title: Keras - Number of samples error with multidimensional input
body: <p>I'm trying to construct a (very simple) Keras model as a baseline for a project. I have a list of 3459 numpy arrays of shape (2, 6, 15) as input, and a list of target values (ints as numpy arrays with shape ()). When I try to train the model I get this error: </p>
  
  <p>"ValueError: Number of samples 2 is less than samples required for specified batch_size 32 and steps 108."</p>
  
  <p>The model so far is extremely simple, but I'm having no luck getting it to train:</p>
  
  <pre><code>input = Input(shape=(2, 6, 15))
  x = Dense(64, activation='relu')(input)
  x = Dense(64, activation='relu')(x)
  output = Dense(1)(x)
  
  model = Model(inputs=input, outputs=output)
  model.compile(optimizer='adam', loss='mean_squared_error',
                metrics=['accuracy'])
  hist = model.fit(
      X_train,
      y_train,
      batch_size=32,
      epochs=10, 
      validation_data=(X_test, y_test),
      steps_per_epoch=(len(X_train) // 32),
      validation_steps=(len(X_test) // 32))
  </code></pre>
  
  <p>I'm currently loading the data from pickle files, and I suspect that the issue might be the array structure of the individual training cases. When looking at one of the arrays in the X_train it has a structure [[[...]...], [[...]...]], and I suspect the code is confusing the outer brackets as the batch container, so it's reading a batch size of 2 as input instead. Just a theory, but I don't know how to address that to check for myself.</p>