Update app.py
Browse files
app.py
CHANGED
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@@ -18,9 +18,6 @@ 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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global graph
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graph = tf.compat.v1.get_default_graph()
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# Do you want it loud?
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VERBOSE = 1
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@@ -89,8 +86,7 @@ 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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@@ -115,8 +111,7 @@ 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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@@ -129,8 +124,7 @@ 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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# 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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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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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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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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