experimental_experiment.helpers

experimental_experiment.helpers.get_onnx_signature(model: ModelProto) Tuple[Tuple[str, Any], ...][source]

Produces a tuple of tuples correspinding to the signatures.

Parameters:

model – model

Returns:

signature

experimental_experiment.helpers.make_hash(obj: Any) str[source]

Returns a simple hash of id(obj) in four letter.

experimental_experiment.helpers.pretty_onnx(onx: FunctionProto | GraphProto | ModelProto | str) str[source]

Displays an onnx prot in a better way.

experimental_experiment.helpers.string_sig(f: Callable, kwargs: Dict[str, Any] | None = None) str[source]

Displays the signature of a functions if the default if the given value is different from

experimental_experiment.helpers.string_signature(sig: Any) str[source]

Displays the signature of a functions.

experimental_experiment.helpers.string_type(obj: Any, with_shape: bool = False, with_min_max: bool = False) str[source]

Displays the types of an object as a string.

Parameters:
  • obj – any

  • with_shape – displays shapes as well

  • with_min_max – displays information about the values

Returns:

str

<<<

from experimental_experiment.helpers import string_type

print(string_type((1, ["r", 6.6])))

>>>

    (int,#2[str,float])
experimental_experiment.helpers.tensor_dtype_to_np_dtype(tensor_dtype: int) dtype[source]

Convert a TensorProto’s data_type to corresponding numpy dtype. It can be used while making tensor.

Parameters:

tensor_dtype – TensorProto’s data_type

Returns:

numpy’s data_type