title: same model with diferent prediction betwen python and javascript tensorflow
body: <p>Hello I am exporting arcface model from python to tensorflow.js in python I got the following prediction:</p>
  <pre><code>-2.47331879e+02,  2.43775589e+02,  1.48011673e+02,....
  </code></pre>
  <p>But in javascript, I got the following.</p>
  <pre><code>-247.3305206298828,243.7752685546875,148.0111541748047,....
  </code></pre>
  <p>But the input is the same image, the only different thing is that in TensorFlow, I needed to cast the array to tensor using the following line:</p>
  <pre><code>  face = tf.tensor(face[0][0])
  </code></pre>
  <p>Why I am getting different results?</p>
  <p><strong>EDIT</strong></p>
  <p>I am using this code in order to get the image as array in python and in javascript</p>
  <p>Python code:</p>
  <pre><code>img = Image.open('file.jpg')
  img = img.resize((112, 112), Image.ANTIALIAS)
  img = np.expand_dims(img, axis=0)
  img = tf.convert_to_tensor(img, dtype='int32')
  </code></pre>
  <p>Image is save in a file with the following code:</p>
  <pre><code>with open('data.txt', 'w') as outfile:
      json.dump(np.array(img).tolist(), outfile)
  </code></pre>
  <p>And paste in a variable in javascript code.</p>
  <p>Javascript code:</p>
  <pre><code> face = tf.tensor(face[0][0], [1, 112, 112, 3], 'int32')
   const display = document.getElementById('display');
   modelLayer.then(model =&gt; display.innerHTML = 
   model.predict(face).dataSync())
  </code></pre>
  <p><strong>EDIT2</strong></p>
  <p>The euclidean distance between javascript prediction and Python prediction is 0.021145982611487882</p>
  <p>Thanks</p>