下面是我的代码，请大家帮帮我

import tensorflow as tf
from keras.preprocessing.image import ImageDataGenerator
import numpy as np

train_datagen = ImageDataGenerator(
        rescale=1./255,
        shear_range=0.2,
        zoom_range=0.2,
        horizontal_flip=True)

training_set = train_datagen.flow_from_directory(
        'gopi_cnn_training_data',
        target_size=(100, 100),
        batch_size=32)
    

test_datagen = ImageDataGenerator(rescale=1./255)
test_set = test_datagen.flow_from_directory(
        'gopi_cnn_test_data',
        target_size=(100,100),
        batch_size=32)

cnn = tf.keras.models.Sequential()

cnn.add(tf.keras.layers.Conv2D(filters=32, kernel_size=3, activation='relu', input_shape=[100,100,3]))

cnn.add(tf.keras.layers.MaxPool2D(pool_size=2, strides=2))

cnn.add(tf.keras.layers.Conv2D(filters=32, kernel_size=3, activation='relu'))
cnn.add(tf.keras.layers.MaxPool2D(pool_size=2, strides=2))

cnn.add(tf.keras.layers.Flatten())

cnn.add(tf.keras.layers.Dense(units=128, activation='relu'))

cnn.add(tf.keras.layers.Dense(units=1, activation='softmax'))
 
cnn.compile(optimizer='adam', loss = 'categorical_crossentropy', metrics = ['accuracy'])

cnn.fit(x = training_set, validation_data = test_set, epochs = 25)

我收到以下错误InvalidArgumentError：基质大小不兼容：在[0]：[32，21]，在[1]：[128，1] 节点MatMul（定义在C：\Users\THUMMAGO\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow_core\python\framework\ops.py：1751） [Op：__inference_distributed_function_5318]
函数调用堆栈：分布函数