Add training and decoding scripts.

exp/decode-pruned-rnnt-L.sh

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+#!/usr/bin/env bash
+
+export CUDA_VISIBLE_DEVICES="7"
+
+set -ex
+
+# for iter in 176000; do
+for iter in 168000 160000 152000 144000; do
+  for avg in 10 11 12 13 14; do
+    ./pruned_transducer_stateless5/decode.py \
+      --iter $iter \
+      --avg $avg \
+      --exp-dir ./pruned_transducer_stateless5/exp-L \
+      --max-duration 600 \
+      --decoding-method greedy_search \
+      --max-sym-per-frame 1 \
+      --num-encoder-layers 18 \
+      --dim-feedforward 2048 \
+      --nhead 8 \
+      --encoder-dim 512 \
+      --decoder-dim 512 \
+      --joiner-dim 512
+  done
+done

exp/export-L.sh

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+#!/usr/bin/env bash
+
+export CUDA_VISIBLE_DEVICES=0
+
+set -ex
+
+epoch=39
+avg=7
+
+./pruned_transducer_stateless5/export.py \
+  --exp-dir ./pruned_transducer_stateless5/exp-L \
+  --bpe-model data/lang_bpe_500/bpe.model \
+  --epoch $epoch \
+  --avg $avg \
+  --num-encoder-layers 18 \
+  --dim-feedforward 2048 \
+  --nhead 8 \
+  --encoder-dim 512 \
+  --decoder-dim 512 \
+  --joiner-dim 512
+
+mv -v ./pruned_transducer_stateless5/exp-L/pretrained.pt ./pruned_transducer_stateless5/exp-L/pretrained-epoch-${epoch}-avg-${avg}.pt

exp/run-pruned-rnnt-L.sh

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+#!/usr/bin/env bash
+
+export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
+
+./pruned_transducer_stateless5/train.py \
+  --world-size 8 \
+  --num-epochs 40 \
+  --start-epoch 0 \
+  --full-libri 1 \
+  --exp-dir pruned_transducer_stateless5/exp-L \
+  --max-duration 300 \
+  --use-fp16 0 \
+  --num-encoder-layers 18 \
+  --dim-feedforward 2048 \
+  --nhead 8 \
+  --encoder-dim 512 \
+  --decoder-dim 512 \
+  --joiner-dim 512