TaoLv commented on issue #15930: Fix dtype inference in arange_like operator URL: https://github.com/apache/incubator-mxnet/pull/15930#issuecomment-523068244 @eric-haibin-lin do you think the below code snippet can be used as a test case? ```python import mxnet as mx import numpy as np dtypes = [np.float16, np.float32, np.float64] for t in dtypes: x = mx.sym.Variable('x', dtype=t) y = mx.sym.reshape(x, shape=(0, 0, -1)) z = mx.sym.contrib.arange_like(y, axis=-1) mod = z.simple_bind(ctx=mx.gpu(0), x=(3, 4, 5, 6), graph_req='null') mod.arg_arrays[0][:] = np.random.normal(size=mod.arg_arrays[0].shape).astype(t) out = mod.forward(is_train=False) assert out[0].dtype == np.float32 ```
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