/third_party/mindspore/mindspore/ccsrc/backend/optimizer/ascend/ir_fusion/ |
D | adam_apply_one_fusion.cc | 25 VectorRef mul2 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex2], input_vars_[kIndex1]}); in DefinePattern() 30 VectorRef mul0 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex0], input_vars_[kIndex2]}); in DefinePattern() 40 VectorRef mul2 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex2], input_vars_[kIndex1]}); in DefinePattern() 45 VectorRef mul0 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex0], input_vars_[kIndex2]}); in DefinePattern() 55 VectorRef mul2 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex2], input_vars_[kIndex1]}); in DefinePattern() 60 VectorRef mul0 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex0], input_vars_[kIndex2]}); in DefinePattern() 70 VectorRef mul2 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex2], input_vars_[kIndex1]}); in DefinePattern() 75 VectorRef mul0 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex0], input_vars_[kIndex2]}); in DefinePattern() 85 VectorRef mul2 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex2], input_vars_[kIndex1]}); in DefinePattern() 90 VectorRef mul0 = VectorRef({prim::kPrimMul, mul_x_input_vars_[kIndex0], input_vars_[kIndex2]}); in DefinePattern() [all …]
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D | bn_reduce_grad_conv2d_backprop_filter_fusion.cc | 57 …kIndex0] == x_shape[kIndex1] && c[kIndex1] == y_shape[kIndex1] && c[kIndex2] == x_shape[kIndex2] && in CheckSupported() 58 …c[kIndex3] == x_shape[kIndex3] && c[kIndex4] == y_shape[kIndex2] && c[kIndex5] == y_shape[kIndex3]… in CheckSupported() 59 c[kIndex6] == out_shape[kIndex2] && c[kIndex7] == out_shape[kIndex3]); in CheckSupported() 89 conv_back_filter->input(kIndex2)}; in Process()
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D | lamb_next_mv_with_decay_v1_rule.cc | 39 auto sqrt0_anf = real_div2->input(kIndex2); in GetSharedNodes() 48 …return std::make_tuple(add3->input(kIndex2), real_div2->input(kIndex1), add2->input(kIndex1), add2… in GetSharedNodes() 69 auto add4_anf = real_div4->input(kIndex2); in MatchAdd5Pattern() 86 …return add5->input(kIndex2) == mul4 && real_div4->input(kIndex1) == real_div0 && sqrt1->input(kInd… in MatchAdd5Pattern() 87 *add4->input(kIndex2) == *add2_y; in MatchAdd5Pattern() 193 (void)manager->Replace(add1, fusion_node_outputs[kIndex2]); in Process()
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D | lamb_next_mv_with_decay_rule.cc | 51 (void)manager->Replace(add1, new_node_outputs[kIndex2]); in GetLambNextMVWithDecayOutput() 138 …torRef mul2 = VectorRef({prim::kPrimMul, input_vars_[kIndex1], constant_mul_input_vars_[kIndex2]}); in DefinePattern() 141 VectorRef real_div1 = VectorRef({real_div1_var_, add1, input_vars_[kIndex2]}); in DefinePattern() 179 …VectorRef mul2 = VectorRef({prim::kPrimMul, constant_mul_input_vars_[kIndex2], input_vars_[kIndex1… in DefinePattern() 182 VectorRef real_div1 = VectorRef({real_div1_var_, add1, input_vars_[kIndex2]}); in DefinePattern() 220 …torRef mul2 = VectorRef({prim::kPrimMul, input_vars_[kIndex1], constant_mul_input_vars_[kIndex2]}); in DefinePattern() 223 VectorRef real_div1 = VectorRef({real_div1_var_, add1, input_vars_[kIndex2]}); in DefinePattern() 262 …VectorRef mul2 = VectorRef({prim::kPrimMul, constant_mul_input_vars_[kIndex2], input_vars_[kIndex1… in DefinePattern() 265 VectorRef real_div1 = VectorRef({real_div1_var_, add1, input_vars_[kIndex2]}); in DefinePattern()
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D | parameter_and_transop_fusion.cc | 110 AnfAlgo::GetCNodeName(trans_road[kIndex2]) == kTransDataOpName) { in Run() 120 (void)manager->Replace(trans_road[kIndex2], final_node); in Run()
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D | lamb_update_with_lr_v2.cc | 33 VectorRef mul0({prim::kPrimMul, select1, input_varptr_[kIndex2]}); in DefinePattern()
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D | clip_by_value_fusion.cc | 89 … is_first_input ? maximum_input1 : maximum_input0, minimum->input(kIndex2)}; in Process()
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D | mul_addn_fusion.cc | 36 inputs.push_back(addn->input(kIndex2)); in CreateFusionNode()
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D | momentum_lossscale_fusion.cc | 84 cnode->input(kIndex2), in Process()
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/third_party/mindspore/mindspore/ccsrc/backend/optimizer/ascend/mindir/ |
D | maxpool_to_maxpool_with_argmax.cc | 42 auto maxpool_anf = maxpool_grad->input(kIndex2); in GetMaxPool() 102 strides[kIndex1] = strides[kIndex2]; in SetNodeAttrs() 103 strides[kIndex2] = strides[kIndex3]; in SetNodeAttrs() 106 ksize[kIndex1] = ksize[kIndex2]; in SetNodeAttrs() 107 ksize[kIndex2] = ksize[kIndex3]; in SetNodeAttrs()
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D | conv2d_unify_mindir.cc | 42 constexpr auto kIndex2 = 2; variable 195 conv2d_backfil->input(kIndex2), conv2d_backfil->input(kIndex3), conv2d_backfil->input(kIndex1)}; in CreateDepthwiseConv2DBackpropFilter() 278 auto transpose = CreateTranspose(graph, conv2d, conv2d->input(kIndex2), true); in Process() 309 auto transpose = CreateTranspose(graph, conv2d_backin, conv2d_backin->input(kIndex2), true); in Process()
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D | sparse_softmax_cross_entropy_with_logits_unify_mindir.cc | 87 …one_hot_inputs = {NewValueNode(one_hot_primitive), sparse_softmax_node->input(kIndex2), value_on_n… in CreateOneHot() 96 …one_hot_inputs = {NewValueNode(one_hot_primitive), sparse_softmax_node->input(kIndex2), depth_node… in CreateOneHot() 442 auto sparse_softmax_node = GetSparseNode(depend_node, kIndex2); in Process() 456 real_div_node = CreateRealDiv(graph, sparse_softmax_node_grad, mul_node->input(kIndex2)); in Process() 496 auto sparse_softmax_node = GetSparseNode(depend_node, kIndex2); in Process() 572 real_div_node = CreateRealDiv(graph, sparse_softmax_node_grad, mul_node->input(kIndex2)); in Process()
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D | dropout_unify_mindir.cc | 116 MS_EXCEPTION_IF_NULL(getitem_cnode->input(kIndex2)); in NeedUpdate() 117 auto index_vnode = getitem_cnode->input(kIndex2)->cast<ValueNodePtr>(); in NeedUpdate() 211 auto getitem1_node = dropout_grad_cnode->input(kIndex2); in Process() 380 auto mask_input = dropout_grad_cnode->input(kIndex2); in Process()
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/third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/tbe/ |
D | tbe_adapter.h | 68 inputs_json->push_back(inputs_list[kIndex2]); in InputOrderPass() 79 inputs_json->push_back(inputs_list[kIndex2]); in InputOrderPass() 105 inputs_json->push_back(inputs_list[kIndex2]); in DynamicInputAdjusted() 113 inputs_json->push_back(inputs_list[kIndex2]); in DynamicInputAdjusted()
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D | tbe_adapter.cc | 88 inputs_json->push_back(inputs_list[kIndex2]); in DynamicInputAdjusted() 96 inputs_json->push_back(inputs_list[kIndex2]); in DynamicInputAdjusted() 115 inputs_json->push_back(inputs_list[kIndex2]); in InputOrderPass() 126 inputs_json->push_back(inputs_list[kIndex2]); in InputOrderPass() 178 (void)reorder_data_layer->emplace_back(data_layer[kIndex2]); in FusionDataOrderPass()
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/third_party/mindspore/mindspore/ccsrc/backend/optimizer/ascend/ir_fission/ |
D | batch_norm_grad_split.cc | 39 bn_grad_inputs[kIndex2], bn_grad_inputs[kIndex4], bn_grad_inputs[kIndex5]}; in CreateOutputsOfUpdateGrad() 68 bn_grad_inputs[kIndex2], in CreateOutputsOfReduceGrad()
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D | bn_grad_split.cc | 40 bn_grad_inputs[kIndex2], bn_grad_inputs[kIndex4], bn_grad_inputs[kIndex5]}; in CreateOutputsOfUpdateGrad() 67 bn_grad_inputs[kIndex2], in CreateOutputsOfReduceGrad()
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D | batch_norm_bert_fission.cc | 75 auto bn_input1 = bn_cnode->input(kIndex2); in CreateBNTrainingReduce() 107 bn_cnode->input(kIndex2), in CreateBNTrainingUpdateV2()
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D | dynamic_rnn_grad_fission_v2.cc | 67 …auto origin_input1_shape = AnfAlgo::GetOutputInferShape(dynamic_rnn_grad_cnode->input(kIndex2), 0); in CreateTLoopNode() 78 auto origin_output2_shape = AnfAlgo::GetOutputInferShape(dynamic_rnn_grad_cnode, kIndex2); in CreateTLoopNode() 180 auto split_nodes = result_nodes[kIndex2]; in AddLSTMInputGradNode() 229 (void)matmul_inputs.emplace_back(dynamic_rnn_grad_cnode->input(kIndex2)); in AddLSTMInputGradNode() 442 AnfAlgo::GetOutputInferShape(lstm_input_grad, 0)[kIndex2]}; in CreateBatchMatMul2()
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D | dynamic_gru_v2_grad_fission.cc | 42 {"x", kIndex1}, {"weight_input", kIndex2}, {"weight_hidden", kIndex3}, 48 …ing, size_t> output_index = {{"dw_input", kIndex0}, {"dw_hidden", kIndex1}, {"db_input", kIndex2}, 52 {"dh_pre_t", kIndex1}, {"h", kIndex2}, {"dy", kIndex3}, {"dh", kIndex4}, 56 {"dh_prev", kIndex0}, {"dgate_h", kIndex1}, {"dnt_x", kIndex2}};
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D | single_batch_norm_fission.cc | 72 bn_cnode->input(kIndex2), in CreateBNTrainingUpdateV3()
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/third_party/mindspore/mindspore/ccsrc/backend/optimizer/ascend/buffer_fusion/ |
D | ub_pattern_fusion.cc | 128 …item->input(kIndex1), LongToSize(GetValue<int64_t>(GetValueNode(tuple_getitem->input(kIndex2)))))); in CreateFusionOpKernelInfo() 130 …item->input(kIndex1), LongToSize(GetValue<int64_t>(GetValueNode(tuple_getitem->input(kIndex2)))))); in CreateFusionOpKernelInfo() 265 auto output_idx1 = GetValue<int64_t>(GetValueNode(getitem1->input(kIndex2))); in TupleGetitemNodeCompare() 266 auto output_idx2 = GetValue<int64_t>(GetValueNode(getitem2->input(kIndex2))); in TupleGetitemNodeCompare() 332 auto input2 = getitem_ptr->input(kIndex2); in GetFusionScopeOutputNodeList() 376 auto input2 = output_cnode->input(kIndex2); in SetFusionOpRefInfos()
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D | batchmatmul_fusedmuladd_fusion_pass.cc | 30 auto batch_matmul = cnode->input(kIndex2); in MatchBatchMatmulFusedMulAdd()
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D | conv2dbackprop_eltwise_eltwise_fusion_pass.cc | 41 auto double_in_eltwise_input = input_cnode->input(kIndex2); in MatchConv2DBackpropInputEltwiseEltwise()
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/third_party/mindspore/mindspore/ccsrc/runtime/device/ascend/ |
D | kernel_select_graph_kernel.cc | 124 frac_nz_axis.push_back(axis_idx + SizeToLong(kIndex2)); in DefaultToFracNZAxis() 125 } else if (axis_idx == shape_len - SizeToLong(kIndex2)) { in DefaultToFracNZAxis() 127 frac_nz_axis.push_back(axis_idx + SizeToLong(kIndex2)); in DefaultToFracNZAxis()
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