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Update file names in Hubert VQ recipe
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@ -30,10 +30,10 @@ stage=$1
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# even you only have ONE GPU. It needed by CodebookIndexExtractor to determine numbert of jobs to extract codebook indexes parallelly.
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# Suppose only one GPU exists:
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# export CUDA_VISIBLE_DEVICES="0"
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export CUDA_VISIBLE_DEVICES="0"
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#
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# Suppose GPU 2,3,4,5 are available.
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export CUDA_VISIBLE_DEVICES="2,3,4,5"
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# export CUDA_VISIBLE_DEVICES="2,3,4,5"
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if [ $stage -eq 0 ]; then
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@ -71,7 +71,7 @@ if [ $stage -eq 0 ]; then
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if [ -f ${hubert_model} ]; then
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echo "hubert model alread exists."
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else
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wget -c https://dl.fbaipublicfiles.com/hubert/${model_id} -P ${hubert_model}
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wget -c https://dl.fbaipublicfiles.com/hubert/${model_id}.pt -P ${hubert_model}
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wget -c wget https://dl.fbaipublicfiles.com/fairseq/wav2vec/dict.ltr.txt -P ${hubert_model_dir}
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fi
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fi
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@ -36,7 +36,7 @@ from icefall.utils import (
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AttributeDict,
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setup_logger,
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)
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from lhotse import CutSet, load_manifest
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from lhotse import CutSet, load_manifest_lazy
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from lhotse.features.io import NumpyHdf5Writer
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@ -222,7 +222,7 @@ class CodebookIndexExtractor:
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"""
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for subset in self.params.subsets:
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logging.info(f"About to split {subset}.")
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ori_manifest = f"./data/fbank/cuts_train-{subset}.json.gz"
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ori_manifest = f"./data/fbank/cuts_train-{subset}.jsonl.gz"
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split_cmd = f"lhotse split {self.params.world_size} {ori_manifest} {self.manifest_dir}"
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os.system(f"{split_cmd}")
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@ -231,9 +231,9 @@ class CodebookIndexExtractor:
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Merge generated vq included manfiests and storage to self.dst_manifest_dir.
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"""
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for subset in self.params.subsets:
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vq_manifests = f"{self.manifest_dir}/with_codebook_indexes-cuts_train-{subset}*.json.gz"
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vq_manifests = f"{self.manifest_dir}/with_codebook_indexes-cuts_train-{subset}*.jsonl.gz"
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dst_vq_manifest = (
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self.dst_manifest_dir / f"cuts_train-{subset}.json.gz"
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self.dst_manifest_dir / f"cuts_train-{subset}.jsonl.gz"
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)
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if 1 == self.params.world_size:
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merge_cmd = f"cp {vq_manifests} {dst_vq_manifest}"
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@ -294,14 +294,14 @@ class CodebookIndexExtractor:
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def load_ori_dl(self, subset):
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if self.params.world_size == 1:
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ori_manifest_path = f"./data/fbank/cuts_train-{subset}.json.gz"
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ori_manifest_path = f"./data/fbank/librispeech_cuts_train-{subset}.jsonl.gz"
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else:
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ori_manifest_path = (
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self.manifest_dir
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/ f"cuts_train-{subset}.{self.params.manifest_index}.json.gz"
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/ f"librispeech_cuts_train-{subset}.{self.params.manifest_index}.jsonl.gz"
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)
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cuts = load_manifest(ori_manifest_path)
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cuts = load_manifest_lazy(ori_manifest_path)
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dl = LibriSpeechAsrDataModule(self.params).train_dataloaders(cuts)
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return dl
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@ -373,9 +373,9 @@ class CodebookIndexExtractor:
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json_file_path = (
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self.manifest_dir
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/ f"with_codebook_indexes-cuts_train-{manifest_file_id}.json.gz"
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/ f"with_codebook_indexes-cuts_train-{manifest_file_id}.jsonl.gz"
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)
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CutSet.from_cuts(cuts).to_json(json_file_path)
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CutSet.from_cuts(cuts).to_file(json_file_path)
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@torch.no_grad()
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