ZhennanQin commented on a change in pull request #17265: Add bfloat16
floating-point format support based on AMP
URL: https://github.com/apache/incubator-mxnet/pull/17265#discussion_r365519649
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File path: python/mxnet/contrib/amp/amp.py
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@@ -43,14 +44,17 @@
from ... import optimizer as opt
from .loss_scaler import LossScaler
+bfloat16 = np.dtype([('bfloat16', np.uint16)])
Review comment:
This is a good topic, and I want to have a discussion for this.
Currently, MXNet doesn't have its own type system. It's simply using
Numpy.dtype. Numpy doesn't natively support bfloat16, so we define bfloat16 as
a numpy customized type.
Pros: compatible with current design, isinstance(bfloat16, np.dtype) could
return True.
cons: bfloat16.name doesn't work, have to use bfloat16.names[0] instead.
Another solution is, creating MXNet's own data type system, just like
pytorch and tf. This is a big API change, so we wish this can be done when
upgrading to MXNet 2.0.
Currently, we prefer this approach to enable bfloat16 in MXNet 1.x, and
refactor it in MXNet 2.0.
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