Input 0 is incompatible with layer dense_3: expected ndim=2, found ndim=3 about captcha_break HOT 3 OPEN

from captcha.image import ImageCaptcha
import matplotlib.pyplot as plt
import numpy as np
import random
import string

characters = string.digits + string.ascii_uppercase
width, height, n_len, n_class = 170, 80, 4, len(characters)
def gen(batch_size=32):
    X = np.zeros((batch_size, height, width, 3), dtype=np.uint8)
    y = [np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(n_len)]
    generator = ImageCaptcha(width=width, height=height)
    while True:
        for i in range(batch_size):
            random_str = ''.join([random.choice(characters) for j in range(4)])
            X[i] = generator.generate_image(random_str)
            for j, ch in enumerate(random_str):
                y[j][i, :] = 0
                y[j][i, characters.find(ch)] = 1
        yield X, y
def decode(y):
    y = np.argmax(np.array(y), axis=2)[:,0]
    return ''.join([characters[x] for x in y])
X, y = next(gen(1))
plt.imshow(X[0])
plt.title(decode(y))
from keras.models import *
from keras.layers import *
input_tensor = Input((height, width, 3))
x = input_tensor
for i in range(4):
    x = Conv2D(filters=32*2**i, kernel_size=(3, 3), activation='relu')(x)
    x = Conv2D(filters=32*2**i, kernel_size=(3, 3), activation='relu')(x)
    x = MaxPooling2D(pool_size=(2, 2))(x)
x = Flatten()(x)
x = Dropout(0.25)(x)
x = [Dense(n_class, activation='softmax', name='c%d'%(i+1))(x) for i in range(4)]
model = Model(inputs=input_tensor, outputs=x)
model.compile(loss='categorical_crossentropy', optimizer='adadelta', metrics=['accuracy'])
from keras.utils.vis_utils import plot_model
plot_model(model, to_file="model.png", show_shapes=True)
model.fit_generator(gen(), steps_per_epoch=1600, epochs=5, validation_data=gen(), validation_steps=40)