ValueError：图层“sequential_20”的输入 0 与图层不兼容：预期 shape=（None， 784），找到 shape=（50， 28， 28）

问：

这是我第一次用 Python 编写程序，我正在遵循教授给我的一篇论文，但我在运行 model.fit（） 时不断出现错误

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
import keras 
from keras.datasets import mnist
import seaborn as sns

(X_train, Y_train), (X_test, Y_test) = mnist.load_data()

m = X_train.shape[0]

X_train = X_train/255
X_train = X_train.reshape(X_train.shape[0],-1).T
X_test = X_test/255
X_test = X_test.reshape(X_test.shape[0],-1).T 

X_train.shape,X_test.shape

(X_train, Y_train), (X_test, Y_test) = mnist.load_data()
for i in range(9):
  plt.subplot(330 + 1 + i)
  plt.imshow(X_train[i], cmap=plt.get_cmap('gray'))
plt.show()

import keras
from keras.models import Sequential
from keras.layers import Dense, Dropout
from sklearn.metrics import confusion_matrix
from keras.optimizers import Adam

model = Sequential([
    Dense(units=10, input_shape=(784,), activation='relu'),
    Dense(units=10, activation='softmax')
])

model.compile(loss='categorical_crossentropy',optimizer=Adam(learning_rate=0.01), metrics=['accuracy'])
model.summary()



batch_size=50
epoch=5
model.fit(X_train,Y_train,batch_size,epoch)

“模型摘要错误”屏幕