_t size = SizeToLong(outputs_shape_[0].size()); in InferTensorMap()
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| D | prelu_info.cc | 87 …if ((inputs_shape_.size() != PRELU_INPUTS_SIZE) || (outputs_shape_.size() != PRELU_OUTPUTS_SIZE)) { in GetAttrs()
89 << outputs_shape_.size() << " is wrong."; in GetAttrs()
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| D | transpose_info.cc | 91 if ((inputs_shape_.size() != 1) || (outputs_shape_.size() != 1)) { in InferTensorMap()
93 << inputs_shape_.size() << ", " << outputs_shape_.size(); in InferTensorMap()
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| D | maxpool_info.cc | 79 if (outputs_shape_[0][2] % h_strategy != 0) { in CheckHWStrategy()
86 if (outputs_shape_[0][3] % w_strategy != 0) { in CheckHWStrategy()
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| D | batch_parallel_info.cc | 97 for (size_t i = 0; i < outputs_shape_.size(); i++) { in InferTensorMap()
99 for (size_t j = 0; j < outputs_shape_[i].size(); ++j) { in InferTensorMap()
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| D | conv2d_info.cc | 140 if (outputs_shape_[0][2] % h_strategy != 0) { in CheckHWStrategyBase()
147 if (outputs_shape_[0][3] % w_strategy != 0) { in CheckHWStrategyBase()
432 int64_t w_dimension_output_shape = outputs_shape_[0][3]; in ComputeOverlapLeftSizeByRankBias()
442 int64_t w_dimension_output_shape = outputs_shape_[0][3]; in ComputeOverlapRightSizeByRankBias()
947 if (w_strategy > 1 && inputs_shape_[0][3] * stride_[3] != outputs_shape_[0][3]) { in CheckHWStrategy()
1085 int64_t w_output_shape = outputs_shape_[0][3]; in ComputeOverlapLeftSizeByRankBias()
1108 int64_t w_output_shape = outputs_shape_[0][3]; in ComputeOverlapRightSizeByRankBias()
1144 int64_t w_output_shape = outputs_shape_[0][3]; in InferNewPadList()
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| D | gatherd_info.cc | 113 …if (inputs_shape_.empty() || outputs_shape_.empty() || inputs_tensor_map_.empty() || outputs_tenso… in InferTensorInfo()
133 …if (output_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_[i], outputs_shape_[i]) != … in InferTensorInfo()
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| D | unique_info.cc | 91 …if ((inputs_shape_.size() != UNIQUE_INPUTS_SIZE) || (outputs_shape_.size() != UNIQUE_OUTPUTS_SIZE)… in GetAttrs()
93 << outputs_shape_.size() << " is wrong."; in GetAttrs()
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| D | operator_info.cc | 203 …if (inputs_shape_.empty() || outputs_shape_.empty() || inputs_tensor_map_.empty() || outputs_tenso… in InferTensorInfo()
220 …if (output_layout.InitFromVector(dev_matrix_shape_, outputs_tensor_map_[i], outputs_shape_[i]) != … in InferTensorInfo()
704 if (InferSliceShapeByStrategy(outputs_strategy, outputs_shape_, outputs_slice_shape) != SUCCESS) { in InferSliceShape()
1653 if (output_lengths.size() != outputs_shape_.size()) { in SetInputAndOutputTypeLength()
1655 << " do not have the same number of outputs shape: " << outputs_shape_.size(); in SetInputAndOutputTypeLength()
1668 if (outputs_type_lengths_.size() != outputs_shape_.size()) { in GetOutputsTotalSize()
1670 << " do not have the same number of outputs shape: " << outputs_shape_.size(); in GetOutputsTotalSize()
1674 …auto size = std::accumulate(outputs_shape_[i].begin(), outputs_shape_[i].end(), static_cast<double… in GetOutputsTotalSize()
1684 if (outputs_type.size() != outputs_shape_.size()) { in set_outputs_type()
1686 << " do not have the same number of outputs shape: " << outputs_shape_.size(); in set_outputs_type()
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| D | matmul_dds_info.cc | 202 …if ((inputs_shape_.size() != MATMUL_DDS_INPUTS_SIZE) || (outputs_shape_.size() != MATMUL_DDS_OUTPU… in GetAttrs()
204 << outputs_shape_.size() << " is wrong."; in GetAttrs()
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| D | matmul_info.cc | 121 …if ((inputs_shape_.size() != MATMUL_INPUTS_SIZE) || (outputs_shape_.size() != MATMUL_OUTPUTS_SIZE)… in GetAttrs()
297 } else if (outputs_shape_[0][0] % (dev_matrix_shape_[0] * dev_matrix_shape_[1]) != 0) { in InferTensorMap()
329 …(output_layout.InitFromVector(output_dev_matrix_shape, outputs_tensor_map_[0], outputs_shape_[0]) … in InferTensorLayout()
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| D | loss_info.cc | 64 (outputs_shape_.size() != SoftmaxCrossEntropyWithLogitsOutputsSize)) { in GetAttrs()
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| D | operator_info.h | 60 outputs_shape_(std::move(outputs_shape)), in OperatorInfo()
229 Shapes outputs_shape_; variable
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| D | split_info.cc | 129 for (size_t i = 0; i < outputs_shape_.size(); ++i) { in InferTensorMap()
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| D | broadcast_to_info.cc | 106 size_t len_diff = outputs_shape_.at(0).size() - inputs_shape_.at(0).size(); in InferTensorMap()
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| D | reduce_method_info.cc | 350 Shape output_shape = outputs_shape_.at(0); in InferTensorInfo()
479 Shape output_shape = outputs_shape_.at(0); in InferTensorInfo()
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