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OpenDAS
apex
Commits
ceca097f
Unverified
Commit
ceca097f
authored
Jun 15, 2020
by
Asit
Committed by
GitHub
Jun 15, 2020
Browse files
editing comments
parent
02a33875
Changes
1
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-2
apex/contrib/sparsity/asp.py
apex/contrib/sparsity/asp.py
+2
-2
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apex/contrib/sparsity/asp.py
View file @
ceca097f
...
@@ -6,7 +6,7 @@ torchvision_imported=True
...
@@ -6,7 +6,7 @@ torchvision_imported=True
try
:
try
:
import
torchvision
import
torchvision
except
ImportError
:
except
ImportError
:
print
(
"[ASP][Warning] torchvision cannot be imported
, may infuence functionality of MaskRCNN/KeypointRCNN network from torchvision
."
)
print
(
"[ASP][Warning] torchvision cannot be imported."
)
torchvision_imported
=
False
torchvision_imported
=
False
def
eligible_modules
(
model
,
whitelist_layer_types
,
allowed_layer_names
,
disallowed_layer_names
):
def
eligible_modules
(
model
,
whitelist_layer_types
,
allowed_layer_names
,
disallowed_layer_names
):
...
@@ -78,7 +78,7 @@ class ASP:
...
@@ -78,7 +78,7 @@ class ASP:
# function to extract variables that will be sparsified.
# function to extract variables that will be sparsified.
# idea is that you will add one of these functions for each module type that can be sparsified.
# idea is that you will add one of these functions for each module type that can be sparsified.
if
torchvision_imported
:
if
torchvision_imported
:
print
(
"[ASP] torchvision is imported, can work
smoothly
with the MaskRCNN/KeypointRCNN from torchvision."
)
print
(
"[ASP] torchvision is imported, can work with the MaskRCNN/KeypointRCNN from torchvision."
)
sparse_parameter_list
=
{
torch
.
nn
.
Linear
:
[
'weight'
],
torch
.
nn
.
Conv1d
:
[
'weight'
],
torch
.
nn
.
Conv2d
:
[
'weight'
],
torch
.
nn
.
Conv3d
:
[
'weight'
],
torchvision
.
ops
.
misc
.
Conv2d
:
[
'weight'
]}
sparse_parameter_list
=
{
torch
.
nn
.
Linear
:
[
'weight'
],
torch
.
nn
.
Conv1d
:
[
'weight'
],
torch
.
nn
.
Conv2d
:
[
'weight'
],
torch
.
nn
.
Conv3d
:
[
'weight'
],
torchvision
.
ops
.
misc
.
Conv2d
:
[
'weight'
]}
else
:
else
:
sparse_parameter_list
=
{
torch
.
nn
.
Linear
:
[
'weight'
],
torch
.
nn
.
Conv1d
:
[
'weight'
],
torch
.
nn
.
Conv2d
:
[
'weight'
],
torch
.
nn
.
Conv3d
:
[
'weight'
]}
sparse_parameter_list
=
{
torch
.
nn
.
Linear
:
[
'weight'
],
torch
.
nn
.
Conv1d
:
[
'weight'
],
torch
.
nn
.
Conv2d
:
[
'weight'
],
torch
.
nn
.
Conv3d
:
[
'weight'
]}
...
...
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