title: How to change the input shape of an existing tensorflow model (.pb)
body: <p>I want to turn a preexisting tensorflow graph into a graph that can be deployed on the Movidius Neural Compute stick.</p>
  
  <p>When I use the command mvNCCompile (from NCSDK), following Error occurs:
  [Error 5] Toolkit Error: Stage Details Not Supported: Dynamic input shape not supported.</p>
  
  <p>After checking the tensorflow graph in tensorboard I figured out that the input tensor has following shape: (?,?,?,3)
  In my usecase I have always the same input shape which is:(1,368,656,3). </p>
  
  <p>Now I want to change the tensors' dynamic input shape into a static one.</p>
  
  <p>How can I accomplish that?</p>
  
  <p>I have tried following this post: <a href="https://stackoverflow.com/questions/55841854/how-to-change-a-saved-model-input-shape-in-tensorflow">How to change a saved model input shape in Tensorflow?</a>
  but I could not change the graph.</p>
  
  <p>Graph can be found here: <a href="https://github.com/ildoonet/tf-pose-estimation/blob/master/models/graph/mobilenet_thin/graph_opt.pb" rel="nofollow noreferrer">https://github.com/ildoonet/tf-pose-estimation/blob/master/models/graph/mobilenet_thin/graph_opt.pb</a></p>
  
  <pre><code>import tensorflow as tf
  
  graph_path = 
  '/home/bk/Documents/OPSLim/Pose/graph_models/mobilenet_thin/graph_opt.pb'
  
  with tf.gfile.GFile(graph_path, 'rb') as f:
      graph_def = tf.GraphDef()
      graph_def.ParseFromString(f.read())
  
  
  graph = tf.get_default_graph()
  tf_new_image = tf.placeholder(shape=(1, 368, 368, 3), dtype='float32', 
  name='new_image')
  tf.import_graph_def(graph_def, name='TfPoseEstimator', input_map= {"image:0": tf_new_image})
  </code></pre>