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hparams.py
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hparams.py
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class HyperParams:
vision = 'VAE'
memory = 'RNN'
controller = 'A3C'
extra = False
data_dir = 'datasets'
extra_dir = 'additional'
ckpt_dir = 'ckpt'
img_height = 96
img_width = 96
img_channels = 3
batch_size = 2 # actually batchsize * Seqlen
seq_len = 32
test_batch = 1
n_sample = 64
vsize = 128 # latent size of Vision
msize = 128 # size of Memory
asize = 3 # action size
rnn_hunits = 256
ctrl_hidden_dims = 512
log_interval = 5000
save_interval = 10000
use_binary_feature = False
score_cut = 300 # to save
save_start_score = 100
# Rollout
max_ep = 1000
n_rollout = 200
seed = 0
n_workers = 0
class RNNHyperParams:
vision = 'VAE'
memory = 'RNN'
extra = False
data_dir = 'datasets'
extra_dir = 'additional'
ckpt_dir = 'ckpt'
img_height = 96
img_width = 96
img_channels = 3
batch_size = 1 # actually batchsize * Seqlen
test_batch = 1
seq_len = 32
n_sample = 64
vsize = 128 # latent size of Vision
msize = 128 # size of Memory
asize = 3 # action size
rnn_hunits = 256
log_interval = 1000
save_interval = 2000
max_step = 100000
n_workers = 0
class VAEHyperParams:
vision = 'VAE'
extra = False
data_dir = 'datasets'
extra_dir = 'additional'
ckpt_dir = 'ckpt'
img_height = 96
img_width = 96
img_channels = 3
batch_size = 64 #
test_batch = 12
n_sample = 64
vsize = 128 # latent size of Vision
msize = 128 # size of Memory
asize = 3 # action size
log_interval = 5000
save_interval = 10000
max_step = 2000000
n_workers = 0