deep learning - ValueError: Error when checking input: expected conv1d_1_input to have 3 dimensions, but got array with shape (500000, 3253)? -

i want train data convolution neural network, have reshaped data: parameters have used:

'x_train.shape'=(500000, 3253) 'y_train.shape', (500000,) 'y_test.shape', (20000,) 'y_train[0]', 97 'y_test[0]', 99 'y_train.shape', (500000, 256) 'y_test.shape', (20000, 256) 

this how define model architecture:

# 3. define model architecture  model = sequential()  model.add(conv1d(64, 8, strides=1, padding='valid',                         dilation_rate=1, activation=none, use_bias=true, kernel_initializer='glorot_uniform',                         bias_initializer='zeros', kernel_regularizer=none, bias_regularizer=none,                         activity_regularizer=none, kernel_constraint=none, bias_constraint=none, input_shape=x_train.shape))         print('***done***') ###### input_traces=n_features   ###### input_shape=(batch_size, trace_lenght,num_of_channels)            model.add(maxpooling1d(pool_size=2,strides=none, padding='valid',input_shape=x_train.shape)) print('***done***') model.add(flatten()) print('***done***') model.add(dropout(0.5)) print('***done***') #print(model.summary()) model.add(dense(1, activation='relu')) print('***done***')  # # # 4. compile model model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])  # # # # # 5. fit model on training data model.fit(x_train, y_train, batch_size=100, epochs=500,verbose=2) 

the result is:

........ ***done*** ***done*** traceback (most recent call last):   file "cnn_based_attack.py", line 128, in <module>     model.fit(x_train, y_train, batch_size=100, epochs=500,verbose=2)   file "/home/meriem/.local/lib/python2.7/site-packages/keras/models.py", line 853, in fit     initial_epoch=initial_epoch)   file "/home/meriem/.local/lib/python2.7/site-packages/keras/engine/training.py", line 1424, in fit     batch_size=batch_size)   file "/home/meriem/.local/lib/python2.7/site-packages/keras/engine/training.py", line 1300, in _standardize_user_data     exception_prefix='input')   file "/home/meriem/.local/lib/python2.7/site-packages/keras/engine/training.py", line 127, in _standardize_input_data     str(array.shape)) valueerror: error when checking input: expected conv1d_1_input have 3 dimensions, got array shape (500000, 3253) 

the error have in reshaping data , in step 5:

   # # # # # 5. fit model on training data     model.fit(x_train, y_train, batch_size=100, epochs=500,verbose=2) 

how resolve problem?

the input shape wrong, should input_shape = (1, 3253) theano or (3253, 1) tensorflow. input shape doesn't include number of samples.

then need reshape data include channels axis:

x_train = x_train.reshape((500000, 1, 3253)) 

or move channels dimension end if use tensorflow. after these changes should work.