From 8846f56b986ff5d033803438034d3173ea062d6f Mon Sep 17 00:00:00 2001
From: Paul Andrey <paul.andrey@inria.fr>
Date: Fri, 26 Jul 2024 10:52:55 +0200
Subject: [PATCH] Remove deprecated features planned for v2.6 removal.
---
declearn/aggregator/_api.py | 43 -----
declearn/aggregator/_avg.py | 87 +---------
declearn/aggregator/_gma.py | 36 +----
declearn/communication/__init__.py | 8 -
declearn/communication/api/_client.py | 17 --
declearn/communication/messaging/__init__.py | 57 -------
declearn/communication/messaging/_messages.py | 153 ------------------
declearn/dataset/__init__.py | 4 +-
declearn/dataset/_base.py | 42 +----
declearn/main/_client.py | 10 +-
declearn/metrics/_api.py | 41 -----
declearn/metrics/_wrapper.py | 44 -----
declearn/optimizer/modules/_scaffold.py | 19 +--
docs/release-notes/v2.6.0.md | 26 +++
test/aggregator/test_aggregator.py | 28 ----
test/main/test_main_client.py | 24 ---
test/metrics/metric_testing.py | 26 ---
test/metrics/test_metricset.py | 14 +-
18 files changed, 36 insertions(+), 643 deletions(-)
delete mode 100644 declearn/communication/messaging/__init__.py
delete mode 100644 declearn/communication/messaging/_messages.py
diff --git a/declearn/aggregator/_api.py b/declearn/aggregator/_api.py
index 468b837b..56813d50 100644
--- a/declearn/aggregator/_api.py
+++ b/declearn/aggregator/_api.py
@@ -19,7 +19,6 @@
import abc
import dataclasses
-import warnings
from typing import Any, ClassVar, Dict, Generic, Type, TypeVar, Union
from typing_extensions import Self # future: import from typing (py >=3.11)
@@ -185,48 +184,6 @@ class Aggregator(Generic[ModelUpdatesT], metaclass=abc.ABCMeta):
"""Instantiate an Aggregator from its configuration dict."""
return cls(**config)
- def aggregate(
- self,
- updates: Dict[str, Vector[T]],
- n_steps: Dict[str, int], # revise: abstract~generalize kwargs use
- ) -> Vector[T]:
- """DEPRECATED - Aggregate input vectors into a single one.
-
- Parameters
- ----------
- updates: dict[str, Vector]
- Client-wise updates, as a dictionary with clients' names as
- string keys and updates as Vector values.
- n_steps: dict[str, int]
- Client-wise number of local training steps performed during
- the training round having produced the updates.
-
- Returns
- -------
- gradients: Vector
- Aggregated updates, as a Vector - treated as gradients by
- the server-side optimizer.
-
- Raises
- ------
- TypeError
- If the input `updates` are an empty dict.
- """
- warnings.warn(
- "'Aggregator.aggregate' was deprecated in DecLearn v2.4 in favor "
- "of new API methods. It will be removed in DecLearn v2.6 and/or "
- "v3.0.",
- DeprecationWarning,
- )
- if not updates:
- raise TypeError("'Aggregator.aggregate' received an empty dict.")
- partials = [
- self.prepare_for_sharing(updates[client], n_steps[client])
- for client in updates
- ]
- aggregated = sum(partials[1:], start=partials[0])
- return self.finalize_updates(aggregated)
-
def list_aggregators() -> Dict[str, Type[Aggregator]]:
"""Return a mapping of registered Aggregator subclasses.
diff --git a/declearn/aggregator/_avg.py b/declearn/aggregator/_avg.py
index 05dfa5b4..333b4b9d 100644
--- a/declearn/aggregator/_avg.py
+++ b/declearn/aggregator/_avg.py
@@ -17,8 +17,7 @@
"""FedAvg-like mean-aggregation class."""
-import warnings
-from typing import Any, Dict, Optional
+from typing import Any, Dict
from declearn.aggregator._api import Aggregator, ModelUpdates
@@ -44,7 +43,6 @@ class AveragingAggregator(Aggregator[ModelUpdates]):
def __init__(
self,
steps_weighted: bool = True,
- client_weights: Optional[Dict[str, float]] = None,
) -> None:
"""Instantiate an averaging aggregator.
@@ -53,37 +51,14 @@ class AveragingAggregator(Aggregator[ModelUpdates]):
steps_weighted:
Whether to conduct a weighted averaging of local model
updates based on local numbers of training steps.
- client_weights:
- DEPRECATED - this argument no longer affects computations,
- save when using the deprecated 'aggregate' method.
- Optional dict of client-wise base weights to use.
- If None, homogeneous base weights are used.
-
- Notes
- -----
- * One may specify `client_weights` and use `steps_weighted=True`.
- In that case, the product of the client's base weight and their
- number of training steps taken will be used (and unit-normed).
- * One may use incomplete `client_weights`. In that case, unknown-
- clients' base weights will be set to 1.
"""
self.steps_weighted = steps_weighted
- self.client_weights = client_weights or {}
- if client_weights: # pragma: no cover
- warnings.warn(
- f"'client_weights' argument to '{self.__class__.__name__}' was"
- " deprecated in DecLearn v2.4 and is no longer used, saved by"
- " the deprecated 'aggregate' method. It will be removed in"
- " DecLearn v2.6 and/or v3.0.",
- DeprecationWarning,
- )
def get_config(
self,
) -> Dict[str, Any]:
return {
"steps_weighted": self.steps_weighted,
- "client_weights": self.client_weights,
}
def prepare_for_sharing(
@@ -103,63 +78,3 @@ class AveragingAggregator(Aggregator[ModelUpdates]):
updates: ModelUpdates,
) -> Vector:
return updates.updates / updates.weights
-
- def aggregate(
- self,
- updates: Dict[str, Vector],
- n_steps: Dict[str, int],
- ) -> Vector:
- # Make use of 'client_weights' as part of this DEPRECATED method.
- with warnings.catch_warnings():
- warnings.simplefilter(action="ignore", category=DeprecationWarning)
- weights = self.compute_client_weights(updates, n_steps)
- steps_weighted = self.steps_weighted
- try:
- self.steps_weighted = True
- return super().aggregate(updates, weights) # type: ignore
- finally:
- self.steps_weighted = steps_weighted
-
- def compute_client_weights(
- self,
- updates: Dict[str, Vector],
- n_steps: Dict[str, int],
- ) -> Dict[str, float]:
- """Compute weights to use when averaging a given set of updates.
-
- This method is DEPRECATED as of DecLearn v2.4.
- It will be removed in DecLearn 2.6 and/or 3.0.
-
- Parameters
- ----------
- updates: dict[str, Vector]
- Client-wise updates, as a dictionary with clients' names as
- string keys and updates as Vector values.
- n_steps: dict[str, int]
- Client-wise number of local training steps performed during
- the training round having produced the updates.
-
- Returns
- -------
- weights: dict[str, float]
- Client-wise updates-averaging weights, suited to the input
- parameters and normalized so that they sum to 1.
- """
- warnings.warn(
- f"'{self.__class__.__name__}.compute_client_weights' was"
- " deprecated in DecLearn v2.4. It will be removed in DecLearn"
- " v2.6 and/or v3.0.",
- DeprecationWarning,
- )
- if self.steps_weighted:
- weights = {
- client: steps * self.client_weights.get(client, 1.0)
- for client, steps in n_steps.items()
- }
- else:
- weights = {
- client: self.client_weights.get(client, 1.0)
- for client in updates
- }
- total = sum(weights.values())
- return {client: weight / total for client, weight in weights.items()}
diff --git a/declearn/aggregator/_gma.py b/declearn/aggregator/_gma.py
index dfdcc1d7..4832d4a6 100644
--- a/declearn/aggregator/_gma.py
+++ b/declearn/aggregator/_gma.py
@@ -18,7 +18,6 @@
"""Gradient Masked Averaging aggregation class."""
import dataclasses
-import warnings
from typing import Any, Dict, Optional, Tuple
from typing_extensions import Self # future: import from typing (py >=3.11)
@@ -99,7 +98,6 @@ class GradientMaskedAveraging(Aggregator[GMAModelUpdates]):
self,
threshold: float = 1.0,
steps_weighted: bool = True,
- client_weights: Optional[Dict[str, float]] = None,
) -> None:
"""Instantiate a gradient masked averaging aggregator.
@@ -111,20 +109,9 @@ class GradientMaskedAveraging(Aggregator[GMAModelUpdates]):
steps_weighted: bool, default=True
Whether to weight updates based on the number of optimization
steps taken by the clients (relative to one another).
- client_weights: dict[str, float] or None, default=None
- Optional dict of client-wise base weights to use.
- If None, homogeneous base weights are used.
-
- Notes
- -----
- * One may specify `client_weights` and use `steps_weighted=True`.
- In that case, the product of the client's base weight and their
- number of training steps taken will be used (and unit-normed).
- * One may use incomplete `client_weights`. In that case, unknown-
- clients' base weights will be set to 1.
"""
self.threshold = threshold
- self._avg = AveragingAggregator(steps_weighted, client_weights)
+ self._avg = AveragingAggregator(steps_weighted)
def get_config(
self,
@@ -162,24 +149,3 @@ class GradientMaskedAveraging(Aggregator[GMAModelUpdates]):
scores = (1 - clip) * scores + clip # s = 1 if s > t else s
# Correct outputs' magnitude and return them.
return values * scores
-
- def compute_client_weights( # pragma: no cover
- self,
- updates: Dict[str, Vector],
- n_steps: Dict[str, int],
- ) -> Dict[str, float]:
- """Compute weights to use when averaging a given set of updates.
-
- This method is DEPRECATED as of DecLearn v2.4.
- It will be removed in DecLearn 2.6 and/or 3.0.
- """
- # pylint: disable=duplicate-code
- warnings.warn(
- f"'{self.__class__.__name__}.compute_client_weights' was"
- " deprecated in DecLearn v2.4. It will be removed in DecLearn"
- " v2.6 and/or v3.0.",
- DeprecationWarning,
- )
- with warnings.catch_warnings():
- warnings.simplefilter(action="ignore", category=DeprecationWarning)
- return self._avg.compute_client_weights(updates, n_steps)
diff --git a/declearn/communication/__init__.py b/declearn/communication/__init__.py
index 93a508e0..5f15e89b 100644
--- a/declearn/communication/__init__.py
+++ b/declearn/communication/__init__.py
@@ -28,7 +28,6 @@ This module contains the following core submodules:
* [utils][declearn.communication.utils]:
Utils related to network communication endpoints' setup and usage.
-
It re-exports publicly from `utils` the following elements:
* [build_client][declearn.communication.build_client]:
@@ -52,10 +51,6 @@ the associated third-party dependencies are available:
* [websockets][declearn.communication.websockets]:
WebSockets-based network communication endpoints.
Requires the `websockets` third-party package.
-
-Additionnally, for retro-compatibility purposes, it exports the DEPRECATED
-[messaging][declearn.communication.messaging] submodule, that should no
-longer be used, as its contents were re-dispatched elsewhere in DecLearn.
"""
# Messaging API and base tools:
@@ -79,6 +74,3 @@ try:
from . import websockets
except ImportError: # pragma: no cover
_INSTALLABLE_BACKENDS["websockets"] = ("websockets",)
-
-# DEPRECATED submodule, kept for retro-compatibility until 2.6 and/or 3.0.
-from . import messaging
diff --git a/declearn/communication/api/_client.py b/declearn/communication/api/_client.py
index fa5f1648..2482d315 100644
--- a/declearn/communication/api/_client.py
+++ b/declearn/communication/api/_client.py
@@ -339,20 +339,3 @@ class NetworkClient(metaclass=abc.ABCMeta):
)
self.logger.critical(error)
raise TypeError(error)
-
- async def check_message(
- self,
- timeout: Optional[float] = None,
- ) -> SerializedMessage:
- """Await a message from the server, with optional timeout.
-
- This method is DEPRECATED in favor of the `recv_message` one.
- It acts as an alias and will be removed in v2.6 and/or v3.0.
- """
- warnings.warn(
- "'NetworkServer.check_message' was renamed as 'recv_message' "
- "in DecLearn 2.4. It now acts as an alias, but will be removed "
- "in version 2.6 and/or 3.0.",
- DeprecationWarning,
- )
- return await self.recv_message(timeout)
diff --git a/declearn/communication/messaging/__init__.py b/declearn/communication/messaging/__init__.py
deleted file mode 100644
index 510fe6d6..00000000
--- a/declearn/communication/messaging/__init__.py
+++ /dev/null
@@ -1,57 +0,0 @@
-# coding: utf-8
-
-# Copyright 2023 Inria (Institut National de Recherche en Informatique
-# et Automatique)
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""DEPRECATED submodule defining messaging containers and flags.
-
-This submodule was deprecated in DecLearn 2.4 in favor of `declearn.messaging`.
-It should no longer be used, and will be removed in 2.6 and/or 3.0.
-
-Most of its contents are re-exports of non-deprecated classes and functions
-from 'declearn.messaging'. Others will trigger deprecation warnings (and may
-cause failures) if used.
-
-Deprecated classes uniquely-defined here are:
-
-* [Empty][declearn.communication.messaging.Empty]
-* [GetMessageRequest][declearn.communication.messaging.GetMessageRequest]
-* [JoinReply][declearn.communication.messaging.JoinReply]
-* [JoinRequest][declearn.communication.messaging.JoinRequest]
-
-The `flags` submodule is also re-exported, but should preferably be imported
-as `declearn.communication.api.backend.flags`.
-"""
-
-from declearn.communication.api.backend import flags
-
-from ._messages import (
- CancelTraining,
- Empty,
- Error,
- GenericMessage,
- GetMessageRequest,
- EvaluationReply,
- EvaluationRequest,
- InitRequest,
- JoinReply,
- JoinRequest,
- Message,
- PrivacyRequest,
- StopTraining,
- TrainReply,
- TrainRequest,
- parse_message_from_string,
-)
diff --git a/declearn/communication/messaging/_messages.py b/declearn/communication/messaging/_messages.py
deleted file mode 100644
index f81574c2..00000000
--- a/declearn/communication/messaging/_messages.py
+++ /dev/null
@@ -1,153 +0,0 @@
-# coding: utf-8
-
-# Copyright 2023 Inria (Institut National de Recherche en Informatique
-# et Automatique)
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Dataclasses defining messages used in declearn communications."""
-
-import abc
-import dataclasses
-import warnings
-from typing import Any, Dict, Optional
-
-
-from declearn.messaging import (
- CancelTraining,
- Error,
- EvaluationReply,
- EvaluationRequest,
- GenericMessage,
- InitRequest,
- Message,
- PrivacyRequest,
- SerializedMessage,
- StopTraining,
- TrainReply,
- TrainRequest,
-)
-
-
-__all__ = [
- "CancelTraining",
- "Empty",
- "Error",
- "EvaluationReply",
- "EvaluationRequest",
- "GenericMessage",
- "GetMessageRequest",
- "InitRequest",
- "JoinReply",
- "JoinRequest",
- "Message",
- "PrivacyRequest",
- "StopTraining",
- "TrainReply",
- "TrainRequest",
- "parse_message_from_string",
-]
-
-
-@dataclasses.dataclass
-class DeprecatedMessage(Message, register=False, metaclass=abc.ABCMeta):
- """DEPRECATED Message subtype."""
-
- def __post_init__(
- self,
- ) -> None:
- warnings.warn(
- f"'{self.__class__.__name__}' was deprecated in DecLearn v2.4. "
- "It should no longer be used and may cause failures. It will be "
- "removed in DecLearn v2.6 and/or v3.0",
- DeprecationWarning,
- )
-
-
-@dataclasses.dataclass
-class Empty(DeprecatedMessage):
- """DEPRECATED empty message class."""
-
- typekey = "empty"
-
-
-@dataclasses.dataclass
-class GetMessageRequest(DeprecatedMessage):
- """DEPRECATED message-retrieval query message class."""
-
- typekey = "get_message"
-
- timeout: Optional[int] = None
-
-
-@dataclasses.dataclass
-class JoinRequest(DeprecatedMessage):
- """DEPRECATED process joining query message class."""
-
- typekey = "join_request"
-
- name: str
- data_info: Dict[str, Any]
- version: Optional[str] = None
-
-
-@dataclasses.dataclass
-class JoinReply(DeprecatedMessage):
- """DEPRECATED process joining reply message class."""
-
- typekey = "join_reply"
-
- accept: bool
- flag: str
-
-
-def parse_message_from_string(
- string: str,
-) -> Message:
- """DEPRECATED - Instantiate a Message from its serialized string.
-
- This function was DEPRECATED in DecLearn 2.4 and will be removed
- in v2.6 and/or v3.0. Use the `declearn.messaging.SerializedMessage`
- API to parse serialized message strings.
-
- Parameters
- ----------
- string:
- Serialized string dump of the message.
-
- Returns
- -------
- message:
- Message instance recovered from the input string.
-
- Raises
- ------
- KeyError
- If the string's typekey does not match any supported Message
- subclass.
- TypeError
- If the string cannot be parsed to identify a message typekey.
- ValueError
- If the serialized data fails to be properly decoded.
- """
- warnings.warn(
- "'parse_message_from_string' was deprecated in DecLearn 2.4, in "
- "favor of using 'declearn.messaging.SerializedMessage' to parse "
- "and deserialize 'Message' instances from strings. It will be "
- "removed in DecLearn version 2.6 and/or 3.0.",
- DeprecationWarning,
- )
- serialized = SerializedMessage.from_message_string(
- string
- ) # type: SerializedMessage[Any]
- return serialized.deserialize()
diff --git a/declearn/dataset/__init__.py b/declearn/dataset/__init__.py
index 7436e1ce..d885c587 100644
--- a/declearn/dataset/__init__.py
+++ b/declearn/dataset/__init__.py
@@ -29,8 +29,6 @@ API tools
Abstract base class defining an API to access training or testing data.
* [DataSpec][declearn.dataset.DataSpecs]:
Dataclass to wrap a dataset's metadata.
-* [load_dataset_from_json][declearn.dataset.load_dataset_from_json]
- DEPRECATED Utility function to parse a JSON into a dataset object.
Dataset subclasses
------------------
@@ -67,6 +65,6 @@ Utility entry-point
from . import utils
from . import examples
-from ._base import Dataset, DataSpecs, load_dataset_from_json
+from ._base import Dataset, DataSpecs
from ._inmemory import InMemoryDataset
from ._split_data import split_data
diff --git a/declearn/dataset/_base.py b/declearn/dataset/_base.py
index c0f3bbe7..64cf1c83 100644
--- a/declearn/dataset/_base.py
+++ b/declearn/dataset/_base.py
@@ -19,11 +19,10 @@
import abc
import dataclasses
-import warnings
from typing import Any, Iterator, List, Optional, Set, Tuple, Union
from declearn.typing import Batch
-from declearn.utils import access_registered, create_types_registry, json_load
+from declearn.utils import create_types_registry
__all__ = [
"DataSpecs",
@@ -109,42 +108,3 @@ class Dataset(metaclass=abc.ABCMeta):
Optional weights associated with the samples, that are
typically used to balance a model's loss or metrics.
"""
-
-
-def load_dataset_from_json(path: str) -> Dataset: # pragma: no cover
- """DEPRECATED Instantiate a dataset based on a JSON dump file.
-
- Parameters
- ----------
- path: str
- Path to a JSON file output by the `save_to_json`
- method of the Dataset that is being reloaded.
- The actual type of dataset should be specified
- under the "name" field of that file.
-
- Returns
- -------
- dataset: Dataset
- Dataset (subclass) instance, reloaded from JSON.
-
- Raises
- ------
- NotImplementedError
- If the target `Dataset` does not implement a `load_from_json`
- method (which was removed from the API in DecLearn 2.3.0).
- """
- warnings.warn(
- "'load_dataset_from_json' was deprecated in Declearn 2.4.0, after"
- "'Dataset.load_from_json' was removed from the API in v2.3.0. It "
- "may raise a 'NotImplementedError', and will be removed in DecLearn "
- "2.6 and/or 3.0.",
- category=DeprecationWarning,
- stacklevel=2,
- )
- dump = json_load(path)
- cls = access_registered(dump["name"], group="Dataset")
- if not hasattr(cls, "load_from_json"):
- raise NotImplementedError(
- f"Dataset class '{cls}' does not implement 'load_from_json'."
- )
- return cls.load_from_json(path)
diff --git a/declearn/main/_client.py b/declearn/main/_client.py
index 506046e6..0b03c36a 100644
--- a/declearn/main/_client.py
+++ b/declearn/main/_client.py
@@ -32,7 +32,7 @@ from declearn.communication.utils import (
NetworkClientConfig,
verify_server_message_validity,
)
-from declearn.dataset import Dataset, load_dataset_from_json
+from declearn.dataset import Dataset
from declearn.fairness.api import FairnessControllerClient
from declearn.main.utils import Checkpointer
from declearn.messaging import Message, SerializedMessage
@@ -116,16 +116,12 @@ class FederatedClient:
if replace_netwk_logger:
self.netwk.logger = self.logger
# Assign the wrapped training dataset.
- if isinstance(train_data, str):
- train_data = load_dataset_from_json(train_data)
if not isinstance(train_data, Dataset):
- raise TypeError("'train_data' should be a Dataset or path to one.")
+ raise TypeError("'train_data' should be a Dataset.")
self.train_data = train_data
# Assign the wrapped validation dataset (if any).
- if isinstance(valid_data, str):
- valid_data = load_dataset_from_json(valid_data)
if not (valid_data is None or isinstance(valid_data, Dataset)):
- raise TypeError("'valid_data' should be a Dataset or path to one.")
+ raise TypeError("'valid_data' should be a Dataset.")
self.valid_data = valid_data
# Assign an optional checkpointer.
if checkpoint is not None:
diff --git a/declearn/metrics/_api.py b/declearn/metrics/_api.py
index 04405777..46a53d50 100644
--- a/declearn/metrics/_api.py
+++ b/declearn/metrics/_api.py
@@ -18,7 +18,6 @@
"""Iterative and federative evaluation metrics base class."""
import abc
-import warnings
from copy import deepcopy
from typing import Any, ClassVar, Dict, Generic, Optional, Type, TypeVar, Union
@@ -248,46 +247,6 @@ class Metric(Generic[MetricStateT], metaclass=abc.ABCMeta):
)
self._states = deepcopy(states) # type: ignore
- def agg_states(
- self,
- states: MetricStateT,
- ) -> None:
- """Aggregate provided state variables into self ones.
-
- This method is DEPRECATED as of DecLearn v2.4, in favor of
- merely aggregating `MetricState` instances, using either
- their `aggregate` method or the overloaded `+` operator.
- It will be removed in DecLearn 2.6 and/or 3.0.
-
- This method is designed to aggregate results from multiple
- similar metrics objects into a single one before computing
- its results.
-
- Parameters
- ----------
- states:
- `MetricState` emitted by another instance of this class
- via its `get_states` method.
-
- Raises
- ------
- TypeError
- If `states` is of improper type.
- """
- warnings.warn(
- "'Metric.agg_states' was deprecated in DecLearn v2.4, in favor "
- "of aggregating 'MetricState' instances directly, and setting "
- "final aggregated states using 'Metric.set_state'. It will be "
- "removed in DecLearn 2.6 and/or 3.0.",
- DeprecationWarning,
- )
- if not isinstance(states, self.state_cls):
- raise TypeError(
- f"'{self.__class__.__name__}.set_states' expected "
- f"'{self.state_cls}' inputs, got '{type(states)}'."
- )
- self.set_states(self._states + states)
-
def __init_subclass__(
cls,
register: bool = True,
diff --git a/declearn/metrics/_wrapper.py b/declearn/metrics/_wrapper.py
index cbb5cee2..9e7a1709 100644
--- a/declearn/metrics/_wrapper.py
+++ b/declearn/metrics/_wrapper.py
@@ -17,7 +17,6 @@
"""Wrapper for an ensemble of Metric objects."""
-import warnings
from typing import Any, Dict, List, Optional, Sequence, Tuple, Union
import numpy as np
@@ -215,49 +214,6 @@ class MetricSet:
if metric.name in states:
metric.set_states(states[metric.name])
- def agg_states(
- self,
- states: Dict[str, MetricState],
- ) -> None:
- """Aggregate provided state variables into self ones.
-
- This method is DEPRECATED as of DecLearn v2.4, in favor of
- merely aggregating `MetricState` instances, using either
- their `aggregate` method or the overloaded `+` operator.
- It will be removed in DecLearn 2.6 and/or 3.0.
-
- This method is designed to aggregate results from multiple
- similar metrics objects into a single one before computing
- its results.
-
- Parameters
- ----------
- states: dict[str, float or numpy.ndarray]
- Dict of states emitted by another instance of this class
- via its `get_states` method.
-
- Raises
- ------
- KeyError
- If any state variable is missing from `states`.
- TypeError
- If any state variable is of improper type.
- ValueError
- If any array state variable is of improper shape.
- """
- warnings.warn(
- "'MetricSet.agg_states' was deprecated in DecLearn v2.4, in favor "
- "of aggregating 'MetricState' instances directly, and setting "
- "final aggregated states using 'MetricSet.set_state'. It will be "
- "removed in DecLearn 2.6 and/or 3.0.",
- DeprecationWarning,
- )
- with warnings.catch_warnings():
- warnings.simplefilter(action="ignore", category=DeprecationWarning)
- for metric in self.metrics:
- if metric.name in states:
- metric.agg_states(states[metric.name])
-
def get_config(
self,
) -> Dict[str, Any]:
diff --git a/declearn/optimizer/modules/_scaffold.py b/declearn/optimizer/modules/_scaffold.py
index c5c9a4a8..277bac03 100644
--- a/declearn/optimizer/modules/_scaffold.py
+++ b/declearn/optimizer/modules/_scaffold.py
@@ -35,7 +35,7 @@ References
import dataclasses
import uuid
import warnings
-from typing import Any, Dict, List, Optional, Set, Tuple, Union
+from typing import Any, Dict, Optional, Set, Tuple, Union
from declearn.model.api import Vector
from declearn.optimizer.modules._api import AuxVar, OptiModule
@@ -386,25 +386,10 @@ class ScaffoldServerModule(OptiModule[ScaffoldAuxVar]):
def __init__(
self,
- clients: Optional[List[str]] = None,
) -> None:
- """Instantiate the server-side SCAFFOLD gradients-correction module.
-
- Parameters
- ----------
- clients:
- DEPRECATED and unused starting with declearn 2.4.
- Optional list of known clients' id strings.
- """
+ """Instantiate the server-side SCAFFOLD gradients-correction module."""
self.s_state = 0.0 # type: Union[Vector, float]
self.clients = set() # type: Set[str]
- if clients: # pragma: no cover
- warnings.warn(
- "ScaffoldServerModule's 'clients' argument has been deprecated"
- " as of declearn v2.4, and no longer has any effect. It will"
- " be removed in declearn 2.6 and/or 3.0.",
- DeprecationWarning,
- )
def run(
self,
diff --git a/docs/release-notes/v2.6.0.md b/docs/release-notes/v2.6.0.md
index 1c1da1aa..4d1bf837 100644
--- a/docs/release-notes/v2.6.0.md
+++ b/docs/release-notes/v2.6.0.md
@@ -131,6 +131,32 @@ fairness levels of the last model.
## Other changes
+### Removal of deprecated features
+
+A number of features were deprecated in DecLearn 2.4.0 (whether legacy API
+methods, submdules or methods that were re-organized or renamed, parameters
+that were no longer used or a plainly-removed function). As of this new
+release, those features that had been kept back with a deprecation warning
+are now removed from the code.
+
+As a remainder, the removed features include:
+
+* Legacy aggregation methods:
+ - `declearn.aggregator.Aggregator.aggregate`
+ - `declearn.metrics.Metric.agg_states`
+ - `declearn.metrics.MetricSet.agg_states`
+* Legacy instantiation parameters:
+ - `declearn.aggregator.AveragingAggregator` parameter `client_weights`
+ - `declearn.aggregator.GradientMaskedAveraging` parameter `client_weights`
+ - `declearn.optimizer.modules.ScaffoldServerModule` parameter `clients`
+* Legacy names that were aliasing new locations:
+ - `declearn.communication.messaging` (moved to `declearn.messaging`)
+ - `declearn.communication.NetworkClient.check_message` (renamed
+ `recv_message`)
+* `declearn.dataset.load_dataset_from_json`
+
+### New developer-oriented changes
+
A few minor changes are shipped with this new release, that are mostly of
interest to developers - including end-users writing custom algorithms or
bridging DecLearn APIs within their own orchestration code.
diff --git a/test/aggregator/test_aggregator.py b/test/aggregator/test_aggregator.py
index e619bcce..8d1f74b4 100644
--- a/test/aggregator/test_aggregator.py
+++ b/test/aggregator/test_aggregator.py
@@ -143,31 +143,3 @@ class TestAggregator:
result = aggregator.finalize_updates(output)
expect = aggregator.finalize_updates(updates_a + updates_b)
assert result == expect
-
- # DEPRECATED: the following tests cover deprecated methods
-
- @pytest.mark.parametrize("framework", VECTOR_FRAMEWORKS)
- def test_aggregate(
- self,
- agg_cls: Type[Aggregator],
- updates: Dict[str, Vector],
- ) -> None:
- """Test that the legacy (deprecated) 'aggregate' method still works."""
- agg = agg_cls()
- n_steps = {key: 10 for key in updates}
- with pytest.warns(DeprecationWarning):
- outputs = agg.aggregate(updates, n_steps)
- ref_vec = list(updates.values())[0]
- assert isinstance(outputs, type(ref_vec))
- assert outputs.shapes() == ref_vec.shapes()
- assert outputs.dtypes() == ref_vec.dtypes()
-
- def test_aggregate_empty(
- self,
- agg_cls: Type[Aggregator],
- ) -> None:
- """Test that 'aggregate' raises the expected error on empty inputs."""
- agg = agg_cls()
- with pytest.warns(DeprecationWarning):
- with pytest.raises(TypeError):
- agg.aggregate(updates={}, n_steps={})
diff --git a/test/main/test_main_client.py b/test/main/test_main_client.py
index e002b9dc..345c1a20 100644
--- a/test/main/test_main_client.py
+++ b/test/main/test_main_client.py
@@ -139,17 +139,6 @@ class TestFederatedClientInit: # pylint: disable=too-many-public-methods
client = FederatedClient(netwk=MOCK_NETWK, train_data=dataset)
assert client.train_data is dataset
- def test_train_data_str(self) -> None:
- """Test specifying 'train_data' as a file path."""
- path = "mock_path_to_dataset.json"
- with mock.patch(
- "declearn.main._client.load_dataset_from_json",
- return_value=mock.create_autospec(Dataset, instance=True),
- ) as patched:
- client = FederatedClient(netwk=MOCK_NETWK, train_data=path)
- patched.assert_called_once_with(path)
- assert client.train_data is patched.return_value
-
def test_train_data_invalid(self) -> None:
"""Test specifying 'train_data' as an invalid type."""
with pytest.raises(TypeError):
@@ -172,19 +161,6 @@ class TestFederatedClientInit: # pylint: disable=too-many-public-methods
)
assert client.valid_data is dataset
- def test_valid_data_str(self) -> None:
- """Test specifying 'valid_data' as a file path."""
- path = "mock_path_to_dataset.json"
- with mock.patch(
- "declearn.main._client.load_dataset_from_json",
- return_value=mock.create_autospec(Dataset, instance=True),
- ) as patched:
- client = FederatedClient(
- netwk=MOCK_NETWK, train_data=MOCK_DATASET, valid_data=path
- )
- patched.assert_called_once_with(path)
- assert client.valid_data is patched.return_value
-
def test_valid_data_invalid(self) -> None:
"""Test specifying 'valid_data' as an invalid type."""
with pytest.raises(TypeError):
diff --git a/test/metrics/metric_testing.py b/test/metrics/metric_testing.py
index 2adb2fd9..043c6341 100644
--- a/test/metrics/metric_testing.py
+++ b/test/metrics/metric_testing.py
@@ -177,32 +177,6 @@ class MetricTestSuite:
expect = test_case.agg_scores
assert_dict_equal(metric.get_result(), expect, np_tolerance=self.tol)
- def test_legacy_agg_states(self, test_case: MetricTestCase) -> None:
- """Test that the deprecated `agg_states` method works as expected."""
- # Set up and update two identical metrics.
- metric = test_case.metric
- metbis = deepcopy(test_case.metric)
- metric.update(**test_case.inputs)
- metbis.update(**test_case.inputs)
- # Aggregate the second into the first. Verify that they now differ.
- assert_dict_equal(
- metric.get_states().to_dict(), metbis.get_states().to_dict()
- )
- with pytest.warns(DeprecationWarning):
- metbis.agg_states(metric.get_states())
- assert_dict_equal(
- metric.get_states().to_dict(), test_case.states.to_dict()
- )
- with pytest.raises(AssertionError): # assert not equal
- assert_dict_equal(
- metric.get_states().to_dict(), metbis.get_states().to_dict()
- )
- # Verify the correctness of the aggregated states and scores.
- states = test_case.agg_states
- scores = test_case.agg_scores
- assert_dict_equal(metbis.get_states().to_dict(), states.to_dict())
- assert_dict_equal(metbis.get_result(), scores, np_tolerance=self.tol)
-
def test_update_with_squeezable_inputs(
self, test_case: MetricTestCase
) -> None:
diff --git a/test/metrics/test_metricset.py b/test/metrics/test_metricset.py
index 1ff2eae2..8eb7b445 100644
--- a/test/metrics/test_metricset.py
+++ b/test/metrics/test_metricset.py
@@ -18,7 +18,7 @@
"""Unit tests for `declearn.metrics.MetricSet`."""
from unittest import mock
-from typing import Dict, Tuple
+from typing import Tuple
import numpy as np
import pytest
@@ -129,18 +129,6 @@ class TestMetricSet:
states["mse"]
)
- def test_agg_states(self) -> None:
- """Test that deprecated `MetricSet.agg_states` works as expected."""
- mae, mse, metrics = get_mock_metricset()
- states = {
- "mae": mae.get_states(),
- "mse": mse.get_states(),
- } # type: Dict[str, MetricState]
- with pytest.warns(DeprecationWarning):
- metrics.agg_states(states)
- mae.agg_states.assert_called_once_with(states["mae"]) # type: ignore
- mse.agg_states.assert_called_once_with(states["mse"]) # type: ignore
-
def test_get_config(self) -> None:
"""Test that `MetricSet.get_config` works as expected."""
mae = MeanAbsoluteError()
--
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