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f7dc16a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | """Shape-controlled BF16 GEMMs for inference.
Validated with CUDA 12.8 / PyTorch 2.8. This is not a guarantee
of bitwise reproducibility on other GPUs, shapes, or library versions.
Parameters keep nn.Linear's names and shapes for checkpoint compatibility.
"""
import torch
from torch.nn import functional as F
def _shape_linear(x, weight, bias, output_chunk_size=0, input_alignment=1):
padding = (-weight.shape[1]) % input_alignment
if padding:
x = F.pad(x, (0, padding))
# Do not detach/cache: gradients and newly loaded weights must propagate.
weight = F.pad(weight, (0, padding))
if output_chunk_size and weight.shape[0] > output_chunk_size:
weights = weight.split(output_chunk_size, dim=0)
biases = (
bias.split(output_chunk_size, dim=0)
if bias is not None else [None] * len(weights)
)
return torch.cat(
[F.linear(x, w, b) for w, b in zip(weights, biases)], dim=-1
)
return F.linear(x, weight, bias)
def compatible_linear(x, weight, bias=None, output_chunk_size=0, input_alignment=1):
# Match the validated patch's explicit CUDA BF16 path. Other dtypes retain
# their original linear/autocast behavior; there is no GPU-model dispatch.
if x.is_cuda and x.dtype == torch.bfloat16 and weight.dtype == torch.bfloat16:
return _shape_linear(x, weight, bias, output_chunk_size, input_alignment)
return F.linear(x, weight, bias)
class CompatibleLinear(torch.nn.Linear):
def __init__(self, in_features, out_features, bias=True, *,
output_chunk_size=0, input_alignment=1, device=None, dtype=None):
if output_chunk_size < 0 or input_alignment < 1:
raise ValueError("output_chunk_size must be >= 0 and input_alignment >= 1")
super().__init__(in_features, out_features, bias=bias, device=device, dtype=dtype)
self.output_chunk_size = output_chunk_size
self.input_alignment = input_alignment
def forward(self, x):
return compatible_linear(
x, self.weight, self.bias, self.output_chunk_size, self.input_alignment
)
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