ccm commited on
Commit
b0dbf03
·
1 Parent(s): f5dff1a

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -3
app.py CHANGED
@@ -18,6 +18,7 @@ sess = tf.compat.v1.Session()
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  from keras import backend as K
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  K.set_session(sess)
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  # Do you want it loud?
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  VERBOSE = 1
@@ -87,7 +88,8 @@ class Network(object):
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  other_data_input = data_input.reshape((self.G, self.G, self.G), order='F')
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  # Get the outputs
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- predicted_output = self.network.predict(data_input)
 
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  true_output = self.new_curves[idx].reshape((3, self.F))
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  predicted_output = predicted_output.reshape((3, self.F))
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@@ -112,7 +114,8 @@ class Network(object):
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  other_data_input = data_input.reshape((3, self.F))
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  # Get the outputs
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- predicted_output = self.network.predict(data_input)
 
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  true_output = self.new_geometry[idx].reshape((self.G, self.G, self.G), order='F')
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  predicted_output = predicted_output.reshape((self.G, self.G, self.G), order='F')
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@@ -125,7 +128,8 @@ class Network(object):
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  data_input = other_data_input.reshape((1, 3*self.F))
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  # Get the outputs
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- predicted_output = self.network.predict(data_input)
 
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  predicted_output = predicted_output.reshape((self.G, self.G, self.G), order='F')
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  # return idx, other_data_input, true_output, predicted_output
 
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  from keras import backend as K
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  K.set_session(sess)
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+ graph = tf.get_default_graph()
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  # Do you want it loud?
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  VERBOSE = 1
 
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  other_data_input = data_input.reshape((self.G, self.G, self.G), order='F')
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  # Get the outputs
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+ with graph.as_default():
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+ predicted_output = self.network.predict(data_input)
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  true_output = self.new_curves[idx].reshape((3, self.F))
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  predicted_output = predicted_output.reshape((3, self.F))
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  other_data_input = data_input.reshape((3, self.F))
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  # Get the outputs
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+ with graph.as_default():
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+ predicted_output = self.network.predict(data_input)
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  true_output = self.new_geometry[idx].reshape((self.G, self.G, self.G), order='F')
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  predicted_output = predicted_output.reshape((self.G, self.G, self.G), order='F')
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  data_input = other_data_input.reshape((1, 3*self.F))
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  # Get the outputs
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+ with graph.as_default():
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+ predicted_output = self.network.predict(data_input)
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  predicted_output = predicted_output.reshape((self.G, self.G, self.G), order='F')
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  # return idx, other_data_input, true_output, predicted_output