ParametersRecordยถ
- class ParametersRecord(*args: Any, **kwargs: dict[str, Any])[์์ค]ยถ
๊ธฐ๋ฐ ํด๋์ค:
ArrayRecordDeprecated class
ParametersRecord, useArrayRecordinstead.This class exists solely for backward compatibility with legacy code that previously used
ParametersRecord. It has been renamed toArrayRecord.๊ฒฝ๊ณ
ParametersRecordis deprecated and will be removed in a future release. UseArrayRecordinstead.์์
Legacy (deprecated) usage:
from flwr.common import ParametersRecord record = ParametersRecord()
Updated usage:
from flwr.common import ArrayRecord record = ArrayRecord()
๋ฉ์๋
clear()copy()Return a shallow copy of the dictionary.
์ด ๊ฐ์ฒด์ ์ ์ฅ๋ ๋ฐ์ดํธ ์๋ฅผ ๋ฐํํฉ๋๋ค.
deflate()Deflate the ArrayRecord.
from_array_dict(array_dict, *[, keep_input])Create ArrayRecord from a dictionary of
Array.from_numpy_ndarrays(ndarrays, *[, keep_input])Create ArrayRecord from a list of NumPy
ndarray.from_torch_state_dict(state_dict, *[, ...])Create ArrayRecord from PyTorch
state_dict.get(k[,d])inflate(object_content[, children])Inflate an ArrayRecord from bytes.
items()keys()pop(k[,d])ํค๋ฅผ ์ฐพ์ ์ ์์ผ๋ฉด ์ฃผ์ด์ง ๊ฒฝ์ฐ d๊ฐ ๋ฐํ๋๊ณ , ๊ทธ๋ ์ง ์์ผ๋ฉด KeyError๊ฐ ๋ฐ์ํฉ๋๋ค.
popitem()as a 2-tuple; but raise KeyError if D is empty.
setdefault(k[,d])to_numpy_ndarrays(*[, keep_input])Return the ArrayRecord as a list of NumPy
ndarray.to_torch_state_dict(*[, keep_input])Return the ArrayRecord as a PyTorch
state_dict.update([E, ]**F)If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
values()์์ฑ
Return a dictionary of Arrays with their Object IDs as keys.
Check if the object is dirty after the last deflation.
Get object ID.
- property children: dict[str, InflatableObject]ยถ
Return a dictionary of Arrays with their Object IDs as keys.
- clear() None. Remove all items from D.ยถ
- copy() Selfยถ
Return a shallow copy of the dictionary.
- count_bytes() intยถ
์ด ๊ฐ์ฒด์ ์ ์ฅ๋ ๋ฐ์ดํธ ์๋ฅผ ๋ฐํํฉ๋๋ค.
์ญ์ง๋ ฌํ์ ํ์ํ ์ง๋ ฌํ๋ ๊ฐ์ฒด์ ๋ฉํ๋ฐ์ดํฐ(์: NumPy ๋ฐฐ์ด)์ ํด๋นํ๋ ์๋์ ๋ฐ์ดํธ๋ ์ด ์นด์ดํ ์ ํฌํจ๋ ์ ์์ต๋๋ค.
- deflate() bytesยถ
Deflate the ArrayRecord.
- classmethod from_array_dict(array_dict: dict[str, Array], *, keep_input: bool = True) ArrayRecordยถ
Create ArrayRecord from a dictionary of
Array.
- classmethod from_numpy_ndarrays(ndarrays: list[ndarray[Any, dtype[Any]]], *, keep_input: bool = True) ArrayRecordยถ
Create ArrayRecord from a list of NumPy
ndarray.
- classmethod from_torch_state_dict(state_dict: dict[str, torch.Tensor], *, keep_input: bool = True) ArrayRecordยถ
Create ArrayRecord from PyTorch
state_dict.
- get(k[, d]) D[k] if k in D, else d. d defaults to None.ยถ
- classmethod inflate(object_content: bytes, children: dict[str, InflatableObject] | None = None) ArrayRecordยถ
Inflate an ArrayRecord from bytes.
- ๋งค๊ฐ๋ณ์:
object_content (bytes) โ The deflated object content of the ArrayRecord.
children (Optional[dict[str, InflatableObject]] (default: None)) โ Dictionary of children InflatableObjects mapped to their Object IDs. These children enable the full inflation of the ArrayRecord.
- ๋ฐํ:
The inflated ArrayRecord.
- ๋ฐํ ํ์:
- property is_dirty: boolยถ
Check if the object is dirty after the last deflation.
- items() a set-like object providing a view on D's items.ยถ
- keys() a set-like object providing a view on D's keys.ยถ
- property object_id: strยถ
Get object ID.
- pop(k[, d]) v, remove specified key and return the corresponding value.ยถ
ํค๋ฅผ ์ฐพ์ ์ ์์ผ๋ฉด ์ฃผ์ด์ง ๊ฒฝ์ฐ d๊ฐ ๋ฐํ๋๊ณ , ๊ทธ๋ ์ง ์์ผ๋ฉด KeyError๊ฐ ๋ฐ์ํฉ๋๋ค.
- popitem() (k, v), remove and return some (key, value) pairยถ
as a 2-tuple; but raise KeyError if D is empty.
- setdefault(k[, d]) D.get(k,d), also set D[k]=d if k not in Dยถ
- to_numpy_ndarrays(*, keep_input: bool = True) list[ndarray[Any, dtype[Any]]]ยถ
Return the ArrayRecord as a list of NumPy
ndarray.
- to_torch_state_dict(*, keep_input: bool = True) OrderedDict[str, torch.Tensor]ยถ
Return the ArrayRecord as a PyTorch
state_dict.
- update([E, ]**F) None. Update D from mapping/iterable E and F.ยถ
If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
- values() an object providing a view on D's values.ยถ