sandeep-krishnamurthy opened a new issue #11349: Infer shape partial returns () after slice / slice_axis operations URL: https://github.com/apache/incubator-mxnet/issues/11349 Code snippet ``` var1 = mx.sym.var(name="data", shape=(0,20)) var2 = mx.sym.slice(var1,begin=(None, None), end=(None,10)) var2.infer_shape_partial() # Actual Output : ([(0, 20)], [()], []) # Expected Output: ([(0, 20)], [(0,10)], []) ``` Same behavior for `slice_axis` and `slice` operators. To summarize: Even if one dimension is 0 (i.e., unknown), infer shape partial returns empty tuple. However, note that if you use other operators like broadcast_add() broadcast_sub() etc. will return expected output on infer_shape_partial(). Per @reminisce - This is a buggy behavior in few operators. https://github.com/apache/incubator-mxnet/blob/master/src/operator/tensor/matrix_op-inl.h#L693 => This makes it return early than try to infer partial shapes. This is a blocking issue in keras-mxnet for users who use slice operator and custom loss functionality. @rahul003
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