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OpenDAS
vllm_cscc
Commits
0a130908
Commit
0a130908
authored
Feb 28, 2025
by
zhuwenwen
Browse files
Merge branch 'v0.7.2-dev-w8a8' into 'v0.7.2-dev'
V0.7.2 dev w8a8 See merge request dcutoolkit/deeplearing/vllm!76
parents
6b7651af
6fd8c21b
Changes
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17 changed files
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5054 deletions
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_5120_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_5120_5120_K100_AI.json
+0
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_6912_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_5120_6912_K100_AI.json
+0
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_8192_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_5120_8192_K100_AI.json
+0
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_6144_4096_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_6144_4096_K100_AI.json
+0
-418
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_7168_8192_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_7168_8192_K100_AI.json
+0
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_7680_5120_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_7680_5120_K100_AI.json
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_1024_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_1024_K100_AI.json
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_14336_K100_AI.json
...rs/quantization/configs/w8a8/W8A8_8192_14336_K100_AI.json
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_2048_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_2048_K100_AI.json
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_3584_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_3584_K100_AI.json
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_4096_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_4096_K100_AI.json
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_7168_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_7168_K100_AI.json
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vllm/model_executor/models/gpt_neox.py
vllm/model_executor/models/gpt_neox.py
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vllm/model_executor/models/llama.py
vllm/model_executor/models/llama.py
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-1
vllm/model_executor/models/qwen.py
vllm/model_executor/models/qwen.py
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vllm/model_executor/models/qwen2.py
vllm/model_executor/models/qwen2.py
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vllm/utils.py
vllm/utils.py
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_5120_K100_AI.json
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_8192_K100_AI.json
deleted
100644 → 0
View file @
6b7651af
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_6144_4096_K100_AI.json
deleted
100644 → 0
View file @
6b7651af
{
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_7168_8192_K100_AI.json
deleted
100644 → 0
View file @
6b7651af
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vllm/model_executor/layers/quantization/configs/w8a8/W8A8_7680_5120_K100_AI.json
deleted
100644 → 0
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_1024_K100_AI.json
deleted
100644 → 0
View file @
6b7651af
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_14336_K100_AI.json
deleted
100644 → 0
View file @
6b7651af
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_2048_K100_AI.json
deleted
100644 → 0
View file @
6b7651af
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_3584_K100_AI.json
deleted
100644 → 0
View file @
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_4096_K100_AI.json
deleted
100644 → 0
View file @
6b7651af
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_7168_K100_AI.json
deleted
100644 → 0
View file @
6b7651af
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0
,
"num_warps"
:
4
},
"24"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
4
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"28"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"32"
:
{
"BLOCK_SIZE_M"
:
16
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
4
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"36"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"40"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"44"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"48"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"52"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"56"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"60"
:
{
"BLOCK_SIZE_M"
:
32
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"64"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
64
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
4
},
"72"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"80"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"88"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"96"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"104"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"112"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"120"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"128"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"136"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
4
,
"SPLIT_K"
:
1
,
"num_stages"
:
1
,
"num_warps"
:
4
},
"144"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
1
,
"num_warps"
:
4
},
"152"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
1
,
"num_warps"
:
4
},
"160"
:
{
"BLOCK_SIZE_M"
:
64
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
4
,
"SPLIT_K"
:
1
,
"num_stages"
:
1
,
"num_warps"
:
4
},
"256"
:
{
"BLOCK_SIZE_M"
:
128
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
256
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"512"
:
{
"BLOCK_SIZE_M"
:
256
,
"BLOCK_SIZE_N"
:
128
,
"BLOCK_SIZE_K"
:
128
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"1024"
:
{
"BLOCK_SIZE_M"
:
256
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
64
,
"GROUP_SIZE_M"
:
2
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"2048"
:
{
"BLOCK_SIZE_M"
:
256
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
64
,
"GROUP_SIZE_M"
:
4
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"4096"
:
{
"BLOCK_SIZE_M"
:
256
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
64
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
},
"8192"
:
{
"BLOCK_SIZE_M"
:
256
,
"BLOCK_SIZE_N"
:
256
,
"BLOCK_SIZE_K"
:
64
,
"GROUP_SIZE_M"
:
8
,
"SPLIT_K"
:
1
,
"num_stages"
:
0
,
"num_warps"
:
8
}
}
}
\ No newline at end of file
vllm/model_executor/models/gpt_neox.py
View file @
0a130908
...
...
@@ -370,7 +370,8 @@ class GPTNeoXForCausalLM(nn.Module, SupportsPP):
combined_words
=
"|"
.
join
(
lay_key_words
)
weight_shapes
=
[]
all_json
=
{}
matched_key_words
=
set
()
for
layername
,
weight
in
params_dict
.
items
():
matches
=
re
.
findall
(
combined_words
,
layername
)
if
matches
and
"scale"
not
in
layername
:
...
...
@@ -384,20 +385,19 @@ class GPTNeoXForCausalLM(nn.Module, SupportsPP):
weight_data
.
data
.
copy_
(
_weight
)
#下面是针对模型记录模型出现k和n值
elif
len
(
weight_shapes
)
<
4
:
#k=weight_data.shape[1]
#print("n:{},k:{}".format(n,k))
elif
len
(
matched_key_words
)
<
4
and
matches
[
0
]
not
in
matched_key_words
:
matched_key_words
.
add
(
matches
[
0
])
weight_shapes
.
append
({
n
,
k
})
json_file
=
self
.
tritonsingleton
.
get_w8a8json_name
(
n
,
k
)
configs_dict
=
self
.
tritonsingleton
.
get_triton_cache
(
json_file
,
n
,
k
)
if
configs_dict
:
all_json
.
update
(
configs_dict
)
#("weight_shapes:",weight_shapes)
if
self
.
w8a8_strategy
==
1
:
self
.
tritonsingleton
.
triton_json_dict
.
append
(
all_json
)
#print("self.tritonsingleton.triton_json_dict:",self.tritonsingleton.triton_json_dict)
#找到的所有config都进行一次warmup
for
key
,
value
in
all_json
.
items
():
m
=
int
(
key
.
split
(
'_'
)[
0
])
...
...
vllm/model_executor/models/llama.py
View file @
0a130908
...
...
@@ -562,6 +562,7 @@ class LlamaModel(nn.Module):
combined_words
=
"|"
.
join
(
lay_key_words
)
weight_shapes
=
[]
all_json
=
{}
matched_key_words
=
set
()
for
layername
,
weight
in
params_dict
.
items
():
matches
=
re
.
findall
(
combined_words
,
layername
)
...
...
@@ -579,7 +580,8 @@ class LlamaModel(nn.Module):
weight_data
.
data
.
copy_
(
_weight
)
#下面是针对模型记录模型出现k和n值
elif
len
(
weight_shapes
)
<
4
:
elif
len
(
matched_key_words
)
<
4
and
matches
[
0
]
not
in
matched_key_words
:
matched_key_words
.
add
(
matches
[
0
])
k
=
weight_data
.
shape
[
1
]
weight_shapes
.
append
({
n
,
k
})
...
...
vllm/model_executor/models/qwen.py
View file @
0a130908
...
...
@@ -1185,6 +1185,7 @@ class QWenBaseModel(nn.Module, SupportsPP, SupportsLoRA):
combined_words
=
"|"
.
join
(
lay_key_words
)
weight_shapes
=
[]
all_json
=
{}
matched_key_words
=
set
()
for
layername
in
loaded_params
:
weight
=
params_dict
[
layername
]
...
...
@@ -1199,7 +1200,8 @@ class QWenBaseModel(nn.Module, SupportsPP, SupportsLoRA):
weight_data
.
data
.
copy_
(
_weight
)
#下面是针对模型记录模型出现k和n值
elif
len
(
weight_shapes
)
<
4
:
elif
len
(
matched_key_words
)
<
4
and
matches
[
0
]
not
in
matched_key_words
:
matched_key_words
.
add
(
matches
[
0
])
k
=
weight_data
.
shape
[
1
]
weight_shapes
.
append
({
n
,
k
})
...
...
vllm/model_executor/models/qwen2.py
View file @
0a130908
...
...
@@ -539,6 +539,7 @@ class Qwen2Model(nn.Module):
combined_words
=
"|"
.
join
(
lay_key_words
)
weight_shapes
=
[]
all_json
=
{}
matched_key_words
=
set
()
for
layername
in
loaded_params
:
weight
=
params_dict
[
layername
]
...
...
@@ -553,7 +554,8 @@ class Qwen2Model(nn.Module):
weight_data
.
data
.
copy_
(
_weight
)
#下面是针对模型记录模型出现k和n值
elif
len
(
weight_shapes
)
<
4
:
elif
len
(
matched_key_words
)
<
4
and
matches
[
0
]
not
in
matched_key_words
:
matched_key_words
.
add
(
matches
[
0
])
k
=
weight_data
.
shape
[
1
]
weight_shapes
.
append
({
n
,
k
})
...
...
vllm/utils.py
View file @
0a130908
...
...
@@ -1534,8 +1534,6 @@ class W8a8GetCacheJSON:
def
_initialize
(
self
):
current_folder_path
=
os
.
path
.
dirname
(
os
.
path
.
abspath
(
__file__
))
json_folder_path
=
current_folder_path
+
'/../lmslim/configs/w8a8'
if
not
os
.
path
.
exists
(
json_folder_path
):
json_folder_path
=
current_folder_path
+
'/model_executor/layers/quantization/configs/w8a8'
self
.
triton_json_dir
=
(
os
.
getenv
(
'TRITON_JSON_DIR'
,
json_folder_path
))
self
.
triton_json_dict
=
[]
...
...
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