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OpenDAS
apex
Commits
d6b2e7d3
Commit
d6b2e7d3
authored
Jun 29, 2018
by
Michael Carilli
Browse files
Merge branch 'master' of
https://github.com/NVIDIA/apex
parents
5e54253f
6f0748d6
Changes
2
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12 additions
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8 deletions
+12
-8
examples/imagenet/main.py
examples/imagenet/main.py
+6
-4
examples/imagenet/main_fp16_optimizer.py
examples/imagenet/main_fp16_optimizer.py
+6
-4
No files found.
examples/imagenet/main.py
View file @
d6b2e7d3
...
@@ -377,13 +377,15 @@ def validate(val_loader, model, criterion):
...
@@ -377,13 +377,15 @@ def validate(val_loader, model, criterion):
output
=
model
(
input_var
)
output
=
model
(
input_var
)
loss
=
criterion
(
output
,
target_var
)
loss
=
criterion
(
output
,
target_var
)
reduced_loss
=
reduce_tensor
(
loss
.
data
)
# measure accuracy and record loss
# measure accuracy and record loss
prec1
,
prec5
=
accuracy
(
output
.
data
,
target
,
topk
=
(
1
,
5
))
prec1
,
prec5
=
accuracy
(
output
.
data
,
target
,
topk
=
(
1
,
5
))
reduced_prec1
=
reduce_tensor
(
prec1
)
if
args
.
distributed
:
reduced_prec5
=
reduce_tensor
(
prec5
)
reduced_loss
=
reduce_tensor
(
loss
.
data
)
prec1
=
reduce_tensor
(
prec1
)
prec5
=
reduce_tensor
(
prec5
)
else
:
reduced_loss
=
loss
.
data
losses
.
update
(
to_python_float
(
reduced_loss
),
input
.
size
(
0
))
losses
.
update
(
to_python_float
(
reduced_loss
),
input
.
size
(
0
))
top1
.
update
(
to_python_float
(
prec1
),
input
.
size
(
0
))
top1
.
update
(
to_python_float
(
prec1
),
input
.
size
(
0
))
...
...
examples/imagenet/main_fp16_optimizer.py
View file @
d6b2e7d3
...
@@ -338,13 +338,15 @@ def validate(val_loader, model, criterion):
...
@@ -338,13 +338,15 @@ def validate(val_loader, model, criterion):
output
=
model
(
input_var
)
output
=
model
(
input_var
)
loss
=
criterion
(
output
,
target_var
)
loss
=
criterion
(
output
,
target_var
)
reduced_loss
=
reduce_tensor
(
loss
.
data
)
# measure accuracy and record loss
# measure accuracy and record loss
prec1
,
prec5
=
accuracy
(
output
.
data
,
target
,
topk
=
(
1
,
5
))
prec1
,
prec5
=
accuracy
(
output
.
data
,
target
,
topk
=
(
1
,
5
))
reduced_prec1
=
reduce_tensor
(
prec1
)
if
args
.
distributed
:
reduced_prec5
=
reduce_tensor
(
prec5
)
reduced_loss
=
reduce_tensor
(
loss
.
data
)
prec1
=
reduce_tensor
(
prec1
)
prec5
=
reduce_tensor
(
prec5
)
else
:
reduced_loss
=
loss
.
data
losses
.
update
(
to_python_float
(
reduced_loss
),
input
.
size
(
0
))
losses
.
update
(
to_python_float
(
reduced_loss
),
input
.
size
(
0
))
top1
.
update
(
to_python_float
(
prec1
),
input
.
size
(
0
))
top1
.
update
(
to_python_float
(
prec1
),
input
.
size
(
0
))
...
...
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