flytekit.extras.pytorch.PyTorchCheckpoint¶

class flytekit.extras.pytorch.PyTorchCheckpoint(module=None, hyperparameters=None, optimizer=None)[source]¶

This class is helpful to save a checkpoint.

Methods

Parameters:

module (Module | None)
hyperparameters (Dict[str, Any] | NamedTuple | IsDataclass | None)
optimizer (Optimizer | None)

classmethod from_dict(kvs, *, infer_missing=False)¶

Parameters:: kvs (dict | list | str | int | float | bool | None)
Return type:: A

classmethod from_json(s, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw)¶

Parameters:: s (str | bytes | bytearray)
Return type:: A

classmethod schema(*, infer_missing=False, only=None, exclude=(), many=False, context=None, load_only=(), dump_only=(), partial=False, unknown=None)¶

Parameters:

infer_missing (bool)
many (bool)
partial (bool)

Return type:

SchemaF[A]

to_dict(encode_json=False)¶

Return type:: Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, indent=None, separators=None, default=None, sort_keys=False, **kw)¶

Parameters:

skipkeys (bool)
ensure_ascii (bool)
check_circular (bool)
allow_nan (bool)
indent (int | str | None)
separators (Tuple[str, str] | None)
default (Callable | None)
sort_keys (bool)

Return type:

str

Attributes

dataclass_json_config = None

hyperparameters: Dict[str, Any] | NamedTuple | IsDataclass | None = None

module: Module | None = None

optimizer: Optimizer | None = None