[GitHub] sandeep-krishnamurthy commented on a change in pull request #12498: Code modification for testcases of various network models in directory example

[GitBox <gi...@apache.org>]

sandeep-krishnamurthy commented on a change in pull request #12498: Code modification for  testcases of various network models in directory example
URL: https://github.com/apache/incubator-mxnet/pull/12498#discussion_r226874463
 
 

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 File path: example/bayesian-methods/bdk_demo.py
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 @@ -180,18 +183,18 @@ def run_mnist_SGLD(training_num=50000):
     minibatch_size = 100
     net = get_mnist_sym()
     data_shape = (minibatch_size,) + X.shape[1::]
-    data_inputs = {'data': nd.zeros(data_shape, ctx=dev()),
-                   'softmax_label': nd.zeros((minibatch_size,), ctx=dev())}
+    data_inputs = {'data': nd.zeros(data_shape, ctx=dev(xpu)),
+                   'softmax_label': nd.zeros((minibatch_size,), ctx=dev(xpu))}
     initializer = mx.init.Xavier(factor_type="in", magnitude=2.34)
-    exe, sample_pool = SGLD(sym=net, dev=dev(), data_inputs=data_inputs, X=X, Y=Y,
+    exe, sample_pool = SGLD(sym=net, dev=dev(xpu), data_inputs=data_inputs, X=X, Y=Y,
                             X_test=X_test, Y_test=Y_test,
                             total_iter_num=1000000,
                             initializer=initializer,
                             learning_rate=4E-6, prior_precision=1.0, minibatch_size=100,
                             thin_interval=100, burn_in_iter_num=1000)
 
 
-def run_mnist_DistilledSGLD(training_num=50000):
+def run_mnist_DistilledSGLD(training_num=50000, xpu=0):
 
 Review comment:
   This means, by default, mx.gpu(0). Should it default to CPU instead by making xpu=None?
   

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