I'm working on text classification using Tensorflow-hub pretrained Word2vec model. And I'm seeking for adding an LSTM layer to the keras model. For that, I used the following code:
model = tf.keras.models.Sequential()
model.add(hub.KerasLayer(hub.load('https://tfhub.dev/google/Wiki-words-250/2'),
input_shape=[],
dtype=tf.string,
trainable=True))
After adding an LSTM layer:
model.add(tf.keras.layers.LSTM(32))
It shows me the follwing error:
~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\input_spec.py in assert_input_compatibility(input_spec, inputs, layer_name)
174 ndim = x.shape.ndims
175 if ndim != spec.ndim:
--> 176 raise ValueError('Input ' + str(input_index) + ' of layer ' +
177 layer_name + ' is incompatible with the layer: '
178 'expected ndim=' + str(spec.ndim) + ', found ndim=' +
ValueError: Input 0 of layer lstm_0 is incompatible with the layer: expected ndim=3, found ndim=2. Full shape received: [None, 250]
Any help is appreciable.
You can reshape the output of the hub.KerasLayer:
model.add(hub.KerasLayer(hub.load('https://tfhub.dev/google/Wiki-words-250/2'),
input_shape=[],
dtype=tf.string,
trainable=True))
model.add(tf.keras.layers.Reshape((250, 1)))
model.add(tf.keras.layers.LSTM(32))
model.summary()
Layer (type) Output Shape Param #
=================================================================
keras_layer_4 (KerasLayer) (None, 250) 252343750
_________________________________________________________________
reshape_2 (Reshape) (None, 250, 1) 0
_________________________________________________________________
lstm_2 (LSTM) (None, 32) 4352
=================================================================
Total params: 252,348,102
Trainable params: 252,348,102
Non-trainable params: 0