Fixing rocm. (#2021)
# What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
This commit is contained in:
parent
8aece3bd68
commit
0a94fad79f
|
@ -126,40 +126,34 @@ if ENGINE != "triton":
|
|||
import flash_attn_2_cuda
|
||||
|
||||
logger.info("ROCm: using Flash Attention 2 Composable Kernel implementation.")
|
||||
except ImportError:
|
||||
try:
|
||||
import flash_attn_cuda
|
||||
except ImportError as e:
|
||||
if major >= 8:
|
||||
architecture_suffix = f"-{SYSTEM}"
|
||||
raise ImportError(
|
||||
"Flash Attention V2 is not installed.\n"
|
||||
"Use the official Docker image (ghcr.io/huggingface/text-generation-inference:latest) "
|
||||
f"or install flash attention v2 with `cd server && make install install-flash-attention-v2{architecture_suffix}`"
|
||||
)
|
||||
elif is_sm75:
|
||||
raise ImportError(
|
||||
"Flash Attention is not installed.\n"
|
||||
"Use the official Docker image (ghcr.io/huggingface/text-generation-inference:latest) "
|
||||
"or install flash attention with `cd server && make install install-flash-attention`"
|
||||
) from e
|
||||
else:
|
||||
|
||||
ENGINE = "v1"
|
||||
logger.info("ROCm: using Flash Attention 1")
|
||||
except ImportError as e:
|
||||
if major >= 8:
|
||||
architecture_suffix = f"-{SYSTEM}"
|
||||
raise ImportError(
|
||||
"Flash Attention V2 is not installed.\n"
|
||||
"Use the official Docker image (ghcr.io/huggingface/text-generation-inference:latest) "
|
||||
f"or install flash attention v2 with `cd server && make install install-flash-attention-v2{architecture_suffix}`"
|
||||
)
|
||||
elif is_sm75:
|
||||
raise ImportError(
|
||||
"Flash Attention is not installed.\n"
|
||||
"Use the official Docker image (ghcr.io/huggingface/text-generation-inference:latest) "
|
||||
"or install flash attention with `cd server && make install install-flash-attention`"
|
||||
) from e
|
||||
else:
|
||||
|
||||
for idx in range(torch.cuda.device_count()):
|
||||
name = torch.cuda.get_device_name(idx)
|
||||
if "MI210" not in name and "MI250" not in name:
|
||||
raise ImportError(
|
||||
f"AMD GPU {torch.cuda.get_device_name(idx)} does not support flash-attention"
|
||||
)
|
||||
raise ImportError(
|
||||
f"AMD GPU with ROCm capability {major} {minor} is not supported"
|
||||
) from e
|
||||
for idx in range(torch.cuda.device_count()):
|
||||
name = torch.cuda.get_device_name(idx)
|
||||
if "MI210" not in name and "MI250" not in name:
|
||||
raise ImportError(
|
||||
f"AMD GPU {torch.cuda.get_device_name(idx)} does not support flash-attention"
|
||||
)
|
||||
raise ImportError(
|
||||
f"AMD GPU with ROCm capability {major} {minor} is not supported"
|
||||
) from e
|
||||
|
||||
|
||||
SUPPORTS_WINDOWING = ENGINE != "v1"
|
||||
SUPPORTS_WINDOWING = False
|
||||
if ENGINE == "ck":
|
||||
|
||||
def attention(
|
||||
|
@ -186,17 +180,12 @@ if ENGINE == "ck":
|
|||
out,
|
||||
cu_seqlens,
|
||||
cu_seqlens,
|
||||
None,
|
||||
None,
|
||||
None,
|
||||
max_s,
|
||||
max_s,
|
||||
0.0,
|
||||
softmax_scale,
|
||||
False,
|
||||
causal,
|
||||
window_size_left,
|
||||
0,
|
||||
False,
|
||||
None,
|
||||
)
|
||||
|
@ -234,62 +223,4 @@ elif ENGINE == "triton":
|
|||
return output
|
||||
|
||||
else:
|
||||
|
||||
def attention(
|
||||
q,
|
||||
k,
|
||||
v,
|
||||
out,
|
||||
cu_seqlens,
|
||||
max_s,
|
||||
softmax_scale,
|
||||
window_size_left=-1,
|
||||
):
|
||||
if window_size_left != -1:
|
||||
raise NotImplementedError(
|
||||
"window_size_left is only available with flash attn v2"
|
||||
)
|
||||
|
||||
# Flash attention v1 requires q, k and v to have the same number of heads
|
||||
if k.shape[1] != q.shape[1]:
|
||||
# MQA expand
|
||||
if k.shape[1] == 1:
|
||||
k = k.expand(-1, q.shape[1], -1)
|
||||
# Grouped attention reshape
|
||||
else:
|
||||
original_shape = k.shape
|
||||
k = (
|
||||
k.unsqueeze(2)
|
||||
.expand(-1, -1, q.shape[1] // k.shape[1], -1)
|
||||
.reshape(original_shape[0], -1, original_shape[2])
|
||||
)
|
||||
if v.shape[1] != q.shape[1]:
|
||||
# MQA expand
|
||||
if v.shape[1] == 1:
|
||||
v = v.expand(-1, q.shape[1], -1)
|
||||
# Grouped attention reshape
|
||||
else:
|
||||
original_shape = v.shape
|
||||
v = (
|
||||
v.unsqueeze(2)
|
||||
.expand(-1, -1, q.shape[1] // v.shape[1], -1)
|
||||
.reshape(original_shape[0], -1, original_shape[2])
|
||||
)
|
||||
|
||||
return flash_attn_cuda.fwd(
|
||||
q,
|
||||
k,
|
||||
v,
|
||||
out,
|
||||
cu_seqlens,
|
||||
cu_seqlens,
|
||||
max_s,
|
||||
max_s,
|
||||
0.0,
|
||||
softmax_scale,
|
||||
False,
|
||||
True,
|
||||
False,
|
||||
0,
|
||||
None,
|
||||
)
|
||||
raise RuntimeError(f"Unknown attention engine {ENGINE}")
|
||||
|
|
Loading…
Reference in New Issue