revise the conver model script, now we use conver_t2t_to_fairseq.py to convert…

revise the conver model script,  now we use conver_t2t_to_fairseq.py to convert the t2t checkpoint into fairseq.pt

convert_dense_model.sh

-#! /usr/bin/bash
-set -e
-
-# device, you can set multiple devices, e.g. device=(0 1 2)
-# then program will parallelly translate over various evalset (e.g. evalset=(cwmt18-dev mt06 mt08), or over various alpha (e.g. alphas=(1.0 1.1 1.2). 
-# However, note that multiple evalset and multiple alpha can not set concurrently.
-# more device will not be used. e.g. you set device=(0 1 2 3), but you only choose three evalset, the gpu=3 will not be used
-device=(0 1 2 3 4 5 6 7)
-# your model
-model=dense_transformer
-# your hparams
-params=dense_transformer_base
-# your tag, must set!
-tag=dense16
-
-model_dir=t2tmodel/$tag/ensemble15
-
-output_dir=checkpoints/$tag
-
-if [ ! -d "$output_dir" ]; then
-  mkdir -p $output_dir
-fi
-
-n_head=8
-result=$(echo $params | sed -n '/base/'p)
-                if [[ "$result" != "" ]]; then
-                        n_head=8
-                else
-                        n_head=16
-                fi
-echo "n_head=$n_head"
-
-CUDA_VISIBLE_DEVICES=0 python3 scripts/convert_dense_to_fairseq.py -model $model_dir/ensemble_15-0 -src_vocab t2tmodel/source_dic -tgt_vocab t2tmodel/target_dic -head_num $n_head -vocab_output $model_dir/fairseq.vocab -model_output $output_dir/fairseq.pt
-
-rm online.vocab

convert_model.sh

@@ -6,10 +6,6 @@ set -e
 # However, note that multiple evalset and multiple alpha can not set concurrently.
 # more device will not be used. e.g. you set device=(0 1 2 3), but you only choose three evalset, the gpu=3 will not be used
 device=(0 1 2 3 4 5 6 7)
-# your model
-model=transformer
-# your hparams
-params=transformer_big
 # your tag, must set!
 tag=big_v3_multistep4