ParametersRecordยถ

class ParametersRecord(*args: Any, **kwargs: dict[str, Any])[์†Œ์Šค]ยถ

๊ธฐ๋ฐ˜ ํด๋ž˜์Šค: ArrayRecord

Deprecated class ParametersRecord, use ArrayRecord instead.

This class exists solely for backward compatibility with legacy code that previously used ParametersRecord. It has been renamed to ArrayRecord.

๊ฒฝ๊ณ 

ParametersRecord is deprecated and will be removed in a future release. Use ArrayRecord instead.

์˜ˆ์ œ

Legacy (deprecated) usage:

from flwr.common import ParametersRecord

record = ParametersRecord()

Updated usage:

from flwr.common import ArrayRecord

record = ArrayRecord()

๋ฉ”์†Œ๋“œ

clear()

copy()

Return a shallow copy of the dictionary.

count_bytes()

์ด ๊ฐ์ฒด์— ์ €์žฅ๋œ ๋ฐ”์ดํŠธ ์ˆ˜๋ฅผ ๋ฐ˜ํ™˜ํ•ฉ๋‹ˆ๋‹ค.

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„ ์ˆ˜ ์—†์œผ๋ฉด ์ฃผ์–ด์ง„ ๊ฒฝ์šฐ d๊ฐ€ ๋ฐ˜ํ™˜๋˜๊ณ , ๊ทธ๋ ‡์ง€ ์•Š์œผ๋ฉด KeyError๊ฐ€ ๋ฐœ์ƒํ•ฉ๋‹ˆ๋‹ค.

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

children

Return a dictionary of Arrays with their Object IDs as keys.

is_dirty

Check if the object is dirty after the last deflation.

object_id

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 ๊ฐ์ฒด์— ์ €์žฅ๋œ ๋ฐ”์ดํŠธ ์ˆ˜๋ฅผ ๋ฐ˜ํ™˜ํ•ฉ๋‹ˆ๋‹ค.

์—ญ์ง๋ ฌํ™”์— ํ•„์š”ํ•œ ์ง๋ ฌํ™”๋œ ๊ฐ์ฒด์˜ ๋ฉ”ํƒ€๋ฐ์ดํ„ฐ(์˜ˆ: NumPy ๋ฐฐ์—ด)์— ํ•ด๋‹นํ•˜๋Š” ์†Œ๋Ÿ‰์˜ ๋ฐ”์ดํŠธ๋„ ์ด ์นด์šดํŒ…์— ํฌํ•จ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

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.

๋งค๊ฐœ๋ณ€์ˆ˜:
  • 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.

๋ฐ˜ํ™˜:

The inflated ArrayRecord.

๋ฐ˜ํ™˜ ํ˜•์‹:

ArrayRecord

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„ ์ˆ˜ ์—†์œผ๋ฉด ์ฃผ์–ด์ง„ ๊ฒฝ์šฐ d๊ฐ€ ๋ฐ˜ํ™˜๋˜๊ณ , ๊ทธ๋ ‡์ง€ ์•Š์œผ๋ฉด KeyError๊ฐ€ ๋ฐœ์ƒํ•ฉ๋‹ˆ๋‹ค.

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