bfloat16 Datatype Support Status
Overview
bfloat16 (BF16) is a new floating-point format that can accelerate machine learning (deep learning training, in particular) algorithms.
FP16 format has 5 bits of exponent and 10 bits of mantissa, while BF16 has 8 bits of exponent and 7 bits of mantissa. Compared to FP32, while reducing the precision (only 7 bits mantissa), BF16 retains a range that is similar to FP32, which makes it appropriate for deep learning training.
Support List
When computing with tensors of bfloat16 data type, the operators used must also support bfloat16 data type. Currently, only Ascend backend has adapted operators.
The bfloat16 data type does not support implicit type conversion, that is, when the data types of parameters are inconsistent, the bfloat16 precision type will not be automatically converted to a higher precision type.
API Name |
Ascend |
Descriptions |
Version |
|---|---|---|---|
❌ |
Since numpy does not support bfloat16 data type, it is not possible to convert a tensor of bfloat16 type to numpy type. |
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✔️ |
When using the auto-mixed-precision interface, you can specify bfloat16 as the low-precision data type. |
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✔️ |
When using the custom-mixed-precision interface, you can specify bfloat16 as the low-precision data type. |
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✔️ |
2.2.10 |
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✔️ |
2.2.10 |
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✔️ |
2.2.10 |
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✔️ |
2.2.10 |
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✔️ |
2.2.0 |
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✔️ |
2.2.0 |
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✔️ |
2.2.0 |
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✔️ |
2.2.10 |
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✔️ |
2.2.0 |
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✔️ |
2.2.0 |
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✔️ |
2.2.0 |
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✔️ |
2.2.0 |
The overall bfloat16 datatype capability is currently supported, and more operators will be added to support the bfloat16 datatype.