title: How to obtain embedded representation of single test instance after training
body: <p>The first layer of my RNN is embedded layer as follows.</p>
  
  <pre><code>visible = Input(shape=(250,)) 
  embed=Embedding(vocab_size,50)(visible)     
  x2=keras.layers.GRU(224, return_sequences=False)(embed)
  predictions=Dense(1, activation='sigmoid')(x2)
  </code></pre>
  
  <p>I train this network and predict some output. </p>
  
  <p>Now after training, I test it on my test data which is very straight forward. </p>
  
  <p>I want to know the exact embeddings of my test data or for the sake of implementation, embeddings of any of my test sequence after the model has been trained. I want to use those embedding in some other application. Is there any way to extract those embedding for my test sequence data after the training?</p>
  
  <p>Try: Let's say my model is m, the I obtain the embedding weights as follows.</p>
  
  <pre><code>embeddings = m.layers[1].get_weights()
  </code></pre>
  
  <p>I also have a reverse dictionary <code>reverse_char_map</code> as follows.</p>
  
  <pre><code>{1: 'c',
   2: 'C',
   3: '(',
   4: ')',
   5: 'O',
   6: '=',
   7: '1',
   8: '2',
   9: 'N',
   10: '3',
   11: 'n',
   12: '[',
   13: ']',
   14: 'S',
   15: '4',
   16: '-',
   17: 'l',
   18: '+',
   19: 'H',
   20: '5',
   21: 'F',
   22: '.',
   23: '#',
   24: 's',
   25: 'o',
   26: '6',
   27: 'P',
   28: 'B',
   29: 'r',
   30: 'a',
   31: '7',
   32: 'e',
   33: 'I',
   34: 'i',
   35: '8',
   36: 'u',
   37: 'K',
   38: '9',
   39: 'R',
   40: '%',
   41: '0',
   42: 'Z',
   43: 'h',
   44: 'L',
   45: 'A',
   46: 't',
   47: 'd',
   48: 'G',
   49: 'M',
   50: 'g',
   51: 'U',
   52: 'b',
   53: 'T',
   54: 'W',
   55: 'p',
   56: 'V'}
  </code></pre>
  
  <p>I don't know how to use <code>embeddings</code> with <code>reverse_char_map</code> to obtain embeddings for one of the test input sequence.</p>