reminisce opened a new pull request #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361 This PR is implemented based upon the discussion with @eric-haibin-lin. It provides two APIs and NumPy-compatible NDArray indexing behavior, i.e. `y = x[i]`. 1. `set_numpy_comp(enable)` This is a thread-safe utility function for users to enable or disable NumPy-compatible behaviors in MXNet. This will generally affect the behavior of the following two operations: 1. NDArray indexing. When `enable=False`, NDArray indexing always returns a tensor with `ndim >= 1`, which is the default behavior of MXNet kept for backward compatibility. When `enable=True`, NDArray indexing will return a tensor with `ndim >= 0`, which is consistent with NumPy's indexing behavior. The result tensor with `ndim = 0` is actually a scalar whose shape is `()`. For example: >>> from mxnet.base import set_numpy_comp >>> x = mx.nd.arange(6) >>> x [0. 1. 2. 3. 4. 5.] <NDArray 6 @cpu(0)> >>> x[1] [1.] <NDArray 1 @cpu(0)> >>> set_numpy_comp(enable=True) >>> x[1] 1.0 <NDArray @cpu(0)> >>> set_numpy_comp(enable=False) >>> x[1] [1.] <NDArray 1 @cpu(0)> 2. NDArray's convenience fluent methods. When `enable=True`, the convenience fluent methods will dispatch the calls to NumPy operators if implemented in MXNet. For example, given an NDArray `data`, `data.sum()` will call `mxnet.ndarray.sum(data)` when `enable=False` (default behavior), and mxnet.numpy.sum(data)` when `enable=True`. 2. `_is_numpy_comp()` This is a thread-safe utility function for checking whether NumPy-compatibility has been enabled or disabled. This is implemented for developers to use. Users are not expected to call this function. @junrushao1994 @eric-haibin-lin @szha @zheng-da @yzhliu
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