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69 lines (61 loc) · 1.59 KB
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#!/bin/bash
REPO_DIR='/SMiLE'
dataset='FB15k'
gpu_id=0
data_path="${REPO_DIR}/data"
#pretrained_embeddings=$data_path/../act_$dataset\_mult_500.out
#pretrained_method='compgcn'
pretrained_embeddings="${data_path}/${dataset}/${dataset}.emd"
outdir="${REPO_DIR}/output/${dataset}-1"
mkdir $outdir
# Pretrain Setting
n_heads=4
n_layers=4
n_pretrain_epochs=15
pretrain_batch_size=1024
pretrain_checkpoint=4
# Schema Setting
# relation_weight=1
schema_weight=1
topNfilters=-700
use_schema=True
# Finetune Setting
ft_n_epochs=15
ft_batch_size=256
ft_checkpoint=500
walk_type='bfs'
num_walks_per_node=1
beam_width=6
max_length=6
gcn_option=no_gcn
node_edge_composition_func=mult
ft_input_option='last4_cat'
path_option='shortest'
is_pre_trained=True
python main.py \
--gpu_id $gpu_id \
--data_name $dataset \
--data_path $data_path \
--outdir $outdir \
--pretrained_embeddings $pretrained_embeddings \
--n_epochs $n_pretrain_epochs \
--batch_size $pretrain_batch_size \
--checkpoint $pretrain_checkpoint \
--schema_weight $schema_weight\
--n_layers $n_layers \
--n_heads $n_heads \
--gcn_option $gcn_option \
--node_edge_composition_func $node_edge_composition_func \
--ft_input_option $ft_input_option \
--path_option $path_option \
--ft_n_epochs $ft_n_epochs \
--ft_batch_size $ft_batch_size \
--ft_checkpoint $ft_checkpoint \
--num_walks_per_node $num_walks_per_node \
--beam_width $beam_width \
--max_length $max_length \
--walk_type $walk_type \
--topNfilters $topNfilters \
--is_pre_trained \
--use_schema
#>> $log_file