onnx.helper¶
tools¶
make function¶
All functions uses to create an ONNX graph.
- onnx.helper.make_attribute(key: str, value: Any, doc_string: Optional[str] = None) onnx.onnx_ml_pb2.AttributeProto¶
Makes an AttributeProto based on the value type.
- onnx.helper.make_empty_tensor_value_info(name: str) onnx.onnx_ml_pb2.ValueInfoProto¶
- onnx.helper.make_function(domain: str, fname: str, inputs: Sequence[str], outputs: Sequence[str], nodes: Sequence[onnx.onnx_ml_pb2.NodeProto], opset_imports: Sequence[onnx.onnx_ml_pb2.OperatorSetIdProto], attributes: Optional[Sequence[str]] = [], doc_string: Optional[str] = None) onnx.onnx_ml_pb2.FunctionProto¶
- onnx.helper.make_graph(nodes: Sequence[onnx.onnx_ml_pb2.NodeProto], name: str, inputs: Sequence[onnx.onnx_ml_pb2.ValueInfoProto], outputs: Sequence[onnx.onnx_ml_pb2.ValueInfoProto], initializer: Optional[Sequence[onnx.onnx_ml_pb2.TensorProto]] = None, doc_string: Optional[str] = None, value_info: Sequence[onnx.onnx_ml_pb2.ValueInfoProto] = [], sparse_initializer: Optional[Sequence[onnx.onnx_ml_pb2.SparseTensorProto]] = None) onnx.onnx_ml_pb2.GraphProto¶
- onnx.helper.make_map(name: str, key_type: int, keys: List[Any], values: onnx.onnx_data_pb2.SequenceProto) onnx.onnx_data_pb2.MapProto¶
Make a Map with specified key-value pair arguments.
Criteria for conversion: - Keys and Values must have the same number of elements - Every key in keys must be of the same type - Every value in values must be of the same type
- onnx.helper.make_model(graph: onnx.onnx_ml_pb2.GraphProto, **kwargs: Any) onnx.onnx_ml_pb2.ModelProto¶
- onnx.helper.make_node(op_type: str, inputs: Sequence[str], outputs: Sequence[str], name: Optional[str] = None, doc_string: Optional[str] = None, domain: Optional[str] = None, **kwargs: Any) onnx.onnx_ml_pb2.NodeProto¶
Construct a NodeProto.
- Parameters
op_type (string) – The name of the operator to construct
inputs (list of string) – list of input names
outputs (list of string) – list of output names
name (string, default None) – optional unique identifier for NodeProto
doc_string (string, default None) – optional documentation string for NodeProto
domain (string, default None) – optional domain for NodeProto. If it’s None, we will just use default domain (which is empty)
**kwargs (dict) – the attributes of the node. The acceptable values are documented in
make_attribute().
- onnx.helper.make_operatorsetid(domain: str, version: int) onnx.onnx_ml_pb2.OperatorSetIdProto¶
Construct an OperatorSetIdProto.
- Parameters
domain (string) – The domain of the operator set id
version (integer) – Version of operator set id
- onnx.helper.make_optional(name: str, elem_type: <google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper object at 0x7f5d869f0340>, value: typing.Optional[typing.Any]) onnx.onnx_data_pb2.OptionalProto¶
Make an Optional with specified value arguments.
- onnx.helper.make_optional_type_proto(inner_type_proto: onnx.onnx_ml_pb2.TypeProto) onnx.onnx_ml_pb2.TypeProto¶
Makes an optional TypeProto.
- onnx.helper.make_sequence(name: str, elem_type: <google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper object at 0x7f5d869f0580>, values: typing.Sequence[typing.Any]) onnx.onnx_data_pb2.SequenceProto¶
Make a Sequence with specified value arguments.
- onnx.helper.make_sequence_type_proto(inner_type_proto: onnx.onnx_ml_pb2.TypeProto) onnx.onnx_ml_pb2.TypeProto¶
Makes a sequence TypeProto.
- onnx.helper.make_sequence_value_info(name: str, elem_type: int, shape: Optional[Sequence[Optional[Union[str, int]]]], doc_string: str = '', elem_shape_denotation: Optional[List[str]] = None) onnx.onnx_ml_pb2.ValueInfoProto¶
Makes a Sequence[Tensors] ValueInfoProto based on the data type and shape.
- onnx.helper.make_sparse_tensor(values: onnx.onnx_ml_pb2.TensorProto, indices: onnx.onnx_ml_pb2.TensorProto, dims: Sequence[int]) onnx.onnx_ml_pb2.SparseTensorProto¶
- onnx.helper.make_sparse_tensor_type_proto(elem_type: int, shape: Optional[Sequence[Optional[Union[str, int]]]], shape_denotation: Optional[List[str]] = None) onnx.onnx_ml_pb2.TypeProto¶
Makes a SparseTensor TypeProto based on the data type and shape.
- onnx.helper.make_sparse_tensor_value_info(name: str, elem_type: int, shape: Optional[Sequence[Optional[Union[str, int]]]], doc_string: str = '', shape_denotation: Optional[List[str]] = None) onnx.onnx_ml_pb2.ValueInfoProto¶
Makes a SparseTensor ValueInfoProto based on the data type and shape.
- onnx.helper.make_tensor(name, data_type, dims, vals, raw=False)¶
Make a TensorProto with specified arguments. If raw is False, this function will choose the corresponding proto field to store the values based on data_type. If raw is True, use “raw_data” proto field to store the values, and values should be of type bytes in this case.
- onnx.helper.make_tensor_sequence_value_info(name: str, elem_type: int, shape: Optional[Sequence[Optional[Union[str, int]]]], doc_string: str = '', elem_shape_denotation: Optional[List[str]] = None) onnx.onnx_ml_pb2.ValueInfoProto¶
Makes a Sequence[Tensors] ValueInfoProto based on the data type and shape.
- onnx.helper.make_tensor_type_proto(elem_type: int, shape: Optional[Sequence[Optional[Union[str, int]]]], shape_denotation: Optional[List[str]] = None) onnx.onnx_ml_pb2.TypeProto¶
Makes a Tensor TypeProto based on the data type and shape.
- onnx.helper.make_training_info(algorithm: onnx.onnx_ml_pb2.GraphProto, algorithm_bindings: List[Tuple[str, str]], initialization: Optional[onnx.onnx_ml_pb2.GraphProto], initialization_bindings: Optional[List[Tuple[str, str]]]) onnx.onnx_ml_pb2.TrainingInfoProto¶
- onnx.helper.make_tensor_type_proto(elem_type: int, shape: Optional[Sequence[Optional[Union[str, int]]]], shape_denotation: Optional[List[str]] = None) onnx.onnx_ml_pb2.TypeProto¶
Makes a Tensor TypeProto based on the data type and shape.
- onnx.helper.make_tensor_value_info(name: str, elem_type: int, shape: Optional[Sequence[Optional[Union[str, int]]]], doc_string: str = '', shape_denotation: Optional[List[str]] = None) onnx.onnx_ml_pb2.ValueInfoProto¶
Makes a ValueInfoProto based on the data type and shape.
- onnx.helper.make_value_info(name: str, type_proto: onnx.onnx_ml_pb2.TypeProto, doc_string: str = '') onnx.onnx_ml_pb2.ValueInfoProto¶
Makes a ValueInfoProto with the given type_proto.
getter¶
- onnx.helper.get_attribute_value(attr: onnx.onnx_ml_pb2.AttributeProto) Any¶
print¶
- onnx.helper.printable_attribute(attr: onnx.onnx_ml_pb2.AttributeProto, subgraphs: bool = False) Union[str, Tuple[str, List[onnx.onnx_ml_pb2.GraphProto]]]¶
- onnx.helper.printable_node(node: onnx.onnx_ml_pb2.NodeProto, prefix: str = '', subgraphs: bool = False) Union[str, Tuple[str, List[onnx.onnx_ml_pb2.GraphProto]]]¶
- onnx.helper.printable_tensor_proto(t: onnx.onnx_ml_pb2.TensorProto) str¶
- onnx.helper.printable_value_info(v: onnx.onnx_ml_pb2.ValueInfoProto) str¶