flytekit.extras.pytorch.PyTorchTensorTransformer

class flytekit.extras.pytorch.PyTorchTensorTransformer[source]

Methods

assert_type(t, v)
Parameters:
get_literal_type(t)

Converts the python type to a Flyte LiteralType

Parameters:

t (Type[T])

Return type:

LiteralType

guess_python_type(literal_type)[source]

Converts the Flyte LiteralType to a python object type.

Parameters:

literal_type (LiteralType)

Return type:

Type[Tensor]

to_html(ctx, python_val, expected_python_type)

Converts any python val (dataframe, int, float) to a html string, and it will be wrapped in the HTML div

Parameters:
Return type:

str

to_literal(ctx, python_val, python_type, expected)

Converts a given python_val to a Flyte Literal, assuming the given python_val matches the declared python_type. Implementers should refrain from using type(python_val) instead rely on the passed in python_type. If these do not match (or are not allowed) the Transformer implementer should raise an AssertionError, clearly stating what was the mismatch :param ctx: A FlyteContext, useful in accessing the filesystem and other attributes :param python_val: The actual value to be transformed :param python_type: The assumed type of the value (this matches the declared type on the function) :param expected: Expected Literal Type

Parameters:
Return type:

Literal

to_python_value(ctx, lv, expected_python_type)

Converts the given Literal to a Python Type. If the conversion cannot be done an AssertionError should be raised :param ctx: FlyteContext :param lv: The received literal Value :param expected_python_type: Expected native python type that should be returned

Parameters:
Return type:

T

Attributes

PYTORCH_FORMAT = 'PyTorchTensor'
name
python_type

This returns the python type

type_assertions_enabled

Indicates if the transformer wants type assertions to be enabled at the core type engine layer