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authorjustheuristic <justheuristic@gmail.com>2022-09-18 01:02:13 +0300
committerjustheuristic <justheuristic@gmail.com>2022-09-18 01:02:13 +0300
commit4b4a9effd1fa88bc30bb1bc1e732d74e034c9d66 (patch)
tree263e4d5a9cec5ffbd1c8f14de08a104777b5bd4f /bitsandbytes
parent7906dc4c9a6d741699a561e03956f1f7ee4b8abc (diff)
debugprint
Diffstat (limited to 'bitsandbytes')
-rw-r--r--bitsandbytes/autograd/_functions.py6
1 files changed, 2 insertions, 4 deletions
diff --git a/bitsandbytes/autograd/_functions.py b/bitsandbytes/autograd/_functions.py
index 88a33a5..9928fbd 100644
--- a/bitsandbytes/autograd/_functions.py
+++ b/bitsandbytes/autograd/_functions.py
@@ -366,9 +366,8 @@ class MatMul8bitLt(torch.autograd.Function):
CxAt, SAt = F.transform(CAt, formatB, transpose=True)
C32grad, Sgrad = F.transform(Cgradt, "col32", transpose=True)
gradB32, SgradB32 = F.igemmlt(C32grad, CxAt, Sgrad, SAt)
- grad_B = F.mm_dequant(gradB32, SgradB32, SCgradt, SCAt).to(ctx.dtype_B)
+ grad_B = F.mm_dequant(gradB32, SgradB32, SCgradt, SCAt)
if state.threshold > 0.0 and subA is not None:
- assert False, idx
grad_B[:, idx] += torch.matmul(grad_output.t(), subA)
if req_gradA:
@@ -382,8 +381,7 @@ class MatMul8bitLt(torch.autograd.Function):
grad_A = F.mm_dequant(gradA32, SgradA32, SCgrad, state.SCBt).view(ctx.grad_shape).to(ctx.dtype_A)
elif state.CB is not None:
- CB = state.CB.to(ctx.dtype_B)
- CB.mul_(state.SCB.unsqueeze(1).div_(127.0).to(CB.dtype))
+ CB = state.CB.to(ctx.dtype_A, copy=True).mul_(state.SCB.unsqueeze(1).div(127.0))
grad_A = torch.matmul(grad_output, CB).view(ctx.grad_shape).to(ctx.dtype_A)
else:
raise Exception('State must contain either CBt or CB matrix for backward')