sxjscience commented on issue #17327: np.ndarray indexing after hybridize URL: https://github.com/apache/incubator-mxnet/issues/17327#issuecomment-574875177 @ZheyuYe In terms of `mx.npx.pick` we can support multiple-dimensional selection as long as we are selecting the leading ones: ```python import mxnet as mx import mxnet.numpy as np mx.npx.set_np() a = mx.np.random.uniform(-1, 1, (10, 10, 5)) b = np.random.randint(0, 5, (10,)).broadcast_to((10, 10)) mx.npx.pick(a, b) ``` Also, would you provide a reproducible code snippet (like above) to mention which type of indexing operation is missing?
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