From 0a629be04f7a27c531b671921e1a445de34895b4 Mon Sep 17 00:00:00 2001
From: Pherkel
Date: Sun, 20 Aug 2023 13:11:58 +0200
Subject: added tokenizer training
---
pyproject.toml | 4 ++++
1 file changed, 4 insertions(+)
(limited to 'pyproject.toml')
diff --git a/pyproject.toml b/pyproject.toml
index 8490aa5..b7e6ffb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -15,14 +15,18 @@ audioloader = {git = "https://github.com/marvinborner/AudioLoader.git"}
tqdm = "^4.66.1"
numpy = "^1.25.2"
mido = "^1.3.0"
+tokenizers = "^0.13.3"
[tool.poetry.group.dev.dependencies]
black = "^23.7.0"
mypy = "^1.5.1"
pylint = "^2.17.5"
+ruff = "^0.0.285"
[tool.poetry.scripts]
train = "swr2_asr.train:run_cli"
+train-bpe-tokenizer = "swr2_asr.tokenizer:train_bpe_tokenizer"
+train-char-tokenizer = "swr2_asr.tokenizer:train_char_tokenizer"
[build-system]
requires = ["poetry-core"]
--
cgit v1.2.3
From 33744072d8c0906950cdc9cd00fc1f345a51d9d4 Mon Sep 17 00:00:00 2001
From: Pherkel
Date: Sun, 20 Aug 2023 15:23:02 +0200
Subject: please the linters
---
.github/workflows/format.yml | 38 +++++++++++++++++++++-----------------
Makefile | 3 +++
mypy.ini | 6 ++++++
poetry.lock | 25 +++++++++++++++++++++----
pyproject.toml | 1 +
swr2_asr/loss_scores.py | 36 +++++++++++++++++++-----------------
swr2_asr/tokenizer.py | 18 ++++++++++--------
swr2_asr/train.py | 12 ++++++------
8 files changed, 87 insertions(+), 52 deletions(-)
(limited to 'pyproject.toml')
diff --git a/.github/workflows/format.yml b/.github/workflows/format.yml
index 4a5a509..8411d60 100644
--- a/.github/workflows/format.yml
+++ b/.github/workflows/format.yml
@@ -6,20 +6,24 @@ jobs:
build:
runs-on: ubuntu-latest
steps:
- - uses: actions/checkout@master
- - name: Set up Python
- uses: actions/setup-python@v3
- with:
- python-version: "3.10"
- - name: Install dependencies
- run: |
- python -m pip install -U pip poetry
- poetry --version
- poetry check --no-interaction
- poetry config virtualenvs.in-project true
- poetry install --no-interaction
- - name: Run CI
- run: |
- make lint
-
-
+ - uses: actions/checkout@master
+ - name: Set up Python
+ uses: actions/setup-python@v3
+ with:
+ python-version: "3.10"
+ - name: Install dependencies
+ run: |
+ python -m pip install -U pip poetry
+ poetry --version
+ poetry check --no-interaction
+ poetry config virtualenvs.in-project true
+ poetry install --no-interaction
+ - name: Check for format issues
+ run: |
+ make format-check
+ - name: Run pylint
+ run: |
+ poetry run pylint swr2_asr
+ - name: Run mypy
+ run: |
+ poetry run mypy --strict swr2_asr
diff --git a/Makefile b/Makefile
index 4f0ea9c..a37644c 100644
--- a/Makefile
+++ b/Makefile
@@ -1,6 +1,9 @@
format:
@poetry run black .
+format-check:
+ @poetry run black --check .
+
lint:
@poetry run mypy --strict swr2_asr
@poetry run pylint swr2_asr
\ No newline at end of file
diff --git a/mypy.ini b/mypy.ini
index f7cfc59..c13aa05 100644
--- a/mypy.ini
+++ b/mypy.ini
@@ -9,3 +9,9 @@ ignore_missing_imports = true
[mypy-click.*]
ignore_missing_imports = true
+
+[mypy-tokenizers.*]
+ignore_missing_imports = true
+
+[mypy-tqmd.*]
+ignore_missing_imports = true
\ No newline at end of file
diff --git a/poetry.lock b/poetry.lock
index 49d37d1..1f3609a 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -14,7 +14,10 @@ files = [
[package.dependencies]
lazy-object-proxy = ">=1.4.0"
typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
-wrapt = {version = ">=1.11,<2", markers = "python_version < \"3.11\""}
+wrapt = [
+ {version = ">=1.11,<2", markers = "python_version < \"3.11\""},
+ {version = ">=1.14,<2", markers = "python_version >= \"3.11\""},
+]
[[package]]
name = "AudioLoader"
@@ -680,7 +683,10 @@ files = [
[package.dependencies]
astroid = ">=2.15.6,<=2.17.0-dev0"
colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
-dill = {version = ">=0.2", markers = "python_version < \"3.11\""}
+dill = [
+ {version = ">=0.2", markers = "python_version < \"3.11\""},
+ {version = ">=0.3.6", markers = "python_version >= \"3.11\""},
+]
isort = ">=4.2.5,<6"
mccabe = ">=0.6,<0.8"
platformdirs = ">=2.2.0"
@@ -967,6 +973,17 @@ torch = "*"
tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)"]
tutorials = ["matplotlib", "pandas", "tabulate"]
+[[package]]
+name = "types-tqdm"
+version = "4.66.0.1"
+description = "Typing stubs for tqdm"
+optional = false
+python-versions = "*"
+files = [
+ {file = "types-tqdm-4.66.0.1.tar.gz", hash = "sha256:6457c90f03cc5a0fe8dd11839c8cbf5572bf542b438b1af74233801728b5dfbc"},
+ {file = "types_tqdm-4.66.0.1-py3-none-any.whl", hash = "sha256:6a1516788cbb33d725803439b79c25bfed7e8176b8d782020b5c24aedac1649b"},
+]
+
[[package]]
name = "typing-extensions"
version = "4.7.1"
@@ -1078,5 +1095,5 @@ files = [
[metadata]
lock-version = "2.0"
-python-versions = "~3.10"
-content-hash = "a72b4e5791a6216b58b53a72bf68d97dbdbc95978b3974fddd9e5f9b76e36321"
+python-versions = "^3.10"
+content-hash = "6b42e36364178f1670267137f73e8d2b2f3fc1d534a2b198d4ca3f65457d55c2"
diff --git a/pyproject.toml b/pyproject.toml
index eb17479..fabe364 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,6 +23,7 @@ black = "^23.7.0"
mypy = "^1.5.1"
pylint = "^2.17.5"
ruff = "^0.0.285"
+types-tqdm = "^4.66.0.1"
[tool.poetry.scripts]
train = "swr2_asr.train:run_cli"
diff --git a/swr2_asr/loss_scores.py b/swr2_asr/loss_scores.py
index 977462d..c49cc15 100644
--- a/swr2_asr/loss_scores.py
+++ b/swr2_asr/loss_scores.py
@@ -1,7 +1,9 @@
+"""Methods for determining the loss and scores of the model."""
import numpy as np
def avg_wer(wer_scores, combined_ref_len):
+ """Calculate the average word error rate (WER) of the model."""
return float(sum(wer_scores)) / float(combined_ref_len)
@@ -13,34 +15,34 @@ def _levenshtein_distance(ref, hyp):
extend the edits to word level when calculate levenshtein disctance for
two sentences.
"""
- m = len(ref)
- n = len(hyp)
+ len_ref = len(ref)
+ len_hyp = len(hyp)
# special case
if ref == hyp:
return 0
- if m == 0:
- return n
- if n == 0:
- return m
+ if len_ref == 0:
+ return len_hyp
+ if len_hyp == 0:
+ return len_ref
- if m < n:
+ if len_ref < len_hyp:
ref, hyp = hyp, ref
- m, n = n, m
+ len_ref, len_hyp = len_hyp, len_ref
# use O(min(m, n)) space
- distance = np.zeros((2, n + 1), dtype=np.int32)
+ distance = np.zeros((2, len_hyp + 1), dtype=np.int32)
# initialize distance matrix
- for j in range(0, n + 1):
+ for j in range(0, len_hyp + 1):
distance[0][j] = j
# calculate levenshtein distance
- for i in range(1, m + 1):
+ for i in range(1, len_ref + 1):
prev_row_idx = (i - 1) % 2
cur_row_idx = i % 2
distance[cur_row_idx][0] = i
- for j in range(1, n + 1):
+ for j in range(1, len_hyp + 1):
if ref[i - 1] == hyp[j - 1]:
distance[cur_row_idx][j] = distance[prev_row_idx][j - 1]
else:
@@ -49,7 +51,7 @@ def _levenshtein_distance(ref, hyp):
d_num = distance[prev_row_idx][j] + 1
distance[cur_row_idx][j] = min(s_num, i_num, d_num)
- return distance[m % 2][n]
+ return distance[len_ref % 2][len_hyp]
def word_errors(
@@ -143,8 +145,8 @@ def wer(reference: str, hypothesis: str, ignore_case=False, delimiter=" "):
if ref_len == 0:
raise ValueError("Reference's word number should be greater than 0.")
- wer = float(edit_distance) / ref_len
- return wer
+ word_error_rate = float(edit_distance) / ref_len
+ return word_error_rate
def cer(reference, hypothesis, ignore_case=False, remove_space=False):
@@ -181,5 +183,5 @@ def cer(reference, hypothesis, ignore_case=False, remove_space=False):
if ref_len == 0:
raise ValueError("Length of reference should be greater than 0.")
- cer = float(edit_distance) / ref_len
- return cer
+ char_error_rate = float(edit_distance) / ref_len
+ return char_error_rate
diff --git a/swr2_asr/tokenizer.py b/swr2_asr/tokenizer.py
index 79d6727..a665159 100644
--- a/swr2_asr/tokenizer.py
+++ b/swr2_asr/tokenizer.py
@@ -63,15 +63,15 @@ class CharTokenizer:
else:
splits = [split]
- chars = set()
- for sp in splits:
+ chars: set = set()
+ for s_plit in splits:
transcript_path = os.path.join(
- dataset_path, language, sp, "transcripts.txt"
+ dataset_path, language, s_plit, "transcripts.txt"
)
# check if dataset is downloaded, download if not
if download and not os.path.exists(transcript_path):
- MultilingualLibriSpeech(dataset_path, language, sp, download=True)
+ MultilingualLibriSpeech(dataset_path, language, s_plit, download=True)
with open(
transcript_path,
@@ -82,7 +82,7 @@ class CharTokenizer:
lines = [line.split(" ", 1)[1] for line in lines]
lines = [line.strip() for line in lines]
- for line in tqdm(lines, desc=f"Training tokenizer on {sp} split"):
+ for line in tqdm(lines, desc=f"Training tokenizer on {s_plit} split"):
chars.update(line)
offset = len(self.char_map)
for i, char in enumerate(chars):
@@ -205,10 +205,12 @@ def train_bpe_tokenizer(
lines = []
- for sp in splits:
- transcripts_path = os.path.join(dataset_path, language, sp, "transcripts.txt")
+ for s_plit in splits:
+ transcripts_path = os.path.join(
+ dataset_path, language, s_plit, "transcripts.txt"
+ )
if download and not os.path.exists(transcripts_path):
- MultilingualLibriSpeech(dataset_path, language, sp, download=True)
+ MultilingualLibriSpeech(dataset_path, language, s_plit, download=True)
with open(
transcripts_path,
diff --git a/swr2_asr/train.py b/swr2_asr/train.py
index 8943f71..6af1e80 100644
--- a/swr2_asr/train.py
+++ b/swr2_asr/train.py
@@ -83,7 +83,7 @@ class CNNLayerNorm(nn.Module):
"""Layer normalization built for cnns input"""
def __init__(self, n_feats: int):
- super(CNNLayerNorm, self).__init__()
+ super().__init__()
self.layer_norm = nn.LayerNorm(n_feats)
def forward(self, data):
@@ -105,7 +105,7 @@ class ResidualCNN(nn.Module):
dropout: float,
n_feats: int,
):
- super(ResidualCNN, self).__init__()
+ super().__init__()
self.cnn1 = nn.Conv2d(
in_channels, out_channels, kernel, stride, padding=kernel // 2
@@ -147,7 +147,7 @@ class BidirectionalGRU(nn.Module):
dropout: float,
batch_first: bool,
):
- super(BidirectionalGRU, self).__init__()
+ super().__init__()
self.bi_gru = nn.GRU(
input_size=rnn_dim,
@@ -181,7 +181,7 @@ class SpeechRecognitionModel(nn.Module):
stride: int = 2,
dropout: float = 0.1,
):
- super(SpeechRecognitionModel, self).__init__()
+ super().__init__()
n_feats //= 2
self.cnn = nn.Conv2d(1, 32, 3, stride=stride, padding=3 // 2)
# n residual cnn layers with filter size of 32
@@ -227,7 +227,7 @@ class SpeechRecognitionModel(nn.Module):
return data
-class IterMeter(object):
+class IterMeter:
"""keeps track of total iterations"""
def __init__(self):
@@ -381,7 +381,7 @@ def run(
).to(device)
print(
- "Num Model Parameters", sum([param.nelement() for param in model.parameters()])
+ "Num Model Parameters", sum((param.nelement() for param in model.parameters()))
)
optimizer = optim.AdamW(model.parameters(), hparams["learning_rate"])
criterion = nn.CTCLoss(blank=28).to(device)
--
cgit v1.2.3