Update-2024.06.04

This commit is contained in:
chun
2024-06-04 11:19:08 +08:00
parent ca6377e98c
commit e1cef6aead
87 changed files with 1436 additions and 209 deletions
@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 10
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:1
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.08333333333333333
ratio_list:
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seed: 42
snr: 1.0
snr_list:
- 1.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
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@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 10
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:1
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.08333333333333333
ratio_list:
- 0.08333333333333333
seed: 42
snr: 13.0
snr_list:
- 13.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
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args:
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@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 10
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:1
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.08333333333333333
ratio_list:
- 0.08333333333333333
seed: 42
snr: 19.0
snr_list:
- 19.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
- !!python/object/apply:numpy.dtype
args:
- i8
- false
- true
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@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 10
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:1
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.08333333333333333
ratio_list:
- 0.08333333333333333
seed: 42
snr: 4.0
snr_list:
- 4.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
- !!python/object/apply:numpy.dtype
args:
- i8
- false
- true
state: !!python/tuple
- 3
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41QCAAAAAAA=
@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 10
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:1
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.08333333333333333
ratio_list:
- 0.08333333333333333
seed: 42
snr: 7.0
snr_list:
- 7.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
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args:
- i8
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@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 20
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:0
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.16666666666666666
ratio_list:
- 0.16666666666666666
seed: 42
snr: 1.0
snr_list:
- 1.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
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dataset_name: cifar10
inner_channel: 20
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:0
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.16666666666666666
ratio_list:
- 0.16666666666666666
seed: 42
snr: 13.0
snr_list:
- 13.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
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@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 20
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:0
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.16666666666666666
ratio_list:
- 0.16666666666666666
seed: 42
snr: 19.0
snr_list:
- 19.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
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args:
- i8
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@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 20
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:0
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.16666666666666666
ratio_list:
- 0.16666666666666666
seed: 42
snr: 4.0
snr_list:
- 4.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
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@@ -0,0 +1,46 @@
dataset_name: cifar10
inner_channel: 20
params:
ReduceLROnPlateau: false
batch_size: 64
channel: AWGN
dataset: cifar10
device: cuda:0
disable_tqdm: false
epochs: 1000
gamma: 0.1
if_scheduler: true
init_lr: 0.001
lr_reduce_factor: 0.5
lr_schedule_patience: 15
max_time: 12
min_lr: 1.0e-05
num_workers: 4
out_dir: ./out
parallel: false
ratio: 0.16666666666666666
ratio_list:
- 0.16666666666666666
seed: 42
snr: 7.0
snr_list:
- 7.0
step_size: 640
weight_decay: 0.0005
total_parameters: !!python/object/apply:numpy.core.multiarray.scalar
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