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add xpu tuning to CE #645

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Merged
shivam15s merged 2 commits into from
Apr 2, 2025
Merged

add xpu tuning to CE #645

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7316b0d
add xpu tuning to CE
mgrabban Apr 2, 2025
c382d81
fix style
mgrabban Apr 2, 2025
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5 changes: 3 additions & 2 deletions src/liger_kernel/ops/cross_entropy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
from liger_kernel.ops.utils import compare_version
from liger_kernel.ops.utils import element_mul_kernel
from liger_kernel.ops.utils import is_hip
from liger_kernel.utils import infer_device

if compare_version("triton", operator.ge, "3.0.0"):
try:
Expand Down Expand Up @@ -59,7 +60,7 @@ def liger_cross_entropy_kernel(
z_loss_ptr: Pointer to tensor to store the z loss. No operation if RETURN_Z_LOSS is 0.
loss_stride (int): The stride of the loss tensor.
n_cols (int): The number of columns in the input tensor.
n_non_ignore (flaot): The number of non-ignored elements in the batch.
n_non_ignore (float): The number of non-ignored elements in the batch.
sum_non_ignore_weight (float): The sum of non-ignored target's weights in the batch.
weight_sum (float): The sum of weight tensor.
ignore_index (int): The index to ignore in the target.
Expand Down Expand Up @@ -258,7 +259,7 @@ def liger_cross_entropy_kernel(
# The hard limit of TRITON_MAX_TENSOR_NUMEL is 1048576 https://github.com/triton-lang/triton/blob/ba42a5c68fd0505f8c42f4202d53be0f8d9a5fe0/python/triton/language/core.py#L19
# However, setting limit as 65536 as in LayerNorm tutorial is faster because of less register spilling
# The optimal maximum block size depends on your hardware, your kernel, and your dtype
MAX_FUSED_SIZE = 65536 // 2 # the best size we found by manually tuning
MAX_FUSED_SIZE = 4096 if infer_device() == "xpu" else 65536 // 2 # the best size we found by manually tuning


def cross_entropy_forward(
Expand Down
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