Ok. So I'm fairly new to deep learning. When I ran my code I got ValueError: Input 0 of layer sequential is incompatible with the layer: expected ndim=3, found ndim=2. Full shape received: (None, 1)
My dimensions are
X = (6018,)
y = (6018,)
My model is
model = Sequential()
model.add(LSTM(64,input_shape=(1, 2),return_sequences=True))
model.add(LSTM(64,input_shape=(1, 2)))
model.add(Dense(32,activation='relu'))
model.add(Dense(1,activation='softmax'))
model.compile(optimizer='adam', loss = 'categorical_crossentropy',metrics = ['accuracy'])
model.fit(X,y,epochs=25,batch_size=5)
I've already referenced this but when I tried the solution (of course tweaking the numbers) I still got the error. Any help would be appreciated.
As @Shubham Panchal commented Tensorflow LSTM expects input of shape 3D i.e., [batch_size, time_steps, feature_vector].
Working sample code
import tensorflow as tf
inputs = tf.random.normal([32, 10, 8])
print(inputs.shape)
lstm = tf.keras.layers.LSTM(4)
output = lstm(inputs)
print(output.shape)
print(output)
Output
(32, 10, 8)
(32, 4)
tf.Tensor(
[[ 0.2610239 0.05922208 0.27408293 0.06004168]
[ 0.09504984 -0.09526936 0.15872665 0.06893176]
[-0.00466381 0.25115085 0.09392853 0.30679247]
[-0.10023813 -0.13132107 0.05071423 0.09878921]
[ 0.02017667 -0.21159768 0.13270041 0.05142007]
[-0.0524956 -0.04429652 0.01828319 -0.24461922]
[ 0.4463299 -0.21829244 0.07631823 -0.02308152]
[-0.21405925 -0.0525855 0.2637051 -0.36504647]
[ 0.1591202 0.18965898 0.0729805 0.03004023]
[-0.04382075 0.03762269 -0.2226677 -0.04472603]
[-0.01629235 -0.15920192 0.23090638 0.00677661]
[ 0.23487142 -0.07626372 -0.01555465 0.06253306]
[ 0.2891141 0.1554318 -0.25290352 0.0484328 ]
[ 0.11477407 0.07930709 -0.39913383 0.04535771]
[ 0.24248329 -0.01814366 0.32974967 0.22873886]
[-0.08170582 0.04182371 0.19988067 -0.00295247]
[ 0.40137917 0.08512016 -0.26209465 0.04500046]
[ 0.12149049 -0.14915761 0.26120573 0.3150496 ]
[ 0.59085524 0.10106529 -0.34999618 0.03516199]
[ 0.29735157 0.05837289 -0.06764269 -0.09297346]
[-0.28203732 -0.33540457 0.02560275 -0.20562115]
[-0.06041891 -0.12593071 0.00945436 0.12473141]
[ 0.12043521 -0.11561332 -0.09308923 0.01790712]
[-0.0218282 0.28214487 -0.11302455 0.0034459 ]
[-0.12396459 -0.08603923 0.3626035 0.11152762]
[ 0.13282476 -0.01545438 0.09813337 -0.002675 ]
[ 0.5333185 -0.08465756 -0.27699044 -0.14487849]
[-0.01635256 -0.2978716 -0.13272133 -0.07292715]
[ 0.01473135 -0.04989992 0.11208256 0.19093426]
[-0.042191 -0.11678784 -0.15534575 -0.02011094]
[ 0.21434435 -0.0957195 0.44054344 -0.15512279]
[ 0.4018504 0.20203398 -0.44193134 0.06368993]], shape=(32, 4), dtype=float32)