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‎examples/ae_examples/cvae_dim_example/client.py‎

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from fl4health.clients.basic_client import BasicClient
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from fl4health.metrics import Accuracy
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from fl4health.metrics.base_metrics import Metric
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from fl4health.preprocessing.autoencoders.dim_reduction import CvaeFixedConditionProcessor
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from fl4health.preprocessing.autoencoders.dim_reduction import \
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CvaeFixedConditionProcessor
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from fl4health.utils.config import narrow_dict_type
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from fl4health.utils.load_data import ToNumpy, load_mnist_data
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from fl4health.utils.random import set_all_random_seeds

‎examples/ae_examples/cvae_dim_example/server.py‎

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from flwr.server.strategy import FedAvg
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from examples.models.mnist_model import MnistNet
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from fl4health.checkpointing.checkpointer import BestLossTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import BaseServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn
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from fl4health.checkpointing.checkpointer import \
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BestLossTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import \
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BaseServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import (
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evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn)
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from fl4health.parameter_exchange.full_exchanger import FullParameterExchanger
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from fl4health.servers.base_server import FlServer
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from fl4health.utils.config import load_config

‎examples/ae_examples/cvae_examples/conv_cvae_example/client.py‎

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from torch.optim import Optimizer
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from torch.utils.data import DataLoader
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from examples.ae_examples.cvae_examples.conv_cvae_example.models import ConvConditionalDecoder, ConvConditionalEncoder
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from examples.ae_examples.cvae_examples.conv_cvae_example.models import (
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ConvConditionalDecoder, ConvConditionalEncoder)
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from fl4health.clients.basic_client import BasicClient
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from fl4health.metrics.base_metrics import Metric
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from fl4health.model_bases.autoencoders_base import ConditionalVae

‎examples/ae_examples/cvae_examples/conv_cvae_example/server.py‎

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from flwr.server.client_manager import SimpleClientManager
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from flwr.server.strategy import FedAvg
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from examples.ae_examples.cvae_examples.conv_cvae_example.models import ConvConditionalDecoder, ConvConditionalEncoder
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from fl4health.checkpointing.checkpointer import BestLossTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import BaseServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn
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from examples.ae_examples.cvae_examples.conv_cvae_example.models import (
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ConvConditionalDecoder, ConvConditionalEncoder)
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from fl4health.checkpointing.checkpointer import \
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BestLossTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import \
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BaseServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import (
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evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn)
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from fl4health.model_bases.autoencoders_base import ConditionalVae
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from fl4health.parameter_exchange.full_exchanger import FullParameterExchanger
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from fl4health.servers.base_server import FlServer

‎examples/ae_examples/cvae_examples/mlp_cvae_example/client.py‎

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from torch.optim import Optimizer
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from torch.utils.data import DataLoader
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from examples.ae_examples.cvae_examples.mlp_cvae_example.models import MnistConditionalDecoder, MnistConditionalEncoder
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from examples.ae_examples.cvae_examples.mlp_cvae_example.models import (
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MnistConditionalDecoder, MnistConditionalEncoder)
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from fl4health.clients.basic_client import BasicClient
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from fl4health.metrics.base_metrics import Metric
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from fl4health.model_bases.autoencoders_base import ConditionalVae

‎examples/ae_examples/cvae_examples/mlp_cvae_example/server.py‎

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from flwr.server.client_manager import SimpleClientManager
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from flwr.server.strategy import FedAvg
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from examples.ae_examples.cvae_examples.mlp_cvae_example.models import MnistConditionalDecoder, MnistConditionalEncoder
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from fl4health.checkpointing.checkpointer import BestLossTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import BaseServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn
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from examples.ae_examples.cvae_examples.mlp_cvae_example.models import (
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MnistConditionalDecoder, MnistConditionalEncoder)
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from fl4health.checkpointing.checkpointer import \
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BestLossTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import \
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BaseServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import (
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evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn)
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from fl4health.model_bases.autoencoders_base import ConditionalVae
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from fl4health.parameter_exchange.full_exchanger import FullParameterExchanger
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from fl4health.servers.base_server import FlServer

‎examples/ae_examples/fedprox_vae_example/client.py‎

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from torch.optim import Optimizer
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from torch.utils.data import DataLoader
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from examples.ae_examples.fedprox_vae_example.models import MnistVariationalDecoder, MnistVariationalEncoder
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from examples.ae_examples.fedprox_vae_example.models import (
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MnistVariationalDecoder, MnistVariationalEncoder)
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from fl4health.clients.fed_prox_client import FedProxClient
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from fl4health.model_bases.autoencoders_base import VariationalAe
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from fl4health.preprocessing.autoencoders.loss import VaeLoss

‎examples/ae_examples/fedprox_vae_example/server.py‎

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from flwr.common.typing import Config
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from flwr.server.client_manager import SimpleClientManager
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from examples.ae_examples.fedprox_vae_example.models import MnistVariationalDecoder, MnistVariationalEncoder
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from fl4health.checkpointing.checkpointer import BestLossTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import AdaptiveConstraintServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn
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from examples.ae_examples.fedprox_vae_example.models import (
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MnistVariationalDecoder, MnistVariationalEncoder)
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from fl4health.checkpointing.checkpointer import \
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BestLossTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import \
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AdaptiveConstraintServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import (
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evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn)
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from fl4health.model_bases.autoencoders_base import VariationalAe
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from fl4health.servers.base_server import FlServer
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from fl4health.strategies.fedavg_with_adaptive_constraint import FedAvgWithAdaptiveConstraint
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from fl4health.strategies.fedavg_with_adaptive_constraint import \
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FedAvgWithAdaptiveConstraint
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from fl4health.utils.config import load_config
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from fl4health.utils.parameter_extraction import get_all_model_parameters
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‎examples/apfl_example/server.py‎

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from flwr.server.strategy import FedAvg
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from examples.models.cnn_model import MnistNetWithBnAndFrozen
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from fl4health.metrics.metric_aggregation import evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn
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from fl4health.metrics.metric_aggregation import (
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evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn)
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from fl4health.model_bases.apfl_base import ApflModule
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from fl4health.reporting import JsonReporter
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from fl4health.servers.base_server import FlServer

‎examples/basic_example/server.py‎

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from flwr.server.strategy import FedAvg
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from examples.models.cnn_model import Net
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from fl4health.checkpointing.checkpointer import BestLossTorchModuleCheckpointer, LatestTorchModuleCheckpointer
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from fl4health.checkpointing.server_module import BaseServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn
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from fl4health.checkpointing.checkpointer import (
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BestLossTorchModuleCheckpointer, LatestTorchModuleCheckpointer)
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from fl4health.checkpointing.server_module import \
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BaseServerCheckpointAndStateModule
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from fl4health.metrics.metric_aggregation import (
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evaluate_metrics_aggregation_fn, fit_metrics_aggregation_fn)
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from fl4health.parameter_exchange.full_exchanger import FullParameterExchanger
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from fl4health.servers.base_server import FlServer
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from fl4health.utils.config import load_config, make_dict_with_epochs_or_steps

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