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OpenDAS
vllm_cscc
Commits
083b80ea
"lib/vscode:/vscode.git/clone" did not exist on "923e1ee729605a5c3abf2e43b535e9b2da90e771"
Commit
083b80ea
authored
Jan 16, 2025
by
zhuwenwen
Browse files
增加w8a8相关修改
parent
09428eec
Changes
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+6750
-381
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_4096_4096_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_4096_4096_K100_AI.json
+417
-363
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_4608_3584_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_4608_3584_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_13824_K100_AI.json
...rs/quantization/configs/w8a8/W8A8_5120_13824_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_2560_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_5120_2560_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_5120_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_5120_5120_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_6912_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_5120_6912_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_8192_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_5120_8192_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_6144_4096_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_6144_4096_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_7168_8192_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_7168_8192_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_7680_5120_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_7680_5120_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_1024_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_1024_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_14336_K100_AI.json
...rs/quantization/configs/w8a8/W8A8_8192_14336_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_2048_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_2048_K100_AI.json
+436
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_3584_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_3584_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_4096_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_4096_K100_AI.json
+418
-0
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_7168_K100_AI.json
...ers/quantization/configs/w8a8/W8A8_8192_7168_K100_AI.json
+427
-0
vllm/model_executor/layers/quantization/utils/w8a8_utils.py
vllm/model_executor/layers/quantization/utils/w8a8_utils.py
+27
-14
vllm/model_executor/models/falcon.py
vllm/model_executor/models/falcon.py
+1
-1
vllm/model_executor/models/llama.py
vllm/model_executor/models/llama.py
+5
-1
vllm/model_executor/models/qwen.py
vllm/model_executor/models/qwen.py
+3
-2
No files found.
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_4096_4096_K100_AI.json
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_4608_3584_K100_AI.json
0 → 100644
View file @
083b80ea
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_13824_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_2560_K100_AI.json
0 → 100644
View file @
083b80ea
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_5120_K100_AI.json
0 → 100644
View file @
083b80ea
{
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_6912_K100_AI.json
0 → 100644
View file @
083b80ea
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_5120_8192_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_6144_4096_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_7168_8192_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_7680_5120_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_1024_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_14336_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_2048_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_3584_K100_AI.json
0 → 100644
View file @
083b80ea
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\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_4096_K100_AI.json
0 → 100644
View file @
083b80ea
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}
\ No newline at end of file
vllm/model_executor/layers/quantization/configs/w8a8/W8A8_8192_7168_K100_AI.json
0 → 100644
View file @
083b80ea
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"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/layers/quantization/utils/w8a8_utils.py
View file @
083b80ea
...
...
@@ -238,27 +238,40 @@ def apply_int8_linear(
m
=
x_q
.
shape
[
0
]
k
=
x_q
.
shape
[
1
]
n
=
weight
.
shape
[
1
]
if
f
"
{
m
}
_
{
n
}
_
{
k
}
"
in
W8A8_TRITONJSON
.
triton_json_dict
[
0
]:
best_config
=
W8A8_TRITONJSON
.
triton_json_dict
[
0
][
f
"
{
m
}
_
{
n
}
_
{
k
}
"
]
#print("json files:",best_config)
elif
f
"1_
{
n
}
_
{
k
}
"
in
W8A8_TRITONJSON
.
triton_json_dict
[
0
]:
if
m
<
64
:
m_
=
32
elif
m
<
128
:
m_
=
64
elif
m
<
256
:
m_
=
128
elif
m
<
512
:
#print("m:{},n:{},k:{}".format(m,n,k))
if
f
"1_
{
n
}
_
{
k
}
"
in
W8A8_TRITONJSON
.
triton_json_dict
[
0
]:
if
m
<=
16
:
m_
=
m
#best_config=W8A8_TRITONJSON.triton_json_dict[0][f"{m}_{n}_{k}"]
elif
m
<=
64
:
m_
=
(
m
+
3
)
&
-
4
#取值到最近的4的倍数
elif
m
<=
160
:
m_
=
(
m
+
7
)
&
-
8
elif
m
<
200
:
#256
m_
=
160
elif
m
<
480
:
#512
m_
=
256
elif
m
<
1024
:
elif
m
<
960
:
#
1024
m_
=
512
el
se
:
el
if
m
<
2048
:
m_
=
1024
elif
m
<
4096
:
m_
=
2048
elif
m
<
6000
:
m_
=
4096
else
:
m_
=
8192
best_config
=
W8A8_TRITONJSON
.
triton_json_dict
[
0
][
f
"
{
m_
}
_
{
n
}
_
{
k
}
"
]
else
:
best_config
=
None
print
(
"config not found!"
)
# if best_config==None:
# print("m:{},n:{},k:{}".format(m,n,k))
# print("config not found!")
return
ops
.
triton_scaled_mm
(
x_q
,
weight
,
...
...
vllm/model_executor/models/falcon.py
View file @
083b80ea
...
...
@@ -462,7 +462,7 @@ class FalconForCausalLM(nn.Module, SupportsPP):
self
.
use_gemm_pad
=
os
.
environ
.
get
(
'GEMM_PAD'
)
==
'1'
self
.
use_fa_pad
=
os
.
environ
.
get
(
'FA_PAD'
)
==
'1'
self
.
use_awq_pad
=
os
.
environ
.
get
(
'AWQ_PAD'
)
==
'1'
self
.
w8a8_strategy
=
int
(
os
.
getenv
(
'W8A8_SUPPORT_METHODS'
,
'
0
'
))
self
.
w8a8_strategy
=
int
(
os
.
getenv
(
'W8A8_SUPPORT_METHODS'
,
'
1
'
))
def
get_input_embeddings
(
self
,
input_ids
:
torch
.
Tensor
)
->
torch
.
Tensor
:
return
self
.
transformer
.
get_input_embeddings
(
input_ids
)
...
...
vllm/model_executor/models/llama.py
View file @
083b80ea
...
...
@@ -355,7 +355,7 @@ class LlamaModel(nn.Module):
self
.
use_gemm_pad
=
os
.
environ
.
get
(
'GEMM_PAD'
)
==
'1'
self
.
use_fa_pad
=
os
.
environ
.
get
(
'FA_PAD'
)
==
'1'
self
.
use_awq_pad
=
os
.
environ
.
get
(
'AWQ_PAD'
)
==
'1'
self
.
w8a8_strategy
=
int
(
os
.
getenv
(
'W8A8_SUPPORT_METHODS'
,
'
0
'
))
self
.
w8a8_strategy
=
int
(
os
.
getenv
(
'W8A8_SUPPORT_METHODS'
,
'
1
'
))
def
get_input_embeddings
(
self
,
input_ids
:
torch
.
Tensor
)
->
torch
.
Tensor
:
return
self
.
embed_tokens
(
input_ids
)
...
...
@@ -553,6 +553,10 @@ class LlamaModel(nn.Module):
if
matches
and
"scale"
not
in
layername
:
weight_data
=
params_dict
[
layername
]
n
=
weight_data
.
shape
[
0
]
# k=weight_data.shape[1]
# #判断当前size是否在优化的范围内，假如存在则走triton，假如不存在则走rocblas
# json_file=self.tritonsingleton.get_w8a8json_name(n,k)
#rocblas和cutlass目前都需要weight做处理，但是triton不用
if
self
.
w8a8_strategy
!=
1
:
...
...
vllm/model_executor/models/qwen.py
View file @
083b80ea
...
...
@@ -913,12 +913,13 @@ class QWenBaseModel(nn.Module, SupportsPP, SupportsLoRA):
if
quant_config
is
not
None
:
self
.
quant_method
=
quant_config
.
get_name
()
self
.
quant_config
=
quant_config
self
.
tritonsingleton
=
W8a8GetCacheJSON
()
self
.
use_llama_nn
=
os
.
environ
.
get
(
'LLAMA_NN'
)
==
'1'
self
.
use_gemm_pad
=
os
.
environ
.
get
(
'GEMM_PAD'
)
==
'1'
self
.
use_fa_pad
=
os
.
environ
.
get
(
'FA_PAD'
)
==
'1'
self
.
use_awq_pad
=
os
.
environ
.
get
(
'AWQ_PAD'
)
==
'1'
self
.
w8a8_strategy
=
int
(
os
.
getenv
(
'W8A8_SUPPORT_METHODS'
,
'
0
'
))
self
.
w8a8_strategy
=
int
(
os
.
getenv
(
'W8A8_SUPPORT_METHODS'
,
'
1
'
))
def
_get_image_input_type
(
self
,
...
...
@@ -1147,7 +1148,7 @@ class QWenBaseModel(nn.Module, SupportsPP, SupportsLoRA):
m
=
int
(
key
.
split
(
'_'
)[
0
])
n
=
int
(
key
.
split
(
'_'
)[
1
])
k
=
int
(
key
.
split
(
'_'
)[
2
])
ops
.
_int8_gemm_helper
(
m
=
m
,
n
=
n
,
k
=
k
,
per_token_act_quant
=
True
,
per_out_channel_weight_quant
=
True
,
use_bias
=
False
,
best_config
=
value
)
ops
.
triton
_int8_gemm_helper
(
m
=
m
,
n
=
n
,
k
=
k
,
per_token_act_quant
=
True
,
per_out_channel_weight_quant
=
True
,
use_bias
=
False
,
best_config
=
value
)
return
loaded_params
...
...
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