神经网络中+：'NoneType‘和'int’的操作数类型不受支持

import tensorflow as tf

# 假设 data 是你的输入数据
if data is None:
    raise ValueError("Input data is None")

model = tf.keras.Sequential([
    tf.keras.layers.Input(shape=(28, 28)),
    tf.keras.layers.Flatten(),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dense(10, activation='softmax')
])

import torch.nn as nn

class SimpleModel(nn.Module):
    def __init__(self):
        super(SimpleModel, self).__init__()
        self.flatten = nn.Flatten()
        self.fc1 = nn.Linear(28 * 28, 128)
        self.fc2 = nn.Linear(128, 10)

    def forward(self, x):
        x = self.flatten(x)
        x = self.fc1(x)
        x = nn.functional.relu(x)
        x = self.fc2(x)
        return nn.functional.softmax(x, dim=1)

initializer = tf.keras.initializers.GlorotUniform()
model.add(tf.keras.layers.Dense(128, kernel_initializer=initializer))

self.fc1 = nn.Linear(28 * 28, 128, bias=True)