Kernels:
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File size: 1,950 Bytes
098599e | 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 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | import torch
from kernels.benchmark import Benchmark
def setup_silu_tensors(self, num_tokens: int, hidden_dim: int, dtype=torch.float16):
self.x = torch.randn(num_tokens, 2 * hidden_dim, device="cuda", dtype=dtype)
self.out = torch.empty(num_tokens, hidden_dim, device="cuda", dtype=dtype)
def verify_silu(self):
d = self.x.shape[-1] // 2
ref = torch.nn.functional.silu(self.x[..., :d]) * self.x[..., d:]
return torch.allclose(self.out, ref, atol=1e-3, rtol=1e-3)
class SiluWorkloads(Benchmark):
kernel_id = "kernels-community/activation"
seed = 42
x: torch.Tensor # kernel specific input var
out: torch.Tensor # kernel specific output var
# Workload 1
def setup_small(self):
setup_silu_tensors(self, num_tokens=32, hidden_dim=256)
def benchmark_small(self):
self.kernel.silu_and_mul(self.out, self.x) # type: ignore
def verify_small(self):
return verify_silu(self)
# Workload 2
def setup_medium(self):
setup_silu_tensors(self, num_tokens=1024, hidden_dim=2048)
def benchmark_medium(self):
self.kernel.silu_and_mul(self.out, self.x) # type: ignore
def verify_medium(self):
return verify_silu(self)
class SiluWorkloads2(Benchmark):
kernel_id = "kernels-community/activation"
seed = 42
x: torch.Tensor # kernel specific input var
out: torch.Tensor # kernel specific output var
# Workload 1
def setup_small(self):
setup_silu_tensors(self, num_tokens=32, hidden_dim=256)
def benchmark_small(self):
self.kernel.silu_and_mul(self.out, self.x) # type: ignore
def verify_small(self):
return verify_silu(self)
# Workload 2
def setup_medium(self):
setup_silu_tensors(self, num_tokens=1024, hidden_dim=2048)
def benchmark_medium(self):
self.kernel.silu_and_mul(self.out, self.x) # type: ignore
# Note: show case without a verify
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