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Variational Voxel 3D Detection
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MaLeCi
OpenDR
Variational Voxel 3D Detection
Commits
5a2ed716
Commit
5a2ed716
authored
2 years ago
by
Illia Oleksiienko
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Add full training steps retraining
parent
3e9e4564
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run/modeling.py
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5a2ed716
...
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@@ -151,5 +151,58 @@ def run_vnn_from_classical_2(id=0, gpu_capacity=1, total_devices=4, raise_on_inf
i
+=
gpu_capacity
*
total_devices
def
run_vnn_from_classical_2_full_training_steps
(
id
=
0
,
gpu_capacity
=
1
,
total_devices
=
4
,
raise_on_infer_error
=
True
):
device_id
=
id
%
total_devices
i
=
id
training_samples
=
[
2
,
4
]
eval_samples_list
=
[
1
,
2
,
3
,
4
]
def
create_models
():
result
=
[]
for
init_vnn_name
,
init_vnn_weights
in
[
(
"
fill0001
"
,
"
fill:stds:0.001:0.001
"
),
(
"
fill00001
"
,
"
fill:stds:0.0001:0.0001
"
),
(
"
xavier_uniform001
"
,
"
xavier_uniform:stds:0.01:0.01
"
),
(
"
xavier_normal001
"
,
"
xavier_normal:stds:0.01:0.01
"
),
]:
for
single_training_samples
in
training_samples
:
name
=
f
"
vnnclass1-2
{
init_vnn_name
}
_tanet_car
"
result
.
append
(
Model
(
name
,
samples_list
=
[
single_training_samples
],
eval_samples_list
=
eval_samples_list
,
init_vnn_weights
=
init_vnn_weights
,
classical_name
=
"
tanet_car_2
"
,
config
=
"
vnn_xyres_16.proto
"
,
),
)
return
result
models
=
create_models
()
while
i
<
len
(
models
):
model
=
models
[
i
]
try
:
result
=
model
.
train
(
device
=
"
cuda:
"
+
str
(
device_id
)
)
print
(
result
)
except
Exception
as
e
:
if
raise_on_infer_error
:
raise
e
else
:
print
(
e
)
i
+=
gpu_capacity
*
total_devices
if
__name__
==
"
__main__
"
:
fire
.
Fire
()
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