Add training script.

deep_speech_2/examples/aishell/run_train.sh

+#! /usr/bin/env bash
+
+pushd ../.. > /dev/null
+
+# train model
+# if you wish to resume from an exists model, uncomment --init_model_path
+CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
+python -u train.py \
+--batch_size=64 \
+--trainer_count=8 \
+--num_passes=50 \
+--num_proc_data=12 \
+--num_conv_layers=2 \
+--num_rnn_layers=3 \
+--rnn_layer_size=1024 \
+--num_iter_print=100 \
+--learning_rate=5e-4 \
+--max_duration=27.0 \
+--min_duration=0.0 \
+--test_off=False \
+--use_sortagrad=True \
+--use_gru=False \
+--use_gpu=True \
+--is_local=True \
+--share_rnn_weights=False \
+--train_manifest='data/aishell/manifest.train' \
+--dev_manifest='data/aishell/manifest.dev' \
+--mean_std_path='data/aishell/mean_std.npz' \
+--vocab_path='data/aishell/vocab.txt' \
+--output_model_dir='./checkpoints/aishell' \
+--augment_conf_path='conf/augmentation.config' \
+--specgram_type='linear' \
+--shuffle_method='batch_shuffle_clipped'
+
+if [ $? -ne 0 ]; then
+    echo "Failed in training!"
+    exit 1
+fi
+
+
+exit 0