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Merge branch 'master' into cpp_class_op
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advanced_source/neural_style_tutorial.py

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@@ -403,7 +403,7 @@ def get_input_optimizer(input_img):
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# each iteration of the networks, it is fed an updated input and computes
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# new losses. We will run the ``backward`` methods of each loss module to
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# dynamicaly compute their gradients. The optimizer requires a “closure”
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# function, which reevaluates the modul and returns the loss.
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# function, which reevaluates the module and returns the loss.
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#
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# We still have one final constraint to address. The network may try to
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# optimize the input with values that exceed the 0 to 1 tensor range for

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