mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-06-06 00:03:22 +00:00
300 lines
No EOL
18 KiB
XML
300 lines
No EOL
18 KiB
XML
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<AutoVisualizer xmlns="http://schemas.microsoft.com/vstudio/debugger/natvis/2010">
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and must be updated on protobuf version change -->
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<DisplayString>{{ size={current_size_} }}</DisplayString>
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<Expand>
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<Type Name="google::protobuf::RepeatedPtrField<*>">
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<DisplayString>{{ size={current_size_} }}</DisplayString>
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<Expand>
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<Item Name="[size]" ExcludeView="simple">current_size_</Item>
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<Item Name="[capacity]" ExcludeView="simple">total_size_</Item>
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<Item Name="[arena]" Condition="arena_" ExcludeView="simple">arena_</Item>
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<ArrayItems Condition="rep_ != 0">
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<Size>current_size_</Size>
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<ValuePointer>($T1**)rep_->elements</ValuePointer>
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</ArrayItems>
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</Expand>
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</Type>
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<Type Name="google::protobuf::internal::TaggedPtr<*>">
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<DisplayString>{{ {*($T1*)ptr_} }}</DisplayString>
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<Expand>
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</Expand>
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</Type>
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<Type Name="google::protobuf::internal::TaggedStringPtr">
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<DisplayString>{{ { *(std::string*)((uintptr_t)(ptr_) & ~0x3) } }}</DisplayString>
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<Expand>
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</Expand>
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</Type>
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<!--ONNX Specific protobuf classes
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Some examples show calling functions on classes, however, this is not supported in VS2019
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Thus we need to come up with has_*() utils.
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-->
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<Type Name="onnx::StringStringEntryProto">
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<DisplayString>{{ {_impl_.key_.tagged_ptr_}:{_impl_.value_.tagged_ptr_} }}</DisplayString>
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<Expand>
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<Item Name="[key]">_impl_.key_.tagged_ptr_</Item>
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<Item Name="[value]">_impl_.value_.tagged_ptr_</Item>
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</Expand>
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</Type>
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<Type Name="onnx::TensorAnnotation">
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<DisplayString>{{ tensor_name={_impl_.tensor_name_.tagged_ptr_} }}</DisplayString>
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<Expand>
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<Item Name="[tensor_name]">_impl_.tensor_name_.tagged_ptr_</Item>
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<Item Name="[quant_parameter_tensor_names]">_impl_.quant_parameter_tensor_names_</Item>
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</Expand>
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</Type>
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<Type Name="onnx::ValueInfoProto">
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<Intrinsic Name="_has_type" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000004u) != 0"/>
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<DisplayString>{{ name={_impl_.name_.tagged_ptr_} }}</DisplayString>
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<Expand>
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<Item Name="[name]">_impl_.name_.tagged_ptr_</Item>
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<Item Name="[type]" Condition="_has_type()">_impl_.type_</Item>
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<Item Name="[has_type]">_has_type()</Item>
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</Expand>
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</Type>
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<Type Name="onnx::OperatorSetIdProto">
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<DisplayString>{{ domain={ _impl_.domain_.tagged_ptr_ }, version={ _impl_.version_ } }}</DisplayString>
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<Expand>
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</Expand>
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</Type>
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<Type Name="onnx::AttributeProto">
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<Intrinsic Name="_has_tensor" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000010u) != 0"/>
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<Intrinsic Name="_has_graph" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000020u) != 0"/>
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<Intrinsic Name="_has_type_proto" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000040u) != 0"/>
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<DisplayString>{{ name={ _impl_.name_.tagged_ptr_ }, type={ (AttributeProto_AttributeType)_impl_.type_ } }}</DisplayString>
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<Expand>
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<Item Name="[name]">_impl_.name_.tagged_ptr_</Item>
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<Item Name="[type]">(AttributeProto_AttributeType)_impl_.type_</Item>
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<Item Name="[i]" Condition="_impl_.type_ == AttributeProto_AttributeType_INT">_impl_.i_</Item>
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<Item Name="[ints]" Condition="_impl_.type_ == AttributeProto_AttributeType_INTS">_impl_.ints_</Item>
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<Item Name="[f]" Condition="_impl_.type_ == AttributeProto_AttributeType_FLOAT">_impl_.f_</Item>
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<Item Name="[floats]" Condition="_impl_.type_ == AttributeProto_AttributeType_FLOATS">_impl_.floats_</Item>
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<Item Name="[strings]" Condition="_impl_.type_ == AttributeProto_AttributeType_STRINGS">_impl_.strings_</Item>
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<Item Name="[t]" Condition="_impl_.type_ == AttributeProto_AttributeType_TENSOR && _has_tensor()">_impl_.t_</Item>
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<Item Name="[tensors]" Condition="_impl_.type_ == AttributeProto_AttributeType_TENSORS">_impl_.tensors_</Item>
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<Item Name="[g]" Condition="_impl_.type_ == AttributeProto_AttributeType_GRAPH && _has_graph()">_impl_.g_</Item>
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<Item Name="[graphs]" Condition="_impl_.type_ == AttributeProto_AttributeType_GRAPHS">_impl_.graphs_</Item>
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<Item Name="[tp]" Condition="_impl_.type_ == AttributeProto_AttributeType_TYPE_PROTO && _has_type_proto()">_impl_.tp_</Item>
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<Item Name="[type_protos]" Condition="_impl_.type_ == AttributeProto_AttributeType_TYPE_PROTOS">_impl_.type_protos_</Item>
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<Item Name="[sparse_tensor]" Condition="_impl_.type_ == AttributeProto_AttributeType_SPARSE_TENSOR && _has_sparse_tensor()">_impl_.sparse_tensor_</Item>
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<Item Name="[has_tensor]">_has_tensor()</Item>
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<Item Name="[has_graph]">_has_graph()</Item>
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<Item Name="[has_type_proto]">_has_type_proto()</Item>
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<Item Name="[has_sparse_tensor]">_has_sparse_tensor()</Item>
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</Expand>
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</Type>
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<Type Name="onnx::NodeProto">
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<DisplayString>{{ name={ _impl_.name_.tagged_ptr_ }, domain={ _impl_.domain_.tagged_ptr_ } }}</DisplayString>
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<Expand>
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<Item Name="[name]">_impl_.name_.tagged_ptr_</Item>
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<Item Name="[domain]">_impl_.domain_.tagged_ptr_</Item>
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<Item Name="[op_type]">_impl_.op_type_.tagged_ptr_</Item>
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<Item Name="[input]">_impl_.input_</Item>
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<Item Name="[output]">_impl_.output_</Item>
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<Item Name="[attribute]">_impl_.attribute_</Item>
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</Expand>
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</Type>
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<Type Name="onnx::FunctionProto">
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<DisplayString>{{ name={ _impl_.name_.tagged_ptr_ } }}</DisplayString>
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<Expand>
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<Item Name="[input]">_impl_.input_</Item>
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<Item Name="[output]">_impl_.output_</Item>
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<Item Name="[node]">_impl_.node_</Item>
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<Item Name="[attribute]">_impl_.attribute_</Item>
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<Item Name="[attribute_proto]" ExcludeView="simple">_impl_.attribute_proto_</Item>
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<Item Name="[doc]">_impl_.doc_string_.tagged_ptr_</Item>
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<Item Name="[opset_import]">_impl_.opset_import_</Item>
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<Item Name="[domain]">_impl_.domain_.tagged_ptr_</Item>
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</Expand>
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</Type>
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<Type Name="onnx::GraphProto">
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<DisplayString>{{ name={ _impl_.name_.tagged_ptr_ } }}</DisplayString>
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<Expand>
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<Item Name="[name]">_impl_.name_.tagged_ptr_</Item>
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<Item Name="[value_info]">_impl_.value_info_</Item>
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<Item Name="[input]">_impl_.input_</Item>
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<Item Name="[output]">_impl_.output_</Item>
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<Item Name="[node]">_impl_.node_</Item>
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<Item Name="[initializer]">_impl_.initializer_</Item>
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<Item Name="[sparse_initializer]">_impl_.sparse_initializer_</Item>
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<Item Name="[doc]" ExcludeView="simple">_impl_.doc_string_.tagged_ptr_</Item>
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</Expand>
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</Type>
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<Type Name="onnx::ModelProto">
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<DisplayString>{{ producer={_impl_.producer_name_.tagged_ptr_}, domain={ _impl_.domain_.tagged_ptr_ } }}</DisplayString>
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<Expand>
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<Item Name="[opset_import]" ExcludeView="simple">_impl_.opset_import_</Item>
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<Item Name="[metadata_props]" ExcludeView="simple">_impl_.metadata_props_</Item>
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<Item Name="[producer_version]" ExcludeView="simple">_impl_.producer_version_.tagged_ptr_</Item>
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<Item Name="[ir_version]" ExcludeView="simple">_impl_.ir_version_</Item>
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<Item Name="[model_version]" ExcludeView="simple">_impl_.model_version_</Item>
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<Item Name="[doc]" ExcludeView="simple">_impl_.doc_string_.tagged_ptr_</Item>
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<Item Name="[graph]" ExcludeView="simple">_impl_.graph_</Item>
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</Expand>
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</Type>
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<Type Name="onnx::TensorShapeProto_Dimension">
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<DisplayString Condition="*_impl_._oneof_case_ == 0">empty</DisplayString>
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<DisplayString Condition="*_impl_._oneof_case_ == kDimValue">{{ v = {_impl_.value_.dim_value_} }}</DisplayString>
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<DisplayString Condition="*_impl_._oneof_case_ == kDimParam">{{ p = {_impl_.value_.dim_param_.tagged_ptr_} }}</DisplayString>
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<Expand>
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</Expand>
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</Type>
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<Type Name="onnx::TensorShapeProto">
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<DisplayString>{{ size={ _impl_.dim_.current_size_ } }}</DisplayString>
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<Expand>
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<Item Name="[dims]" ExcludeView="simple">_impl_.dim_</Item>
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</Expand>
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</Type>
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<!--Type Protos-->
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<Type Name="onnx::TypeProto">
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<DisplayString>{{ type={ (ValueCase)*_impl_._oneof_case_ } }}</DisplayString>
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<Expand>
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<Item Name="[type]" ExcludeView="simple">(ValueCase)*_impl_._oneof_case_</Item>
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<Item Name="[tensor_type]" Condition="(ValueCase)*_impl_._oneof_case_ == kTensorType" ExcludeView="simple">_impl_.value_.tensor_type_</Item>
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<Item Name="[sequence_type]" Condition="(ValueCase)*_impl_._oneof_case_ == kSequenceType" ExcludeView="simple">_impl_.value_.sequence_type_</Item>
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<Item Name="[map_type]" Condition="(ValueCase)*_impl_._oneof_case_ == kMapType" ExcludeView="simple">_impl_.value_.map_type_</Item>
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<Item Name="[sparse_tensor_type]" Condition="(ValueCase)*_impl_._oneof_case_ == kSparseTensorType" ExcludeView="simple">_impl_.value_.sparse_tensor_type_</Item>
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<Item Name="[optional_type]" Condition="(ValueCase)*_impl_._oneof_case_ == kOptionalType" ExcludeView="simple">_impl_.value_.optional_type_</Item>
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<Item Name="[denotation]" ExcludeView="simple">_impl_.denotation_.tagged_ptr_</Item>
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</Expand>
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</Type>
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<Type Name="onnx::TypeProto_Tensor">
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<Intrinsic Name="_has_shape" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000001u) != 0"/>
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<DisplayString>{{ elem_type={ (TensorProto_DataType)_impl_.elem_type_ } }}</DisplayString>
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<Expand>
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<Item Name="[elem_type]" ExcludeView="simple">(TensorProto_DataType)_impl_.elem_type_</Item>
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<Item Name="[shape]" Condition="_has_shape()" ExcludeView="simple">_impl_.shape_</Item>
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<Item Name="[has_shape]" ExcludeView="simple">_has_shape()</Item>
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</Expand>
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</Type>
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<Type Name="onnx::TypeProto_Sequence">
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<Intrinsic Name="_has_element_type" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000001u) != 0"/>
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<DisplayString Condition="_has_element_type()">{{ elem_type={ *_impl_.elem_type_ } }}</DisplayString>
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<Expand>
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<Item Name="[elem_type]" Condition="_has_element_type()" ExcludeView="simple">_impl_.elem_type_</Item>
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<Item Name="[has_element_type]" ExcludeView="simple">_has_element_type()</Item>
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</Expand>
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</Type>
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<Type Name="onnx::TypeProto_Map">
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<Intrinsic Name="_has_value_type" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000001u) != 0"/>
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<DisplayString>{{ key_type={ (TensorProto_DataType)_impl_.key_type_ } }}</DisplayString>
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<Expand>
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<Item Name="[key_type]" ExcludeView="simple">(TensorProto_DataType)_impl_.key_type_</Item>
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<Item Name="[value_type]" Condition="_has_value_type()" ExcludeView="simple">_impl_.value_type_</Item>
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<Item Name="[has_value_type]" ExcludeView="simple">_has_value_type()</Item>
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</Expand>
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</Type>
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<Type Name="onnx::TypeProto_SparseTensor">
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<Intrinsic Name="_has_shape" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000001u) != 0"/>
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<DisplayString>{{ elem_type={ (TensorProto_DataType)_impl_.elem_type_ } }}</DisplayString>
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<Expand>
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<Item Name="[elem_type]" ExcludeView="simple">(TensorProto_DataType)_impl_.elem_type_</Item>
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<Item Name="[shape]" Condition="_has_shape()" ExcludeView="simple">_impl_.shape_</Item>
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<Item Name="[has_shape]" ExcludeView="simple">_has_shape()</Item>
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</Expand>
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</Type>
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<Type Name="onnx::TypeProto_Optional">
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<Intrinsic Name="_has_element_type" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000001u) != 0"/>
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<DisplayString Condition="_has_element_type()">{{ elem_type={ *_impl_.elem_type_ } }}</DisplayString>
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<Expand>
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<Item Name="[elem_type]" Condition="_has_element_type()" ExcludeView="simple">_impl_.elem_type_</Item>
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<Item Name="[has_element_type]" ExcludeView="simple">_has_element_type()</Item>
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</Expand>
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</Type>
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<!--Protos-->
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<Type Name="onnx::TensorProto_Segment">
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<DisplayString>{{ begin={ _impl_.begin_ }, end={ _impl_.end_ } }}</DisplayString>
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<Expand></Expand>
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</Type>
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<!--TODO Figure out how to calculate the size of the tensor given its shape. Loops are only possible in custom lists. -->
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<Type Name="onnx::TensorProto">
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<Intrinsic Name="_has_raw_data" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000002u) != 0" />
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<Intrinsic Name="_has_data_location" Expression="((_impl_._has_bits_.has_bits_[0] & 0x00000020u) != 0)" />
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<Intrinsic Name="_shape_array" Expression="(int64_t*)_impl_.dims_.arena_or_elements_" />
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<Intrinsic Name="_shape_size" Expression="_impl_.dims_.current_size_" />
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<Intrinsic Name="_shape_size_1" Expression="_shape_array()[0]" />
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<Intrinsic Name="_shape_size_2" Expression="_shape_array()[0] * _shape_array()[1]"/>
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<Intrinsic Name="_shape_size_3" Expression="_shape_size_2() * _shape_array()[2]" />
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<Intrinsic Name="_shape_size_4" Expression="_shape_size_3() * _shape_array()[3]" />
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<Intrinsic Name="_shape_size_5" Expression="_shape_size_4() * _shape_array()[4]" />
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<DisplayString>{{ name={_impl_.name_.tagged_ptr_}, data_type={ (TensorProto_DataType)_impl_.data_type_ } }}</DisplayString>
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<Expand>
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<Item Name="[name]" ExcludeView="simple">_impl_.name_.tagged_ptr_</Item>
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<Item Name="[data_type]" ExcludeView="simple">(TensorProto_DataType)_impl_.data_type_</Item>
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<Item Name="[size]" Condition="_shape_size() == 0" ExcludeView="simple">1</Item>
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<Item Name="[size]" Condition="_shape_size() == 1" ExcludeView="simple">_shape_size_1()</Item>
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<Item Name="[size]" Condition="_shape_size() == 2" ExcludeView="simple">_shape_size_2()</Item>
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<Item Name="[size]" Condition="_shape_size() == 3" ExcludeView="simple">_shape_size_3()</Item>
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<Item Name="[size]" Condition="_shape_size() == 4" ExcludeView="simple">_shape_size_4()</Item>
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<Item Name="[size]" Condition="_shape_size() == 5" ExcludeView="simple">_shape_size_5()</Item>
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<Item Name="[shape]" ExcludeView="simple">_impl_.dims_</Item>
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<Item Name="[float_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_FLOAT && !_has_raw_data()">_impl_.float_data_</Item>
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<Item Name="[bool_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_BOOL && !_has_raw_data()">_impl_.int32_data_</Item>
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<Item Name="[int8_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_INT8 && !_has_raw_data()">_impl_.int32_data_</Item>
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<Item Name="[uint8_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_UINT8 && !_has_raw_data()">_impl_.int32_data_</Item>
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<Item Name="[int32_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_INT32 && !_has_raw_data()">_impl_.int32_data_</Item>
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<Item Name="[uint32_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_UINT32 && !_has_raw_data()">_impl_.int64_data_</Item>
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<Item Name="[int64_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_INT64 && !_has_raw_data()">_impl_.int64_data_</Item>
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<Item Name="[uint64_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_UINT64 && !_has_raw_data()">_impl_.uint64_data_</Item>
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<Item Name="[double_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_DOUBLE && !_has_raw_data()">_impl_.double_data_</Item>
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<Item Name="[string_data]" ExcludeView="simple" Condition="_impl_.data_type_ == TensorProto_DataType_STRING && !_has_raw_data()">_impl_.string_data_</Item>
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<Item Name="[raw_data]" ExcludeView="simple" Condition="_has_raw_data()">_impl_.raw_data_.tagged_ptr_</Item>
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<Item Name="[data_location]" ExcludeView="simple" Condition="_has_data_location()">(TensorProto_DataLocation) _impl_.data_location_</Item>
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<Item Name="[external_data]" ExcludeView="simple" Condition="_has_data_location()">_impl_.external_data_</Item>
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<Item Name="[has_raw_data]" ExcludeView="simple">_has_raw_data()</Item>
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<Item Name="[has_data_location]" ExcludeView="simple">_has_data_location()</Item>
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<Item Name="[has_segment]" ExcludeView="simple">_has_segment()</Item>
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</Expand>
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</Type>
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<Type Name="onnx::SparseTensorProto">
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<Intrinsic Name="_has_values" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000001u) != 0"/>
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<Intrinsic Name="_has_indices" Expression="(_impl_._has_bits_.has_bits_[0] & 0x00000002u) != 0"/>
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<DisplayString>{{ SparseTensorProto }}</DisplayString>
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<Expand>
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<Item Name="[dense_shape]" ExcludeView="simple">_impl_.dims_</Item>
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<Item Name="[values]" Condition="_has_values()" ExcludeView="simple">_impl_.values_</Item>
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<Item Name="[indices]" Condition="_has_indices()" ExcludeView="simple">_impl_.indices_</Item>
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<Item Name="[has_values]" ExcludeView="simple">_has_values()</Item>
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