import tensorflow as tf

    for path in paths:
        spectrograms.append(np.load("spectrogram/" + path + ".npy"))
        if spectrograms[-1].shape[0] > max_x:
            max_x = spectrograms[-1].shape[0]
    return spectrograms, max_x


# In[4]:


tf.reset_default_graph()
sess = tf.InteractiveSession()
model = Model()
sess.run(tf.global_variables_initializer())


# In[5]:


for e in range(30):
    pbar = tqdm(range(0, len(text_files), batch_size), desc="minibatch loop")
    total_cost, total_acc = 0, 0
