AttributeError: 'Parameters' object has no attribute 'parameters'

Question

I am a college student doing federation learning with flower+pytorch, and I have made a demo of it. The server files and client files are already written and run separately from the console. Now there is a problem, the error message says AttributeError: 'Parameters' object has no attribute 'parameters' My code is short, so I write it all out：

import pandas as pd
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from model import MLP
import flwr as fl
from torch.utils.data import TensorDataset, DataLoader
import multiprocessing
import io
import torch



def preprocess_data(file_path):
    data = pd.read_csv(file_path)

    if data.isnull().sum().sum() > 0:
        num_imputer = SimpleImputer(strategy='median')
        data[data.columns] = num_imputer.fit_transform(data[data.columns])

    scaler = StandardScaler()

    data[data.columns[1:-1]] = scaler.fit_transform(data[data.columns[1:-1]])

    X = data[data.columns[1:-1]].values
    y = data['Class'].values
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

    X_train = torch.tensor(X_train, dtype=torch.float32)
    y_train = torch.tensor(y_train, dtype=torch.long)
    X_test = torch.tensor(X_test, dtype=torch.float32)
    y_test = torch.tensor(y_test, dtype=torch.long)

    return X_train, y_train, X_test, y_test


def train_model(model, trainloader, epochs):
    """Train the model on the training set."""
    criterion = torch.nn.CrossEntropyLoss()
    optimizer = torch.optim.Adam(model.parameters(), lr=0.001)
    for epoch in range(epochs):
        for inputs, labels in trainloader:
            outputs = model(inputs)
            loss = criterion(outputs, labels)
            optimizer.zero_grad()
            loss.backward()
            optimizer.step()


def test_model(model, testloader):
    """Validate the model on the test set."""
    criterion = torch.nn.CrossEntropyLoss()
    correct, total, loss = 0, 0, 0.0
    with torch.no_grad():
        for inputs, labels in testloader:
            outputs = model(inputs)
            loss += criterion(outputs, labels).item()
            _, predicted = torch.max(outputs.data, 1)
            total += labels.size(0)
            correct += (predicted == labels).sum().item()
    accuracy = correct / total
    return loss / len(testloader), accuracy


def load_data(file_path, batch_size=32):
    """Load and preprocess data from a file."""
    # Preprocess the data
    X_train, y_train, X_test, y_test = preprocess_data(file_path)

    # Create TensorDatasets
    train_data = TensorDataset(X_train, y_train)
    test_data = TensorDataset(X_test, y_test)

    # Create DataLoaders
    trainloader = DataLoader(train_data, batch_size=batch_size, shuffle=True)
    testloader = DataLoader(test_data, batch_size=batch_size)

    return trainloader, testloader


def start_client(client_id, features):
    # Load and preprocess data
    trainloader, testloader = load_data('C:\\Users\\Fantasy\\Desktop\\毕设\\程序\\dataset\\creditcard_2023.csv')

    # Create an MLP model instance, the size of the input layer is the number of features
    model = MLP(len(features))

    # Create a client instance
    client = Client(trainloader, testloader, model)

    fl.client.start_client(server_address="127.0.0.1:8080", client=client)



class Client(fl.client.NumPyClient):
    def __init__(self, trainloader, testloader, model):
        self.model = model
        self.trainloader = trainloader
        self.testloader = testloader

    def get_parameters(self, config):
        parameters = {name: io.BytesIO() for name, _ in self.model.named_parameters()}
        for name, param in self.model.named_parameters():
            torch.save(param.detach().cpu(), parameters[name])
        return fl.common.Parameters(parameters, tensor_type="float32")

    def set_parameters(self, parameters):
        self.model.load_state_dict(parameters)

    def fit(self, parameters, config):
        self.set_parameters(parameters)
        train_model(self.model, self.trainloader, epochs=1)
        return self.get_parameters(config={}), len(self.trainloader.dataset), {}

    def evaluate(self, parameters, config):
        self.set_parameters(parameters)
        loss, accuracy = test_model(self.model, self.testloader)
        return loss, len(self.testloader.dataset), {"accuracy": accuracy}


def main():
    # Define the features for each client
    features_list = [['V1', 'V2', 'V3', 'V4'], ['V5', 'V6', 'V7', 'V8'], ['V9', 'V10', 'V11', 'V12']]

    # Create a process for each client
    processes = []
    for i in range(3):  # Replace with the actual number of clients
        features = features_list[i % len(features_list)]  # Assign features to clients in a round-robin fashion
        process = multiprocessing.Process(target=start_client, args=(i, features))
        processes.append(process)

    # Start all processes
    for process in processes:
        process.start()

    # Wait for all processes to finish
    for process in processes:
        process.join()


if __name__ == "__main__":
    main()

I hope someone can help me solve it, because this is the prototype of my graduation project, so I am in a hurry.

The error message is as follows:

Process Process-1:
Traceback (most recent call last):
  File "C:\Users\Fantasy\AppData\Local\Programs\Python\Python310\lib\multiprocessing\process.py", line 314, in _bootstrap
    self.run()
  File "C:\Users\Fantasy\AppData\Local\Programs\Python\Python310\lib\multiprocessing\process.py", line 108, in run       
    self._target(*self._args, **self._kwargs)
  File "C:\Users\Fantasy\Desktop\毕设\程序\code\main.py", line 100, in start_client
    fl.client.start_client(server_address="127.0.0.1:8080", client=client)
  File "C:\Users\Fantasy\Desktop\毕设\程序\code\venv\lib\site-packages\flwr\client\app.py", line 248, in start_client
    _start_client_internal(
  File "C:\Users\Fantasy\Desktop\毕设\程序\code\venv\lib\site-packages\flwr\client\app.py", line 382, in _start_client_internal
    out_message = app(message=message, context=context)
  File "C:\Users\Fantasy\Desktop\毕设\程序\code\venv\lib\site-packages\flwr\client\flower.py", line 76, in __call__
    return self._call(message, context)
  File "C:\Users\Fantasy\Desktop\毕设\程序\code\venv\lib\site-packages\flwr\client\flower.py", line 66, in ffn
    out_message = handle_legacy_message_from_tasktype(
  File "C:\Users\Fantasy\Desktop\毕设\程序\code\venv\lib\site-packages\flwr\client\message_handler\message_handler.py", line 130, in handle_legacy_message_from_tasktype
    out_recordset = getparametersres_to_recordset(
  File "C:\Users\Fantasy\Desktop\毕设\程序\code\venv\lib\site-packages\flwr\common\recordset_compat.py", line 342, in getparametersres_to_recordset
    getparametersres.parameters, keep_input=keep_input
AttributeError: 'Parameters' object has no attribute 'parameters'

I don't know what the problem is, so I can't fix it。This is the first time I've asked a question on stack overflow.