MekkCyber
commited on
Commit
·
679d8ed
1
Parent(s):
81d263b
fixing bindings
Browse files- activation/activation_kernels.cu +8 -9
- torch-ext/activation/__init__.py +11 -2
- torch-ext/activation/layers.py +20 -2
- torch-ext/torch_binding.cpp +12 -0
- torch-ext/torch_binding.h +6 -0
activation/activation_kernels.cu
CHANGED
@@ -226,16 +226,15 @@ void gelu_quick(torch::Tensor& out, // [..., d]
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}
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void gelu(torch::Tensor& out, // [..., d]
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torch::Tensor& input
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std::string approximation) // [..., d]
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{
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}
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void silu(torch::Tensor& out, // [..., d]
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}
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void gelu(torch::Tensor& out, // [..., d]
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torch::Tensor& input) // [..., d]
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{
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LAUNCH_ACTIVATION_KERNEL(vllm::gelu_kernel);
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}
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void gelu_tanh(torch::Tensor& out, // [..., d]
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torch::Tensor& input) // [..., d]
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{
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LAUNCH_ACTIVATION_KERNEL(vllm::gelu_tanh_kernel);
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}
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void silu(torch::Tensor& out, // [..., d]
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torch-ext/activation/__init__.py
CHANGED
@@ -30,8 +30,8 @@ def fatrelu_and_mul(out: torch.Tensor, x: torch.Tensor, threshold: float = 0.0)
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return out
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-
def gelu(out: torch.Tensor, x: torch.Tensor
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ops.gelu(out, x
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return out
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def silu(out: torch.Tensor, x: torch.Tensor) -> None:
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@@ -39,6 +39,11 @@ def silu(out: torch.Tensor, x: torch.Tensor) -> None:
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return out
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def gelu_fast(out: torch.Tensor, x: torch.Tensor) -> None:
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ops.gelu_fast(out, x)
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return out
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@@ -56,11 +61,15 @@ def gelu_quick(out: torch.Tensor, x: torch.Tensor) -> None:
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__all__ = [
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"silu_and_mul",
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"gelu_and_mul",
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"gelu_tanh_and_mul",
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"fatrelu_and_mul",
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"gelu_fast",
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"gelu_new",
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"gelu_quick",
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"layers",
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]
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return out
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def gelu(out: torch.Tensor, x: torch.Tensor) -> None:
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ops.gelu(out, x)
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return out
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def silu(out: torch.Tensor, x: torch.Tensor) -> None:
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return out
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def gelu_tanh(out: torch.Tensor, x: torch.Tensor) -> None:
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ops.gelu_tanh(out, x)
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return out
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def gelu_fast(out: torch.Tensor, x: torch.Tensor) -> None:
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ops.gelu_fast(out, x)
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return out
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__all__ = [
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"silu_and_mul",
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"mul_and_silu",
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"gelu_and_mul",
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"gelu_tanh_and_mul",
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"fatrelu_and_mul",
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"gelu_fast",
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"gelu_new",
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"gelu_quick",
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"gelu_tanh",
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"silu",
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"gelu",
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"layers",
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]
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torch-ext/activation/layers.py
CHANGED
@@ -52,11 +52,29 @@ class Gelu(nn.Module):
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can_torch_compile: bool = True
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def forward(self, x: torch.Tensor
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out = torch.empty_like(x)
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ops.gelu(out, x
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return out
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class MulAndSilu(nn.Module):
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"""An activation function for SwiGLU.
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can_torch_compile: bool = True
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def forward(self, x: torch.Tensor):
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out = torch.empty_like(x)
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ops.gelu(out, x)
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return out
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class GeluTanh(nn.Module):
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"""An activation function for GELU with `tanh` approximation.
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The function computes x -> gelu_tanh(x).
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Shapes:
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x: (num_tokens, d) or (batch_size, seq_len, d)
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return: (num_tokens, d) or (batch_size, seq_len, d)
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"""
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can_torch_compile: bool = True
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def forward(self, x: torch.Tensor):
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out = torch.empty_like(x)
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ops.gelu_tanh(out, x)
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return out
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class MulAndSilu(nn.Module):
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"""An activation function for SwiGLU.
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torch-ext/torch_binding.cpp
CHANGED
@@ -35,6 +35,18 @@ TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, ops) {
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// Quick GELU implementation.
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ops.def("gelu_quick(Tensor! out, Tensor input) -> ()");
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ops.impl("gelu_quick", torch::kCUDA, &gelu_quick);
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}
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REGISTER_EXTENSION(TORCH_EXTENSION_NAME)
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// Quick GELU implementation.
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ops.def("gelu_quick(Tensor! out, Tensor input) -> ()");
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ops.impl("gelu_quick", torch::kCUDA, &gelu_quick);
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// GELU with `tanh` approximation.
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ops.def("gelu_tanh(Tensor! out, Tensor input) -> ()");
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ops.impl("gelu_tanh", torch::kCUDA, &gelu_tanh);
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// SiLU implementation.
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ops.def("silu(Tensor! out, Tensor input) -> ()");
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ops.impl("silu", torch::kCUDA, &silu);
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// GELU with none approximation.
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ops.def("gelu(Tensor! out, Tensor input) -> ()");
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ops.impl("gelu", torch::kCUDA, &gelu);
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}
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REGISTER_EXTENSION(TORCH_EXTENSION_NAME)
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torch-ext/torch_binding.h
CHANGED
@@ -18,3 +18,9 @@ void gelu_new(torch::Tensor &out, torch::Tensor &input);
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void gelu_fast(torch::Tensor &out, torch::Tensor &input);
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void gelu_quick(torch::Tensor &out, torch::Tensor &input);
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void gelu_fast(torch::Tensor &out, torch::Tensor &input);
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void gelu_quick(torch::Tensor &out, torch::Tensor &input);
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void gelu_tanh(torch::Tensor &out, torch::Tensor &input);
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void silu(torch::Tensor &out, torch::Tensor &input);
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void gelu(torch::Tensor &out, torch::Tensor &input);
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