onnx の API リファレンス

onnx (onnx/onnx) の公開 API 88 件 —— クラス 14、関数 61、メソッド 13。実際のソースを静的解析して抽出した正確なシグネチャを掲載しています。

リポジトリ: onnx/onnx

種別	件数
クラス	14
関数	61
メソッド	13

API 一覧

methodonnx.backend.base.Backend.supports_device(device:str) -> bool

Checks whether the backend is compiled with particular device support.

classonnx.backend.base.DeviceType

Describes device type.

func

onnx.checker.check_model(model:onnx.ModelProto | str | bytes | os.PathLike, full_check:bool=False, skip_opset_compatibility_check:bool=False, check_custom_domain:bool=False) -> None

Check the consistency of a model.

funconnx.defs.get_function_ops() -> list[OpSchema]

Return operators defined as functions.

funconnx.defs.onnx_ml_opset_version() -> int

Return current opset for domain `ai.onnx.ml`.

funconnx.defs.onnx_opset_version() -> int

Return current opset for domain `ai.onnx`.

funconnx.defs.register_schema(schema:OpSchema) -> None

funconnx.external_data_helper.load_external_data_for_tensor(tensor:TensorProto, base_dir:str) -> None

Loads data from an external file for tensor.

funconnx.external_data_helper.uses_external_data(tensor:TensorProto) -> bool

Returns true if the tensor stores data in an external location.

funconnx.helper.get_all_tensor_dtypes() -> KeysView[int]

Get all tensor types from TensorProto.

funconnx.helper.make_attribute(key:str, value:Any, doc_string:str | None=None, attr_type:int | None=None) -> AttributeProto

Makes an AttributeProto based on the value type.

funconnx.helper.make_map(name:str, key_type:int, keys:list[Any], values:SequenceProto) -> MapProto

Make a Map with specified key-value pair arguments.

funconnx.helper.make_map_type_proto(key_type:int, value_type:TypeProto) -> TypeProto

Makes a map TypeProto.

func

onnx.helper.make_node(op_type:str, inputs:Sequence[str], outputs:Sequence[str], name:str | None=None, doc_string:str | None=None, domain:str | None=None, overload:str | None=None, **kwargs:Any) -> NodeProto

Construct a NodeProto.

funconnx.helper.make_operatorsetid(domain:str, version:int) -> OperatorSetIdProto

Construct an OperatorSetIdProto.

funconnx.helper.make_opsetid(domain:str, version:int) -> OperatorSetIdProto

Construct an OperatorSetIdProto.

func

onnx.helper.make_optional(name:str, elem_type:OptionalProto.DataType, value:google.protobuf.message.Message | None) -> OptionalProto

Make an Optional with specified value arguments.

funconnx.helper.make_optional_type_proto(inner_type_proto:TypeProto) -> TypeProto

Makes an optional TypeProto.

funconnx.helper.make_sequence(name:str, elem_type:SequenceProto.DataType, values:Sequence[Any]) -> SequenceProto

Make a Sequence with specified value arguments.

funconnx.helper.make_sequence_type_proto(inner_type_proto:TypeProto) -> TypeProto

Makes a sequence TypeProto.

func

onnx.helper.make_tensor(name:str, data_type:int, dims:Sequence[int], vals:Sequence[int | float] | bytes | np.ndarray, raw:bool=False) -> TensorProto

Make a TensorProto with specified arguments.

funconnx.helper.make_value_info(name:str, type_proto:TypeProto, doc_string:str='') -> ValueInfoProto

Makes a ValueInfoProto with the given type_proto.

funconnx.helper.np_dtype_to_tensor_dtype(np_dtype:np.dtype) -> TensorProto.DataType

Convert a numpy's dtype to corresponding tensor type.

funconnx.helper.printable_graph(graph:GraphProto, prefix:str='') -> str

Display a GraphProto as a string.

funconnx.helper.strip_doc_string(proto:google.protobuf.message.Message) -> None

Empties `doc_string` field on any nested protobuf messages

funconnx.helper.tensor_dtype_to_field(tensor_dtype:int) -> str

Convert a TensorProto's data_type to corresponding field name for storage.

funconnx.helper.tensor_dtype_to_np_dtype(tensor_dtype:int) -> np.dtype

Convert a TensorProto's data_type to corresponding numpy dtype.

funconnx.helper.tensor_dtype_to_string(tensor_dtype:int) -> str

Get the name of given TensorProto's data_type.

funconnx.inliner.inline_local_functions(model:onnx.ModelProto, convert_version:bool=False) -> onnx.ModelProto

Inline model-local functions in given model.

func

onnx.inliner.inline_selected_functions(model:onnx.ModelProto, function_ids:list[tuple[str, str]], exclude:bool=False, inline_schema_functions:bool=False) -> onnx.ModelProto

Inline selected functions in given model.

func

onnx.load_model(f:IO[bytes] | str | os.PathLike, format:_SupportedFormat | None=None, load_external_data:bool=True) -> ModelProto

Loads a serialized ModelProto into memory.

funconnx.load_tensor(f:IO[bytes] | str | os.PathLike, format:_SupportedFormat | None=None) -> TensorProto

Loads a serialized TensorProto into memory.

func

onnx.model_container.make_large_tensor_proto(location:str, tensor_name:str, tensor_type:int, shape:tuple[int, ...]) -> onnx.TensorProto

Create an external tensor.

funconnx.numpy_helper.create_random_int(input_shape:tuple[int], dtype:np.dtype, seed:int=1) -> np.ndarray

Create random integer array for backend/test/case/node.

funconnx.numpy_helper.from_dict(dict_:dict[Any, Any], name:str | None=None) -> onnx.MapProto

Converts a Python dictionary into a map def.

funconnx.numpy_helper.from_list(lst:list[Any], name:str | None=None, dtype:int | None=None) -> onnx.SequenceProto

Converts a list into a sequence def.

funconnx.numpy_helper.from_optional(opt:Any | None, name:str | None=None, dtype:int | None=None) -> onnx.OptionalProto

Converts an optional value into a Optional def.

funconnx.numpy_helper.saturate_cast(x:np.ndarray, dtype:np.dtype) -> np.ndarray

Saturate cast for numeric types.

funconnx.numpy_helper.to_array(tensor:onnx.TensorProto, base_dir:str='') -> np.ndarray

Converts a tensor def object to a numpy array.

funconnx.numpy_helper.to_dict(map_proto:onnx.MapProto) -> dict[Any, Any]

Converts a map def to a Python dictionary.

funconnx.numpy_helper.to_float8e8m0(x:np.ndarray, saturate:bool=True, round_mode:str='up') -> np.ndarray

Convert float32 NumPy array to float8e8m0 representation.

funconnx.numpy_helper.to_list(sequence:onnx.SequenceProto) -> list[Any]

Converts a sequence def to a Python list.

funconnx.numpy_helper.to_optional(optional:onnx.OptionalProto) -> Any | None

Converts an optional def to a Python optional.

funconnx.numpy_helper.tobytes_little_endian(array:np.ndarray) -> bytes

Converts an array into bytes in little endian byte order.

funconnx.parser.parse_function(function_text:str) -> onnx.FunctionProto

Parse a string to build a FunctionProto.

funconnx.parser.parse_graph(graph_text:str) -> onnx.GraphProto

Parse a string to build a GraphProto.

funconnx.parser.parse_model(model_text:str) -> onnx.ModelProto

Parse a string to build a ModelProto.

funconnx.parser.parse_node(node_text:str) -> onnx.NodeProto

Parse a string to build a NodeProto.

classonnx.reference.op_run.OpFunction

Runs a custom function.

classonnx.reference.op_run.OpRun

Ancestor to all operators in this subfolder.

method

onnx.reference.op_run.OpRun.create(n_inputs:int | None=None, n_outputs:int | None=None, verbose:int=0, **kwargs:Any) -> Any

Instantiates this class based on the given information.

methodonnx.reference.op_run.OpRun.domain() -> str

Returns node attribute `domain`.

methodonnx.reference.op_run.OpRun.eval(*n_outputs:int | None=None, *verbose:int=0, *args:list[Any], **kwargs:Any) -> Any

Evaluates this operator.

methodonnx.reference.op_run.OpRun.input() -> Sequence[str]

Returns node attribute `input`.

methodonnx.reference.op_run.OpRun.op_type() -> str

Returns node attribute `op_type`.

methodonnx.reference.op_run.OpRun.output() -> Sequence[str]

Returns node attribute `output`.

classonnx.reference.op_run.OpRunExpand

Class any operator to avoid must inherit from.

classonnx.reference.op_run.RuntimeImplementationError

Raised when no implementation was found for an operator.

classonnx.reference.op_run.RuntimeTypeError

Raised when a type of a variable is unexpected.

classonnx.reference.op_run.SparseTensor

Simple representation of a sparse tensor.

funconnx.reference.op_run.to_sparse_tensor(att:onnx.AttributeProto) -> SparseTensor

Hosts a sparse tensor.

classonnx.reference.ops._op.OpRunBinary

Ancestor to all binary operators in this subfolder.

classonnx.reference.ops._op.OpRunBinaryNum

Ancestor to all binary operators in this subfolder.

classonnx.reference.ops._op.OpRunReduceNumpy

Implements the reduce logic.

classonnx.reference.ops._op.OpRunUnary

Ancestor to all unary operators in this subfolder.

methodonnx.reference.ops._op.OpRunUnaryNum.run(x)

Calls method ``OpRunUnary.run``.

funconnx.reference.ops.aionnx_preview._op_list.load_op(domain:str, op_type:str, version:int | None, custom:Any=None) -> Any

Loads the implemented for a specified operator.

func

onnx.reference.ops.aionnx_preview_training._op_list.load_op(domain:str, op_type:str, version:int | None, custom:Any=None) -> Any

Loads the implemented for a specified operator.

funconnx.reference.ops.aionnxml._common_classifier.compute_softmax_zero(values:np.ndarray) -> np.ndarray

The function modifies the input inplace.

funconnx.reference.ops.aionnxml._common_classifier.softmax(values:np.ndarray) -> np.ndarray

Modifications in place.

funconnx.reference.ops.aionnxml._common_classifier.softmax_zero(values:np.ndarray) -> np.ndarray

Modifications in place.

funconnx.reference.ops.aionnxml._op_list.load_op(domain:str, op_type:str, version:int | None, custom:Any=None) -> Any

Loads the implemented for a specified operator.

methodonnx.reference.ops.aionnxml.op_normalizer.Normalizer.norm_l1(x)

L1 normalization

methodonnx.reference.ops.aionnxml.op_normalizer.Normalizer.norm_l2(x)

L2 normalization

methodonnx.reference.ops.aionnxml.op_normalizer.Normalizer.norm_max(x)

Max normalization

classonnx.reference.ops.aionnxml.op_svm_helper.SVMCommon

Base class for SVM.

classonnx.reference.ops.aionnxml.op_svm_regressor.SVMRegressor

The class only implements `POST_TRANSFORM="NONE"`.

methodonnx.reference.ops.aionnxml.op_tree_ensemble_helper.TreeEnsemble.leaf_index_tree(X:np.ndarray, tree_id:int) -> int

Computes the leaf index for one tree.

methodonnx.reference.ops.aionnxml.op_tree_ensemble_helper.TreeEnsemble.leave_index_tree(X:np.ndarray) -> np.ndarray

Computes the leaf index for all trees.

funconnx.reference.ops.experimental._op_list.load_op(domain:str, op_type:str, version:int | None, custom:Any=None) -> Any

Loads the implemented for a specified operator.

classonnx.reference.ops.op_blackman_window.BlackmanWindow

Blankman windowing function.

funconnx.reference.ops.op_matmul.numpy_matmul(a, b)

Implements a matmul product.

funconnx.reference.ops.op_scatter_elements.scatter_elements(data, indices, updates, axis=0, reduction=None)

Scatter elements.

funconnx.save_tensor(proto:TensorProto, f:IO[bytes] | str | os.PathLike, format:_SupportedFormat | None=None) -> None

Saves the TensorProto to the specified path.

func

onnx.shape_inference.infer_shapes(model:ModelProto | bytes, check_type:bool=False, strict_mode:bool=False, data_prop:bool=False) -> ModelProto

Apply shape inference to the provided ModelProto.

func

onnx.shape_inference.infer_shapes_path(model_path:str | os.PathLike, output_path:str | os.PathLike='', check_type:bool=False, strict_mode:bool=False, data_prop:bool=False) -> None

Take model path for shape_inference.

func

onnx.utils.extract_model(input_path:str | os.PathLike, output_path:str | os.PathLike, input_names:list[str], output_names:list[str], check_model:bool=True, infer_shapes:bool=True) -> None

Extracts sub-model from an ONNX model.

funconnx.version_converter.convert_version(model:ModelProto, target_version:int) -> ModelProto

Convert opset version of the ModelProto.

この情報について

掲載しているシグネチャは onnx/onnx の公開ソースコードを Python の ast モジュールで静的解析し、引数名・デフォルト値・型注釈・戻り値型をそのまま抽出したものです。実装コードは保存していません。詳しくは仕組みの解説をご覧ください。

収録ライブラリ一覧（全 805 件）へ戻る