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new config
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tarun018 committed Dec 24, 2020
1 parent 438a4a5 commit 466ef5e
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81 changes: 81 additions & 0 deletions configs/whirl_baselines_v2/27m_vs_30m.yaml
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label: ""
name: ""
params:
algo:
name: a2c_discrete

model:
name: discrete_a2c

load_checkpoint: False
load_path: 'nn/27m_vs_30_cnn'

network:
name: actor_critic
separate: True
#normalization: layer_norm
space:
discrete:

cnn:
type: conv1d
activation: relu
initializer:
name: variance_scaling_initializer
scale: 2
regularizer:
name: 'None'
convs:
- filters: 64
kernel_size: 3
strides: 2
padding: 'same'
- filters: 128
kernel_size: 3
strides: 1
padding: 'valid'
- filters: 256
kernel_size: 3
strides: 1
padding: 'valid'
mlp:
units: [256, 128]
activation: relu
initializer:
name: variance_scaling_initializer
scale: 2
regularizer:
name: 'None'
config:
name: 27m_vs_30m_cnn
reward_shaper:
scale_value: 1
normalize_advantage: True
gamma: 0.99
tau: 0.95
learning_rate: 1e-4
score_to_win: 20
grad_norm: 0.5
entropy_coef: 0.005
truncate_grads: True
env_name: smac_cnn
ppo: true
e_clip: 0.2
clip_value: True
num_actors: 8
steps_num: 128
minibatch_size: 4096
mini_epochs: 1
critic_coef: 2
lr_schedule: None
lr_threshold: 0.05
normalize_input: False
seq_len: 4
use_action_masks: True
ignore_dead_batches : False

env_config:
name: 27m_vs_30m
frames: 4
transpose: True
random_invalid_step: False
81 changes: 81 additions & 0 deletions configs/whirl_baselines_v2/3s5z_vs_3s6z.yaml
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label: ""
name: ""
params:
algo:
name: a2c_discrete

model:
name: discrete_a2c

load_checkpoint: False
load_path: 'nn/3s5z_vs_3s6z_cnn'

network:
name: actor_critic
separate: True
#normalization: layer_norm
space:
discrete:

cnn:
type: conv1d
activation: relu
initializer:
name: variance_scaling_initializer
scale: 2
regularizer:
name: 'None'
convs:
- filters: 64
kernel_size: 3
strides: 2
padding: 'same'
- filters: 128
kernel_size: 3
strides: 1
padding: 'valid'
- filters: 256
kernel_size: 3
strides: 1
padding: 'valid'
mlp:
units: [256, 128]
activation: relu
initializer:
name: variance_scaling_initializer
scale: 2
regularizer:
name: 'None'
config:
name: 3s5z_vs_3s6zaa
reward_shaper:
scale_value: 1
normalize_advantage: True
gamma: 0.99
tau: 0.95
learning_rate: 1e-4
score_to_win: 20
grad_norm: 0.5
entropy_coef: 0.005
truncate_grads: True
env_name: smac_cnn
ppo: true
e_clip: 0.2
clip_value: True
num_actors: 8
steps_num: 128
minibatch_size: 4096
mini_epochs: 1
critic_coef: 2
lr_schedule: None
lr_threshold: 0.05
normalize_input: False
seq_len: 2
use_action_masks: True
ignore_dead_batches : False

env_config:
name: 3s5z_vs_3s6z
frames: 4
transpose: True
random_invalid_step: False
81 changes: 81 additions & 0 deletions configs/whirl_baselines_v2/3s_vs_5z.yaml
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@@ -0,0 +1,81 @@
label: ""
name: ""
params:
algo:
name: a2c_discrete

model:
name: discrete_a2c

load_checkpoint: False
load_path: 'nn/3s_vs_5z_cnn'

network:
name: actor_critic
separate: True
#normalization: layer_norm
space:
discrete:

cnn:
type: conv1d
activation: relu
initializer:
name: variance_scaling_initializer
scale: 2
regularizer:
name: 'None'
convs:
- filters: 64
kernel_size: 3
strides: 2
padding: 'same'
- filters: 128
kernel_size: 3
strides: 1
padding: 'valid'
- filters: 256
kernel_size: 3
strides: 1
padding: 'valid'
mlp:
units: [256, 128]
activation: relu
initializer:
name: variance_scaling_initializer
scale: 2
regularizer:
name: 'None'
config:
name: 3s_vs_5z_cnn
reward_shaper:
scale_value: 1
normalize_advantage: True
gamma: 0.99
tau: 0.95
learning_rate: 1e-4
score_to_win: 20
grad_norm: 0.5
entropy_coef: 0.005
truncate_grads: True
env_name: smac_cnn
ppo: true
e_clip: 0.2
clip_value: True
num_actors: 8
steps_num: 128
minibatch_size: 4096
mini_epochs: 1
critic_coef: 2
lr_schedule: None
lr_threshold: 0.05
normalize_input: False
seq_len: 2
use_action_masks: True
ignore_dead_batches : False

env_config:
name: 3s_vs_5z
frames: 4
transpose: True
random_invalid_step: False
81 changes: 81 additions & 0 deletions configs/whirl_baselines_v2/5m_vs_6m.yaml
Original file line number Diff line number Diff line change
@@ -0,0 +1,81 @@
label: ""
name: ""
params:
algo:
name: a2c_discrete

model:
name: discrete_a2c

load_checkpoint: False
load_path: 'nn/5m_vs_6m_cnn'

network:
name: actor_critic
separate: True
#normalization: layer_norm
space:
discrete:

cnn:
type: conv1d
activation: relu
initializer:
name: variance_scaling_initializer
scale: 2
regularizer:
name: 'None'
convs:
- filters: 64
kernel_size: 3
strides: 2
padding: 'same'
- filters: 128
kernel_size: 3
strides: 1
padding: 'valid'
- filters: 256
kernel_size: 3
strides: 1
padding: 'valid'
mlp:
units: [256, 128]
activation: relu
initializer:
name: variance_scaling_initializer
scale: 2
regularizer:
name: 'None'
config:
name: 5m_vs_6m_bias
reward_shaper:
scale_value: 1
normalize_advantage: True
gamma: 0.99
tau: 0.95
learning_rate: 1e-4
score_to_win: 20
grad_norm: 0.5
entropy_coef: 0.005
truncate_grads: True
env_name: smac_cnn
ppo: true
e_clip: 0.2
clip_value: True
num_actors: 8
steps_num: 128
minibatch_size: 4096
mini_epochs: 1
critic_coef: 2
lr_schedule: None
lr_threshold: 0.05
normalize_input: False
seq_len: 2
use_action_masks: True
ignore_dead_batches : False

env_config:
name: 5m_vs_6m
frames: 4
transpose: True
random_invalid_step: False
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