@@ -97,7 +97,7 @@ def cluster(self, X, y=None, update_interval=None):
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test_iter = mx .io .NDArrayIter ({'data' : X }, batch_size = batch_size , shuffle = False ,
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last_batch_handle = 'pad' )
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args = {k : mx .nd .array (v .asnumpy (), ctx = self .xpu ) for k , v in self .args .items ()}
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- z = model .extract_feature (self .feature , args , test_iter , N , self .xpu ).values ()[0 ]
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+ z = model .extract_feature (self .feature , args , None , test_iter , N , self .xpu ).values ()[0 ]
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kmeans = KMeans (self .num_centers , n_init = 20 )
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kmeans .fit (z )
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args ['dec_mu' ][:] = kmeans .cluster_centers_
@@ -112,7 +112,7 @@ def ce(label, pred):
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self .y_pred = np .zeros ((X .shape [0 ]))
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def refresh (i ):
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if i % update_interval == 0 :
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- z = model .extract_feature (self .feature , args , test_iter , N , self .xpu ).values ()[0 ]
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+ z = model .extract_feature (self .feature , args , None , test_iter , N , self .xpu ).values ()[0 ]
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p = np .zeros ((z .shape [0 ], self .num_centers ))
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self .dec_op .forward ([z , args ['dec_mu' ].asnumpy ()], [p ])
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y_pred = p .argmax (axis = 1 )
@@ -132,7 +132,7 @@ def refresh(i):
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solver .set_iter_start_callback (refresh )
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solver .set_monitor (Monitor (50 ))
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- solver .solve (self .xpu , self .loss , args , self .args_grad ,
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+ solver .solve (self .xpu , self .loss , args , self .args_grad , None ,
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train_iter , 0 , 1000000000 , {}, False )
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self .end_args = args
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if y is not None :
@@ -153,4 +153,4 @@ def mnist_exp(xpu):
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if __name__ == '__main__' :
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logging .basicConfig (level = logging .INFO )
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mnist_exp (mx .gpu (0 ))
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-
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+
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