mseth10 commented on a change in pull request #13328: adding test for softmax
operator for large negative inputs
URL: https://github.com/apache/incubator-mxnet/pull/13328#discussion_r235278053
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File path: tests/python/unittest/test_operator.py
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@@ -4449,6 +4449,20 @@ def test_log_softmax():
check_symbolic_forward(sym, [data], [np.log(np_softmax(data,
axis=axis)+1e-20)])
check_numeric_gradient(sym, [data], rtol=0.05, atol=1e-3)
+def test_softmax_with_large_inputs():
+ def softmax_forward(input_data, true_output):
+ data = mx.sym.Variable('data')
+ out1 = data.softmax(axis=1)
+ exec1 = out1.bind(mx.cpu(), args={'data': input_data})
+ exec1.forward()[0].wait_to_read()
+ ndarr = exec1.outputs[0][0][0][0]
+ nparr = ndarr.asnumpy()
+ assert np.array_equal(nparr, true_output)
Review comment:
assert_almost_equal makes more sense as we are comparing floats here.
Corrected.
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