Add finetuning script for aishell (k2-fsa#974)

* add aishell finetune scripts

* add an example bash script

Author: marcoyang1998

egs/wenetspeech/ASR/finetune.sh

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+#!/usr/bin/env bash
+
+# fix segmentation fault reported in https://github.com/k2-fsa/icefall/issues/674
+export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
+
+set -eou pipefail
+
+stage=-1
+stop_stage=100
+
+# This is an example script for fine-tuning. Here, we fine-tune a model trained
+# on WenetSpeech on Aishell. The model used for fine-tuning is
+# pruned_transducer_stateless2 (zipformer). If you want to fine-tune model
+# from another recipe, you can adapt ./pruned_transducer_stateless2/finetune.py
+# for that recipe. If you have any problem, please open up an issue in https://github.com/k2-fsa/icefall/issues.
+
+# We assume that you have already prepared the Aishell manfiest&features under ./data.
+# If you haven't done that, please see https://github.com/k2-fsa/icefall/blob/master/egs/aishell/ASR/prepare.sh.
+
+. shared/parse_options.sh || exit 1
+
+log() {
+  # This function is from espnet
+  local fname=${BASH_SOURCE[1]##*/}
+  echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
+}
+
+if [ $stage -le -1 ] && [ $stop_stage -ge -1 ]; then
+  log "Stage -1: Download Pre-trained model"
+
+  # clone from huggingface
+  git lfs install
+  git clone https://huggingface.co/luomingshuang/icefall_asr_wenetspeech_pruned_transducer_stateless2
+
+fi
+
+if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
+  log "Stage 0: Start fine-tuning"
+
+  # The following configuration of lr schedule should work well
+  # You may also tune the following parameters to adjust learning rate schedule
+  initial_lr=0.0001
+  lr_epochs=100
+  lr_batches=100000
+
+  # We recommend to start from an averaged model
+  finetune_ckpt=icefall_asr_wenetspeech_pruned_transducer_stateless2/exp/pretrained_epoch_10_avg_2.pt
+  lang_dir=icefall_asr_wenetspeech_pruned_transducer_stateless2/data/lang_char
+  export CUDA_VISIBLE_DEVICES="0,1"
+
+  ./pruned_transducer_stateless2/finetune.py \
+    --world-size 2 \
+    --master-port 18180 \
+    --num-epochs 15 \
+    --context-size 2 \
+    --exp-dir pruned_transducer_stateless2/exp_aishell_finetune \
+    --initial-lr $initial_lr \
+    --lr-epochs $lr_epochs \
+    --lr-batches $lr_batches \
+    --lang-dir $lang_dir \
+    --do-finetune True \
+    --finetune-ckpt $finetune_ckpt \
+    --max-duration 200
+fi
+
+if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
+  log "Stage 1: Decoding"
+
+  epoch=4
+  avg=4
+
+  for m in greedy_search modified_beam_search; do
+    python pruned_transducer_stateless2/decode_aishell.py \
+    --epoch $epoch \
+    --avg $avg \
+    --context-size 2 \
+    --beam-size 4 \
+    --exp-dir pruned_transducer_stateless2/exp_aishell_finetune \
+    --max-duration 400 \
+    --decoding-method $m
+  done
+fi

egs/wenetspeech/ASR/pruned_transducer_stateless2/aishell.py

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+../../../aishell/ASR/tdnn_lstm_ctc/asr_datamodule.py