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config
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config
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[dataset configuration]
dataset_name = porto_6k
workspace = /data
file_name = data/cleaned_mm_edges.txt
data_size = -1
[ckpt]
save_ckpt = True
load_ckpt = False
max_ckpt_to_keep = 100
compute_ppl = False
direct_stdout_to_file = False
samples_per_epoch_in_train = -1
use_v2_saver = False
[model configuration]
model_type = CSSRNN
hidden_dim = 50
emb_dim = 50
num_layers = 1
rnn = lstm
use_bidir_rnn = False
eval_mode = False
# pretrained_input_emb_path = /data/porto_6k/ckpt/embeddings_400.csv
input_dest = True
dest_emb = True
[LPIRNN]
lpi_dim = 50
individual_task_regularizer = -1
individual_task_keep_prob = 0.9
[params for training]
batch_size = 128
lr = 0.0001
lr_decay = 0.9
keep_prob = 0.9
max_grad_norm = 1.0
init_scale = 0.03
max_seq_len = 80
opt = rmsprop
[for epoch]
epoch_count = 1000
samples_for_benchmark = 3000
[misc]
eval_ngram_model = False
[debug]
trace_hid_layer = False
trace_input_id = 5925