Error when checking model input: expected lstm_1_input to have 3 dimensions, but got array with shape (339732, 29) : <p>My input is simply a csv file with 339732 rows and two columns :</p>

<ul>
<li>the first being 29 feature values, i.e. X</li>
<li>the second being a binary label value, i.e. Y</li>
</ul>

<p>I am trying to train my data on a stacked LSTM model:</p>

<pre><code>data_dim = 29
timesteps = 8
num_classes = 2

model = Sequential()
model.add(LSTM(30, return_sequences=True,
               input_shape=(timesteps, data_dim)))  # returns a sequence of vectors of dimension 30
model.add(LSTM(30, return_sequences=True))  # returns a sequence of vectors of dimension 30
model.add(LSTM(30))  # return a single vector of dimension 30
model.add(Dense(1, activation='softmax'))

model.compile(loss='binary_crossentropy',
              optimizer='rmsprop',
              metrics=['accuracy'])

model.summary()
model.fit(X_train, y_train, batch_size = 400, epochs = 20, verbose = 1)
</code></pre>

<p>This throws the error:</p>

<blockquote>
  <p>Traceback (most recent call last):
    File "first_approach.py", line 80, in 
      model.fit(X_train, y_train, batch_size = 400, epochs = 20, verbose = 1)</p>
  
  <p>ValueError: Error when checking model input: expected lstm_1_input to
  have 3 dimensions, but got array with shape (339732, 29)</p>
</blockquote>

<p>I tried reshaping my input using <code>X_train.reshape((1,339732, 29))</code> but it did not work showing error:</p>

<blockquote>
  <p>ValueError: Error when checking model input: expected lstm_1_input to
  have shape (None, 8, 29) but got array with shape (1, 339732, 29)</p>
</blockquote>

<p>How can I feed in my input to the LSTM ?</p>
