我正在尝试合并cnn-LSTM分类模型，但出现以下错误：

  

ValueError：输入0与图层flatten_2不兼容：预期的min_ndim = 3，找到的ndim = 2

环境：

  

Python 3.5

     

Keras 2.2.0

     

Tf-GPU 1.6.0

关于如何解决此问题的任何想法？非常感谢！

from keras.layers import Convolution2D,MaxPooling2D,flatten,Reshape
from keras.models import Sequential
from keras.utils.np_utils import to_categorical
from keras.layers.wrappers import TimeDistributed
from keras.layers.pooling import GlobalAveragePooling1D
import gc
import numpy as np


timesteps = 100;
number_of_samples = 2500;
nb_samples = number_of_samples;
frame_row = 32;
frame_col = 32;
channels = 3;

nb_epoch = 1;
batch_size = timesteps;

data = np.random.random((2500,timesteps,frame_row,frame_col,channels))
label = np.random.randint(4,size=(2500,1))

X_train = data[0:2000,:]
y_train = label[0:2000]
y_train = to_categorical(y_train)
X_test = data[2000:,:]
y_test = label[2000:,:]

# %%

model = Sequential();

model.add(TimeDistributed(Convolution2D(32,3,border_mode='same'),input_shape=(100,32,3)))
model.add(TimeDistributed(Convolution2D(32,3)))
model.add(TimeDistributed(activation('relu')))
model.add(TimeDistributed(Convolution2D(32,3)))
model.add(TimeDistributed(activation('relu')))
model.add(TimeDistributed(MaxPooling2D(pool_size=(2,2))))
model.add(TimeDistributed(Dropout(0.25)))

model.add(TimeDistributed(flatten()))
model.add(TimeDistributed(Dense(512)))

model.add(TimeDistributed(Dense(35,name="first_dense")))

model.add(LSTM(20,return_sequences=True,name="lstm_layer"));

# %%
model.add(TimeDistributed(Dense(4),name="time_distr_dense_one"))
model.add(GlobalAveragePooling1D(name="global_avg"))
model.add(flatten())
model.add(TimeDistributed(Dense(4,activation="softmax"),name="time_distr_dense"))

# %%

model.compile(loss='categorical_crossentropy',optimizer='adam',metrics=['accuracy'])
model.fit(X_train,y_train,epochs=3,validation_split=0.1,batch_size=32,verbose=2)

gc.collect()