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Mojo struct

BFloat16Encoding

The bfloat16 quantization encoding.

Like float32, the bfloat16 encoding uses 8 bits to store the exponent value, so it has the same numeric range as float32. However, it has just 7 bits for the mantissa (compared to 23 bits available in float32), so it has less precision for the fractional part. This is often a better trade-off for ML applications, compared to traditional float16, which has less numeric range because it uses only 5 bits to store the exponent (though it has better precision with 10 bits for the mantissa).

Because this holds the quantized data in a special packing format, it currently does not print float values at runtime—it's just a bag of bits in uint8 format.

Implemented traits​

AnyType, QuantizationEncoding

Methods​

quantize​

static quantize(tensor: Tensor[float32]) -> Tensor[uint8]

Quantizes the full-precision input tensor to bfloat16.

Only supports quantizing from float16 and float32, using a direct elementwise cast.

Args:

  • ​tensor (Tensor[float32]): Full-precision tensor to quantize to bfloat16.

Returns:

Quantized bfloat16 tensor. The tensor datatype is uint8 because this is simply a byte buffer. Each scalar is actually encoded into two bytes (16-bits).

id​

static id() -> String

Identifier for the bfloat16 quantized encoding.

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