haojin2 commented on a change in pull request #11836: Support kAddTo for
softmax backward
URL: https://github.com/apache/incubator-mxnet/pull/11836#discussion_r210762558
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File path: tests/python/unittest/test_operator.py
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@@ -4486,13 +4486,18 @@ def test_where_numeric_gradient(shape, same_shape):
@with_seed()
def test_new_softmax():
for ndim in range(1, 5):
- for _ in range(5):
- shape = np.random.randint(1, 5, size=ndim)
- axis = np.random.randint(-ndim, ndim)
- data = np.random.uniform(-2, 2, size=shape)
- sym = mx.sym.softmax(axis=axis)
- check_symbolic_forward(sym, [data], [np_softmax(data, axis=axis)])
- check_numeric_gradient(sym, [data], rtol=0.05, atol=1e-3)
+ shape = np.random.randint(1, 5, size=ndim)
+ axis = np.random.randint(-ndim, ndim)
+ data = np.random.uniform(-2, 2, size=shape)
+ sym = mx.sym.softmax(axis=axis)
+ expected_fwd = np_softmax(data, axis=axis)
+ expected_bwd = np.zeros(shape)
+ check_symbolic_forward(sym, [data], [expected_fwd])
+ for req in ['add', 'write']:
Review comment:
Done
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