title: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray) - Already have converted the data to numpy array
body: <p>Trying to train a single layer NN for text based multi label classification problem.</p>
  <pre><code>model= Sequential()
  model.add(Dense(20, input_dim=400, kernel_initializer='he_uniform', activation='relu'))
  model.add(Dense(9, activation='sigmoid'))
  model.compile(loss='binary_crossentropy', optimizer='adam')
  
  model.fit(x_train, y_train, verbose=0, epochs=100)
  </code></pre>
  <p>Getting error as :</p>
  <pre><code>ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray).
  </code></pre>
  <p>x_train is a 300-dim word2vec vectorized text data, each instance padded to 400 length. Contains 462 records.</p>
  <p>Observations on training data are as below :</p>
  <pre><code>print('#### Shape of input numpy array #####')
  print(x_train.shape)
  print('#### Shape of each element in the array #####')
  print(x_train[0].shape)
  print('#### Object type for input data #####')
  print(type(x_train))
  print('##### Object type for first element of input data ####')
  print(type(x_train[0]))
  
  #### Shape of input numpy array #####
  (462,)
  #### Shape of each element in the array #####
  (400, 300)
  #### Object type for input data #####
  &lt;class 'numpy.ndarray'&gt;
  ##### Object type for first element of input data ####
  &lt;class 'numpy.ndarray'&gt;
  </code></pre>