| /third_party/mindspore/mindspore/core/ops/ |
| D | lerp.cc | 40 …auto weight_shape_map = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->… in InferShape()
43 if (input_args[kInputIndex2]->isa<abstract::AbstractTensor>()) { in InferShape()
61 if (input_args[kInputIndex2]->isa<abstract::AbstractTensor>()) { in InferType()
62 (void)types.emplace("weight", input_args[kInputIndex2]->BuildType()); in InferType()
64 …(void)CheckAndConvertUtils::CheckSubClass("weight", input_args[kInputIndex2]->BuildType(), {kFloat… in InferType()
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| D | masked_fill.cc | 36 …auto value_shape_map = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->B… in InferShape()
39 if (input_args[kInputIndex2]->isa<abstract::AbstractTensor>()) { in InferShape()
59 if (input_args[kInputIndex2]->isa<abstract::AbstractTensor>()) { in InferType()
62 (void)types.emplace("value", input_args[kInputIndex2]->BuildType()); in InferType()
65 …(void)CheckAndConvertUtils::CheckSubClass("value", input_args[kInputIndex2]->BuildType(), {kFloat}… in InferType()
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| D | gather.cc | 45 …(void)CheckAndConvertUtils::CheckTypeValid("axis_type", input_args[kInputIndex2]->BuildType(), int… in GatherInfer()
51 if (input_args[kInputIndex2]->isa<abstract::AbstractTensor>()) { in GatherInfer()
52 auto axis = input_args[kInputIndex2]->cast<abstract::AbstractTensorPtr>(); in GatherInfer()
59 } else if (input_args[kInputIndex2]->isa<abstract::AbstractScalar>()) { in GatherInfer()
60 auto axis = input_args[kInputIndex2]->cast<abstract::AbstractScalarPtr>(); in GatherInfer()
63 MS_LOG(EXCEPTION) << "Invalid abstract type:" << input_args[kInputIndex2]->type_name(); in GatherInfer()
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| D | fill.cc | 44 auto x_type = input_args[kInputIndex2]->BuildType(); in FillInfer()
46 auto x_value = input_args[kInputIndex2]->BuildValue(); in FillInfer()
58 …MS_LOG(ERROR) << " Fill not supported to flod the constant type " << input_args[kInputIndex2]->ToS… in FillInfer()
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| D | batch_norm.cc | 85 …auto bias = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->BuildShape()… in BatchNormInfer()
111 auto bias_type = input_args[kInputIndex2]->BuildType()->cast<TensorTypePtr>()->element(); in BatchNormInfer()
118 (void)args.emplace("bias", input_args[kInputIndex2]->BuildType()); in BatchNormInfer()
121 (void)args_moving.emplace("scale", input_args[kInputIndex2]->BuildType()); in BatchNormInfer()
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| D | scatter_nd_update.cc | 29 …auto update_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->Buil… in InferShape()
44 auto update_type = input_args[kInputIndex2]->BuildType(); in InferType()
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| D | where.cc | 42 …auto input2_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->Buil… in WhereInfer()
43 auto num2 = input_args[kInputIndex2]->BuildValue()->cast<tensor::TensorPtr>()->ElementsNum(); in WhereInfer()
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| D | fake_quant_with_min_max_vars_per_channel.cc | 49 …auto max_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->BuildSh… in FakeQuantWithMinMaxVarsPerChannelInfer()
57 auto max_type = input_args[kInputIndex2]->BuildType(); in FakeQuantWithMinMaxVarsPerChannelInfer()
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| D | gather_d.cc | 33 …auto index_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->Build… in GatherDInferShape()
68 …(void)CheckAndConvertUtils::CheckTensorTypeValid("index", input_args[kInputIndex2]->BuildType(), v… in GatherDInfer()
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| D | adam.cc | 33 …auto v_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->GetShapeT… in AdamInfer()
42 auto v_type = input_args[kInputIndex2]->BuildType(); in AdamInfer()
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| D | fake_quant_with_min_max_vars.cc | 34 …auto max_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->BuildSh… in InferShape()
56 (void)types.emplace("max", input_args[kInputIndex2]->BuildType()); in InferType()
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| D | binary_cross_entropy.cc | 39 …auto weight_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->Buil… in BinaryCrossEntroyInferShape()
66 (void)types.emplace("weight_shape", input_args[kInputIndex2]->BuildType()); in BinaryCrossEntroyInferType()
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| D | index_add.cc | 35 …auto y_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->BuildShap… in IndexAddInferShape()
70 auto updates_type = input_args[kInputIndex2]->BuildType(); in IndexAddInferType()
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| D | dropout_do_mask.cc | 63 auto keep_prop = input_args[kInputIndex2]; in InferShape()
75 auto keep_prop = input_args[kInputIndex2]; in InferType()
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| D | range.cc | 68 MS_EXCEPTION_IF_NULL(input_args[kInputIndex2]->BuildValue()); in RangeInfer()
71 auto delta_tensor = input_args[kInputIndex2]->BuildValue()->cast<tensor::TensorPtr>(); in RangeInfer()
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| D | apply_adagrad_d_a.cc | 40 auto gradient_squared_accumulator_shape = input_args[kInputIndex2]->BuildShape(); in InferShape()
69 auto gradient_squared_accumulator_type = input_args[kInputIndex2]->BuildType(); in InferType()
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| D | detection_post_process.cc | 124 MS_EXCEPTION_IF_NULL(input_args[kInputIndex2]); in DetectionPostProcessInfer()
127 auto anchors = input_args[kInputIndex2]; in DetectionPostProcessInfer()
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| D | hashtable_lookup.cc | 36 auto value_type = input_args[kInputIndex2]->BuildType(); in HashtableLookupInfer()
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| /third_party/mindspore/mindspore/core/ops/grad/ |
| D | sigmoid_cross_entropy_with_logits_grad.cc | 41 …auto dout_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->BuildS… in SigmoidCrossEntropyWithLogitsGradInfer()
51 (void)args.emplace("dout_type", input_args[kInputIndex2]->BuildType()); in SigmoidCrossEntropyWithLogitsGradInfer()
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| D | smooth_l1_loss_grad.cc | 48 …auto dloss = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->BuildShape(… in SmoothL1LossGradInfer()
58 (void)args.emplace("dloss", input_args[kInputIndex2]->BuildType()); in SmoothL1LossGradInfer()
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| D | soft_margin_loss_grad.cc | 34 …auto dout = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->BuildShape()… in SoftMarginLossGradInferShape()
49 (void)types.emplace("dout", input_args[kInputIndex2]->BuildType()); in SoftMarginLossGradInferType()
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| D | binary_cross_entropy_grad.cc | 32 …auto weight_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[kInputIndex2]->Buil… in BinaryCrossEntroyGradInferShape()
48 (void)types.emplace("weight_shape", input_args[kInputIndex2]->BuildType()); in BinaryCrossEntroyGradInferType()
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| D | conv2d_backprop_input.cc | 59 if (dout_shape_norm[kInputIndex2] != abstract::Shape::SHP_ANY && in SetPadList()
60 x_size_v[kInputIndex2] != abstract::Shape::SHP_ANY) { in SetPadList()
62 …(dout_shape_norm[kInputIndex2] - 1) * stride_h + dilation_h * (kernel_h - 1) + 1 - x_size_v[kInput… in SetPadList()
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| D | batch_norm_grad.cc | 62 auto dscale = input_args[kInputIndex2]->Broaden(); in BatchNormGradInfer()
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| /third_party/mindspore/mindspore/ccsrc/backend/optimizer/ascend/format_type/ |
| D | insert_transpose_for_dynamic_gru_v2.cc | 30 constexpr size_t kInputIndex2 = 2; variable
48 if (index == kInputIndex1 || index == kInputIndex2) { in Insert()
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