pengzhao-intel commented on a change in pull request #13328: adding test for
mkldnn softmax operator for large negative inputs
URL: https://github.com/apache/incubator-mxnet/pull/13328#discussion_r234864191
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File path: tests/python/mkl/test_mkldnn.py
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@@ -383,6 +383,17 @@ def check_fullyconnected_training(stype):
for stype in stypes:
check_fullyconnected_training(stype)
+def test_softmax_with_large_negative_inputs():
+ input_data = mx.nd.array([[[[-1e30,-1e30]]]])
+ data = mx.sym.Variable('data')
+ out1 = data.softmax(axis=1)
+ exec1 = out1.bind(mx.cpu(), args={'data': input_data, 'softmax_label':
mx.nd.ones([1]),
+ 'fc_weight': mx.nd.ones([2,2]),
'fc1_weight': mx.nd.ones([2,2])})
+ exec1.forward()[0].wait_to_read()
+ ndarr = exec1.outputs[0][0][0][0]
+ nparr = ndarr.asnumpy()
+ assert(np.isnan(nparr).any(), False)
Review comment:
Could you build other corner cases to cover more, such as 1e-30 as input and
other possible combinations?
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