mirrors/icefall
1
0
Fork 0
mirror of https://github.com/k2-fsa/icefall.git synced 2025-08-26 18:24:18 +00:00
Code Issues Packages Projects Releases Wiki Activity

format files with isort to meet style guidelines

Browse Source
This commit is contained in:
root 2024-05-02 10:02:02 +09:00
parent d61b73964b
commit 0925a0c300
4 changed files with 54 additions and 30 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

63
egs/reazonspeech/ASR/local/compute_fbank_reazonspeech.py
View File

@ -54,36 +54,51 @@ def make_cutset_blueprints(
# Create test dataset
logging.info("Creating test cuts.")
cut_sets.append(("test", CutSet.from_manifests(
recordings=RecordingSet.from_file(
manifest_dir / "reazonspeech_recordings_test.jsonl.gz"
),
supervisions=SupervisionSet.from_file(
manifest_dir / "reazonspeech_supervisions_test.jsonl.gz"
),
)))
cut_sets.append(
(
"test",
CutSet.from_manifests(
recordings=RecordingSet.from_file(
manifest_dir / "reazonspeech_recordings_test.jsonl.gz"
),
supervisions=SupervisionSet.from_file(
manifest_dir / "reazonspeech_supervisions_test.jsonl.gz"
),
),
)
)
# Create valid dataset
logging.info("Creating valid cuts.")
cut_sets.append(("valid", CutSet.from_manifests(
recordings=RecordingSet.from_file(
manifest_dir / "reazonspeech_recordings_valid.jsonl.gz"
),
supervisions=SupervisionSet.from_file(
manifest_dir / "reazonspeech_supervisions_valid.jsonl.gz"
),
)))
cut_sets.append(
(
"valid",
CutSet.from_manifests(
recordings=RecordingSet.from_file(
manifest_dir / "reazonspeech_recordings_valid.jsonl.gz"
),
supervisions=SupervisionSet.from_file(
manifest_dir / "reazonspeech_supervisions_valid.jsonl.gz"
),
),
)
)
# Create train dataset
logging.info("Creating train cuts.")
cut_sets.append(("train", CutSet.from_manifests(
recordings=RecordingSet.from_file(
manifest_dir / "reazonspeech_recordings_train.jsonl.gz"
),
supervisions=SupervisionSet.from_file(
manifest_dir / "reazonspeech_supervisions_train.jsonl.gz"
),
)))
cut_sets.append(
(
"train",
CutSet.from_manifests(
recordings=RecordingSet.from_file(
manifest_dir / "reazonspeech_recordings_train.jsonl.gz"
),
supervisions=SupervisionSet.from_file(
manifest_dir / "reazonspeech_supervisions_train.jsonl.gz"
),
),
)
)
return cut_sets

1
egs/reazonspeech/ASR/local/prepare_lang_char.py
View File

@ -22,6 +22,7 @@ from pathlib import Path
from lhotse import CutSet
def get_args():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,

12
egs/reazonspeech/ASR/local/utils/asr_datamodule.py
View File

@ -336,14 +336,20 @@ class ReazonSpeechAsrDataModule:
@lru_cache()
def train_cuts(self) -> CutSet:
logging.info("About to get train cuts")
return load_manifest_lazy(self.args.manifest_dir / "reazonspeech_cuts_train.jsonl.gz")
return load_manifest_lazy(
self.args.manifest_dir / "reazonspeech_cuts_train.jsonl.gz"
)
@lru_cache()
def valid_cuts(self) -> CutSet:
logging.info("About to get valid cuts")
return load_manifest_lazy(self.args.manifest_dir / "reazonspeech_cuts_valid.jsonl.gz")
return load_manifest_lazy(
self.args.manifest_dir / "reazonspeech_cuts_valid.jsonl.gz"
)
@lru_cache()
def test_cuts(self) -> List[CutSet]:
logging.info("About to get test cuts")
return load_manifest_lazy(self.args.manifest_dir / "reazonspeech_cuts_test.jsonl.gz")
return load_manifest_lazy(
self.args.manifest_dir / "reazonspeech_cuts_test.jsonl.gz"
)

8
egs/reazonspeech/ASR/zipformer/decode.py
View File

@ -103,7 +103,6 @@ from pathlib import Path
from typing import Dict, List, Optional, Tuple
import k2
from tokenizer import Tokenizer
import torch
import torch.nn as nn
from asr_datamodule import ReazonSpeechAsrDataModule
@ -121,6 +120,7 @@ from beam_search import (
modified_beam_search_lm_shallow_fusion,
modified_beam_search_LODR,
)
from tokenizer import Tokenizer
from train import add_model_arguments, get_model, get_params
from icefall import ContextGraph, LmScorer, NgramLm
@ -1039,7 +1039,9 @@ def main():
for subdir in ["valid"]:
results_dict = decode_dataset(
dl=reazonspeech_corpus.test_dataloaders(getattr(reazonspeech_corpus, f"{subdir}_cuts")()),
dl=reazonspeech_corpus.test_dataloaders(
getattr(reazonspeech_corpus, f"{subdir}_cuts")()
),
params=params,
model=model,
sp=sp,
@ -1065,7 +1067,7 @@ def main():
# if len(tot_err) == 1:
# fout.write(f"{tot_err[0][1]}")
# else:
# fout.write("\n".join(f"{k}\t{v}") for k, v in tot_err)
# fout.write("\n".join(f"{k}\t{v}") for k, v in tot_err)
logging.info("Done!")