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4a50c963
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4a50c963
编写于
10月 22, 2023
作者:
V
v0xie
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电子邮件补丁
差异文件
refactor: remove used OFT functions
上级
de8ee92e
变更
1
隐藏空白更改
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并排
Showing
1 changed file
with
10 addition
and
72 deletion
+10
-72
extensions-builtin/Lora/network_oft.py
extensions-builtin/Lora/network_oft.py
+10
-72
未找到文件。
extensions-builtin/Lora/network_oft.py
浏览文件 @
4a50c963
...
...
@@ -29,98 +29,36 @@ class NetworkModuleOFT(network.NetworkModule):
self
.
block_size
=
self
.
out_dim
//
self
.
num_blocks
self
.
org_module
:
list
[
torch
.
Module
]
=
[
self
.
sd_module
]
#self.org_weight = self.org_module[0].weight.to(self.org_module[0].weight.device, copy=True)
init_multiplier
=
self
.
multiplier
()
*
self
.
calc_scale
()
self
.
last_multiplier
=
init_multiplier
self
.
R
=
self
.
get_weight
(
self
.
oft_blocks
,
init_multiplier
)
self
.
hooks
=
[]
self
.
merged_weight
=
self
.
merge_weight
()
#self.apply_to()
self
.
applied
=
False
self
.
merged
=
False
def
merge_weight
(
self
):
org_weight
=
self
.
org_module
[
0
].
weight
R
=
self
.
R
.
to
(
org_weight
.
device
,
dtype
=
org_weight
.
dtype
)
def
merge_weight
(
self
,
R_weight
,
org_weight
):
R_weight
=
R_weight
.
to
(
org_weight
.
device
,
dtype
=
org_weight
.
dtype
)
if
org_weight
.
dim
()
==
4
:
weight
=
torch
.
einsum
(
"oihw, op -> pihw"
,
org_weight
,
R
)
weight
=
torch
.
einsum
(
"oihw, op -> pihw"
,
org_weight
,
R
_weight
)
else
:
weight
=
torch
.
einsum
(
"oi, op -> pi"
,
org_weight
,
R
)
weight
=
torch
.
einsum
(
"oi, op -> pi"
,
org_weight
,
R
_weight
)
return
weight
def
replace_weight
(
self
,
new_weight
):
org_sd
=
self
.
org_module
[
0
].
state_dict
()
org_sd
[
'weight'
]
=
new_weight
self
.
org_module
[
0
].
load_state_dict
(
org_sd
)
self
.
merged
=
True
def
restore_weight
(
self
):
pass
#org_sd = self.org_module[0].state_dict()
#org_sd['weight'] = self.org_weight
#self.org_module[0].load_state_dict(org_sd)
#self.merged = False
# FIXME: hook forward method of original linear, but how do we undo the hook when we are done?
def
apply_to
(
self
):
if
not
self
.
applied
:
self
.
org_forward
=
self
.
org_module
[
0
].
forward
#self.org_module[0].forward = self.forward
prehook
=
self
.
org_module
[
0
].
register_forward_pre_hook
(
self
.
pre_forward_hook
)
hook
=
self
.
org_module
[
0
].
register_forward_hook
(
self
.
forward_hook
)
self
.
hooks
.
append
(
prehook
)
self
.
hooks
.
append
(
hook
)
self
.
applied
=
True
def
remove_from
(
self
):
if
self
.
applied
:
for
hook
in
self
.
hooks
:
hook
.
remove
()
self
.
hooks
=
[]
self
.
applied
=
False
def
get_weight
(
self
,
oft_blocks
,
multiplier
=
None
):
multiplier
=
multiplier
.
to
(
oft_blocks
.
device
,
dtype
=
oft_blocks
.
dtype
)
constraint
=
self
.
constraint
.
to
(
oft_blocks
.
device
,
dtype
=
oft_blocks
.
dtype
)
block_Q
=
oft_blocks
-
oft_blocks
.
transpose
(
1
,
2
)
norm_Q
=
torch
.
norm
(
block_Q
.
flatten
())
new_norm_Q
=
torch
.
clamp
(
norm_Q
,
max
=
constraint
)
block_Q
=
block_Q
*
((
new_norm_Q
+
1e-8
)
/
(
norm_Q
+
1e-8
))
m_I
=
torch
.
eye
(
self
.
block_size
,
device
=
oft_blocks
.
device
).
unsqueeze
(
0
).
repeat
(
self
.
num_blocks
,
1
,
1
)
block_R
=
torch
.
matmul
(
m_I
+
block_Q
,
(
m_I
-
block_Q
).
inverse
())
block_R_weighted
=
multiplier
*
block_R
+
(
1
-
multiplier
)
*
m_I
R
=
torch
.
block_diag
(
*
block_R_weighted
)
return
R
def
calc_updown
(
self
,
orig_weight
):
if
not
self
.
applied
:
self
.
apply_to
()
self
.
merged_weight
=
self
.
merged_weight
.
to
(
orig_weight
.
device
,
dtype
=
orig_weight
.
dtype
)
R
=
self
.
get_weight
(
self
.
oft_blocks
,
self
.
multiplier
())
merged_weight
=
self
.
merge_weight
(
R
,
orig_weight
)
updown
=
torch
.
zeros_like
(
orig_weight
,
device
=
orig_weight
.
device
,
dtype
=
orig_weight
.
dtype
)
updown
=
merged_weight
.
to
(
orig_weight
.
device
,
dtype
=
orig_weight
.
dtype
)
-
orig_weight
output_shape
=
orig_weight
.
shape
orig_weight
=
self
.
merged_weight
#output_shape = self.oft_blocks.shape
orig_weight
=
orig_weight
return
self
.
finalize_updown
(
updown
,
orig_weight
,
output_shape
)
def
pre_forward_hook
(
self
,
module
,
input
):
#if not self.applied:
# self.apply_to()
multiplier
=
self
.
multiplier
()
*
self
.
calc_scale
()
if
not
multiplier
==
self
.
last_multiplier
or
not
self
.
merged
:
self
.
R
=
self
.
get_weight
(
self
.
oft_blocks
,
multiplier
)
self
.
last_multiplier
=
multiplier
self
.
merged_weight
=
self
.
merge_weight
()
self
.
replace_weight
(
self
.
merged_weight
)
def
forward_hook
(
self
,
module
,
args
,
output
):
pass
\ No newline at end of file
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