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Revert "[AMD][BugFix] Fix omission of wvSplitK kernel for small batc… Test #18

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Revert "[AMD][BugFix] Fix omission of wvSplitK kernel for small batc… Test #18

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32 changes: 4 additions & 28 deletions vllm/model_executor/layers/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,6 @@
from vllm import _custom_ops as ops
from vllm import envs
from vllm.platforms import current_platform
from vllm.utils import direct_register_custom_op


def get_token_bin_counts_and_mask(
Expand Down Expand Up @@ -71,10 +70,10 @@ def default_unquantized_gemm(layer: torch.nn.Module,
return torch.nn.functional.linear(x, weight, bias)


def rocm_unquantized_gemm_impl(
x: torch.Tensor,
weight: torch.Tensor,
bias: Optional[torch.Tensor] = None) -> torch.Tensor:
def rocm_unquantized_gemm(layer: torch.nn.Module,
x: torch.Tensor,
weight: torch.Tensor,
bias: Optional[torch.Tensor] = None):
from vllm.platforms.rocm import on_gfx9
k = weight.shape[1]
use_skinny = (envs.VLLM_ROCM_USE_SKINNY_GEMM and on_gfx9() and \
Expand All @@ -98,29 +97,6 @@ def rocm_unquantized_gemm_impl(
return torch.nn.functional.linear(x, weight, bias)


def rocm_unquantized_gemm_impl_fake(
x: torch.Tensor,
weight: torch.Tensor,
bias: Optional[torch.Tensor] = None) -> torch.Tensor:
return x.new_empty((*x.shape[:-1], weight.shape[0]))


def rocm_unquantized_gemm(layer: torch.nn.Module,
x: torch.Tensor,
weight: torch.Tensor,
bias: Optional[torch.Tensor] = None) -> torch.Tensor:
return torch.ops.vllm.rocm_unquantized_gemm_impl(x, weight, bias)


direct_register_custom_op(
op_name="rocm_unquantized_gemm_impl",
op_func=rocm_unquantized_gemm_impl,
mutates_args=[],
fake_impl=rocm_unquantized_gemm_impl_fake,
dispatch_key=current_platform.dispatch_key,
)


def cpu_unquantized_gemm(layer: torch.nn.Module,
x: torch.Tensor,
weight: torch.Tensor,
Expand Down