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reduce autotune search space (#3525) [skip ci]

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* reduce autotune search space

* consistent docstrings
This commit is contained in:
Wing Lian
2026-03-21 18:30:15 -04:00
committed by GitHub
parent b0294b3427
commit 2c05847a5f
1 changed files with 12 additions and 12 deletions
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24
src/axolotl/integrations/kernels/libs/scattermoe_lora/kernels/lora_ops.py
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@@ -363,7 +363,7 @@ def _scatter2scatter_lora_configs():
Search space:
BLOCK_M: {32, 64, 128}
BLOCK_N: {32, 64, 128, 256}
BLOCK_N: {32, 64}
BLOCK_K: {32, 64, 128}
num_warps: {4, 8}
num_stages: {3, 4, 5}
@@ -371,7 +371,7 @@ def _scatter2scatter_lora_configs():
configs = []
for block_m, block_n, block_k, warps, stages in product(
[32, 64, 128], # BLOCK_M
[32, 64, 128, 256], # BLOCK_N
[32, 64], # BLOCK_N
[32, 64, 128], # BLOCK_K
[4, 8], # num_warps
[3, 4, 5], # num_stages
@@ -943,16 +943,16 @@ def _scatter2scatter_lora_dX_configs():
Search space:
BLOCK_M: {32, 64, 128} (token tile)
BLOCK_K: {32, 64, 128, 256} (output tile)
BLOCK_N: {32, 64, 128, 256} (reduction tile)
BLOCK_K: {32, 64, 128} (output tile)
BLOCK_N: {32, 64} (reduction tile)
num_warps: {4, 8}
num_stages: {3, 4, 5}
"""
configs = []
for block_m, block_k, block_n, warps, stages in product(
[32, 64, 128], # BLOCK_M
[32, 64, 128, 256], # BLOCK_K (output dimension)
[32, 64, 128, 256], # BLOCK_N (reduction dimension)
[32, 64, 128], # BLOCK_K (output dimension)
[32, 64], # BLOCK_N (reduction dimension)
[4, 8], # num_warps
[3, 4, 5], # num_stages
):
@@ -1278,9 +1278,9 @@ def _group_bwd_lora_configs():
support GPUs with limited shared memory (e.g. ~99KB on some GPUs).
Search space:
BLOCK_M: {32, 64, 128, 256} (token-loop tile)
BLOCK_K: {32, 64, 128, 256}
BLOCK_N: {32, 64, 128, 256}
BLOCK_M: {32, 64, 128} (token-loop tile)
BLOCK_K: {32, 64, 128}
BLOCK_N: {32, 64}
num_warps: {4, 8}
num_stages: {3, 4, 5}
@@ -1289,9 +1289,9 @@ def _group_bwd_lora_configs():
"""
configs = []
for block_m, block_k, block_n, warps, stages in product(
[32, 64, 128, 256], # BLOCK_M
[32, 64, 128, 256], # BLOCK_K
[32, 64, 128, 256], # BLOCK_N
[32, 64, 128], # BLOCK_M
[32, 64, 128], # BLOCK_K
[32, 64], # BLOCK_N
[4, 8], # num_warps
[3, 4, 5], # num_stages
):