onnx.numpy_helper#

from_array(arr[, name])

Converts a numpy array to a tensor def.

from_dict(dict[, name])

Converts a Python dictionary into a map def.

from_list(lst[, name, dtype])

Converts a list into a sequence def.

from_optional(opt[, name, dtype])

Converts an optional value into a Optional def.

to_array(tensor[, base_dir])

Converts a tensor def object to a numpy array.

to_dict(map)

Converts a map def to a Python dictionary.

to_list(sequence)

Converts a sequence def to a Python list.

to_optional(optional)

Converts an optional def to a Python optional.

array#

onnx.numpy_helper.from_array(arr: ndarray, name: Optional[str] = None) → TensorProto[source]#

Converts a numpy array to a tensor def.

Parameters:

  • arr – a numpy array.

  • name – (optional) the name of the tensor.

Returns:

the converted tensor def.

Return type:

TensorProto

onnx.numpy_helper.to_array(tensor: TensorProto, base_dir: str = '') → ndarray[source]#

Converts a tensor def object to a numpy array.

Parameters:

  • tensor – a TensorProto object.

  • base_dir – if external tensor exists, base_dir can help to find the path to it

Returns:

the converted array.

Return type:

arr

sequence#

onnx.numpy_helper.to_list(sequence: SequenceProto) → List[Any][source]#

Converts a sequence def to a Python list.

Parameters:

sequence – a SequenceProto object.

Returns:

the converted list.

Return type:

list

onnx.numpy_helper.from_list(lst: List[Any], name: Optional[str] = None, dtype: Optional[int] = None) → SequenceProto[source]#

Converts a list into a sequence def.

Parameters:

  • lst – a Python list

  • name – (optional) the name of the sequence.

  • dtype – (optional) type of element in the input list, used for specifying sequence values when converting an empty list.

Returns:

the converted sequence def.

Return type:

SequenceProto

dictionary#

onnx.numpy_helper.to_dict(map: MapProto) → Dict[Any, Any][source]#

Converts a map def to a Python dictionary.

Parameters:

map – a MapProto object.

Returns:

the converted dictionary.

Return type:

dict

onnx.numpy_helper.from_dict(dict: Dict[Any, Any], name: Optional[str] = None) → MapProto[source]#

Converts a Python dictionary into a map def.

Parameters:

  • dict – Python dictionary

  • name – (optional) the name of the map.

Returns:

the converted map def.

Return type:

MapProto

optional#

onnx.numpy_helper.to_optional(optional: OptionalProto) → Optional[Any][source]#

Converts an optional def to a Python optional.

Parameters:

optional – an OptionalProto object.

Returns:

the converted optional.

Return type:

opt

onnx.numpy_helper.from_optional(opt: Optional[Any], name: Optional[str] = None, dtype: Optional[int] = None) → OptionalProto[source]#

Converts an optional value into a Optional def.

Parameters:

  • opt – a Python optional

  • name – (optional) the name of the optional.

  • dtype – (optional) type of element in the input, used for specifying optional values when converting empty none. dtype must be a valid OptionalProto.DataType value

Returns:

the converted optional def.

Return type:

optional

tools#

onnx.numpy_helper.convert_endian(tensor: TensorProto) → None[source]#

Call to convert endianess of raw data in tensor.

Parameters:

tensor (TensorProto) – TensorProto to be converted.

onnx.numpy_helper.combine_pairs_to_complex(fa: Sequence[int]) → List[complex][source]#