From 403472ca4e65e8ed404e8a73fb9b3fbafe3f2a53 Mon Sep 17 00:00:00 2001
From: Pherkel
Date: Thu, 24 Aug 2023 00:03:56 +0200
Subject: wip: commit before going on vacation :)

---
 pyproject.toml | 9 +++++++++
 1 file changed, 9 insertions(+)

(limited to 'pyproject.toml')

diff --git a/pyproject.toml b/pyproject.toml
index fabe364..94f7553 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,6 +25,15 @@ pylint = "^2.17.5"
 ruff = "^0.0.285"
 types-tqdm = "^4.66.0.1"
 
+[tool.ruff]
+select = ["E", "F", "B", "I"]
+fixable = ["ALL"]
+line-length = 120
+target-version = "py310"
+
+[tool.black]
+line-length = 120
+
 [tool.poetry.scripts]
 train = "swr2_asr.train:run_cli"
 train-bpe-tokenizer = "swr2_asr.tokenizer:train_bpe_tokenizer"
-- 
cgit v1.2.3


From 9b450c685e9ec4e7e74688de3d6dbb719b19fcf6 Mon Sep 17 00:00:00 2001
From: Pherkel
Date: Tue, 29 Aug 2023 11:55:08 +0200
Subject: added padding calculation for audiofiles

---
 poetry.lock       | 187 +++++++++++++++++++++++++++++++++++++++++++++++++++++-
 pyproject.toml    |   1 +
 swr2_asr/utils.py | 108 +++++++++++++++++++++++--------
 3 files changed, 267 insertions(+), 29 deletions(-)

(limited to 'pyproject.toml')

diff --git a/poetry.lock b/poetry.lock
index 1f3609a..77643f5 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -19,6 +19,50 @@ wrapt = [
     {version = ">=1.14,<2", markers = "python_version >= \"3.11\""},
 ]
 
+[[package]]
+name = "attrs"
+version = "19.3.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "attrs-19.3.0-py2.py3-none-any.whl", hash = "sha256:08a96c641c3a74e44eb59afb61a24f2cb9f4d7188748e76ba4bb5edfa3cb7d1c"},
+    {file = "attrs-19.3.0.tar.gz", hash = "sha256:f7b7ce16570fe9965acd6d30101a28f62fb4a7f9e926b3bbc9b61f8b04247e72"},
+]
+
+[package.extras]
+azure-pipelines = ["coverage", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-azurepipelines", "six", "zope.interface"]
+dev = ["coverage", "hypothesis", "pre-commit", "pympler", "pytest (>=4.3.0)", "six", "sphinx", "zope.interface"]
+docs = ["sphinx", "zope.interface"]
+tests = ["coverage", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "zope.interface"]
+
+[[package]]
+name = "audio-metadata"
+version = "0.11.1"
+description = "A library for reading and, in the future, writing metadata from audio files."
+optional = false
+python-versions = ">=3.6,<4.0"
+files = [
+    {file = "audio-metadata-0.11.1.tar.gz", hash = "sha256:9e7ba79d49cf048a911d5f7d55bb2715c10be5c127fe5db0987c5fe1aa7335eb"},
+    {file = "audio_metadata-0.11.1-py3-none-any.whl", hash = "sha256:f5b85ad087324c255f8d1223574c3e7d3c27b649e411d1dd54aa3bf342fe93fb"},
+]
+
+[package.dependencies]
+attrs = ">=18.2,<19.4"
+bidict = "<1.0.0"
+bitstruct = ">=6.0,<9.0"
+more-itertools = ">=4.0,<9.0"
+pendulum = ">=2.0,<2.0.5 || >2.0.5,<2.1.0 || >2.1.0,<=3.0"
+pprintpp = "<1.0.0"
+tbm-utils = ">=2.3,<3.0"
+wrapt = ">=1.0,<2.0"
+
+[package.extras]
+dev = ["coverage[toml] (>=5.0,<6.0)", "flake8 (>=3.5,<4.0)", "flake8-builtins (>=1.0,<2.0)", "flake8-comprehensions (>=2.0,<=4.0)", "flake8-import-order (>=0.18,<0.19)", "flake8-import-order-tbm (>=1.0,<2.0)", "nox (>=2019,<2020)", "sphinx (>=2.0,<3.0)", "sphinx-material (<1.0.0)", "ward (>=0.42.0-beta.0)"]
+doc = ["sphinx (>=2.0,<3.0)", "sphinx-material (<1.0.0)"]
+lint = ["flake8 (>=3.5,<4.0)", "flake8-builtins (>=1.0,<2.0)", "flake8-comprehensions (>=2.0,<=4.0)", "flake8-import-order (>=0.18,<0.19)", "flake8-import-order-tbm (>=1.0,<2.0)"]
+test = ["coverage[toml] (>=5.0,<6.0)", "nox (>=2019,<2020)", "ward (>=0.42.0-beta.0)"]
+
 [[package]]
 name = "AudioLoader"
 version = "0.1.4"
@@ -34,6 +78,32 @@ url = "https://github.com/marvinborner/AudioLoader.git"
 reference = "HEAD"
 resolved_reference = "8fb829bf7fb98f26f8456dc22ef0fe2c7bb38ac2"
 
+[[package]]
+name = "bidict"
+version = "0.22.1"
+description = "The bidirectional mapping library for Python."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "bidict-0.22.1-py3-none-any.whl", hash = "sha256:6ef212238eb884b664f28da76f33f1d28b260f665fc737b413b287d5487d1e7b"},
+    {file = "bidict-0.22.1.tar.gz", hash = "sha256:1e0f7f74e4860e6d0943a05d4134c63a2fad86f3d4732fb265bd79e4e856d81d"},
+]
+
+[package.extras]
+docs = ["furo", "sphinx", "sphinx-copybutton"]
+lint = ["pre-commit"]
+test = ["hypothesis", "pytest", "pytest-benchmark[histogram]", "pytest-cov", "pytest-xdist", "sortedcollections", "sortedcontainers", "sphinx"]
+
+[[package]]
+name = "bitstruct"
+version = "8.17.0"
+description = "This module performs conversions between Python values and C bit field structs represented as Python byte strings."
+optional = false
+python-versions = "*"
+files = [
+    {file = "bitstruct-8.17.0.tar.gz", hash = "sha256:eb94b40e4218a23aa8f90406b836a9e6ed83e48b8d112ce3f96408463bd1b874"},
+]
+
 [[package]]
 name = "black"
 version = "23.7.0"
@@ -348,6 +418,17 @@ ports-rtmidi-python = ["rtmidi-python (>=0.2.2,<0.3.0)"]
 release = ["twine (>=4.0.2,<4.1.0)"]
 test-code = ["pytest (>=7.4.0,<7.5.0)"]
 
+[[package]]
+name = "more-itertools"
+version = "8.14.0"
+description = "More routines for operating on iterables, beyond itertools"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "more-itertools-8.14.0.tar.gz", hash = "sha256:c09443cd3d5438b8dafccd867a6bc1cb0894389e90cb53d227456b0b0bccb750"},
+    {file = "more_itertools-8.14.0-py3-none-any.whl", hash = "sha256:1bc4f91ee5b1b31ac7ceacc17c09befe6a40a503907baf9c839c229b5095cfd2"},
+]
+
 [[package]]
 name = "mpmath"
 version = "1.3.0"
@@ -654,6 +735,40 @@ files = [
     {file = "pathspec-0.11.2.tar.gz", hash = "sha256:e0d8d0ac2f12da61956eb2306b69f9469b42f4deb0f3cb6ed47b9cce9996ced3"},
 ]
 
+[[package]]
+name = "pendulum"
+version = "2.1.2"
+description = "Python datetimes made easy"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
+    {file = "pendulum-2.1.2-cp27-cp27m-macosx_10_15_x86_64.whl", hash = "sha256:b6c352f4bd32dff1ea7066bd31ad0f71f8d8100b9ff709fb343f3b86cee43efe"},
+    {file = "pendulum-2.1.2-cp27-cp27m-win_amd64.whl", hash = "sha256:318f72f62e8e23cd6660dbafe1e346950281a9aed144b5c596b2ddabc1d19739"},
+    {file = "pendulum-2.1.2-cp35-cp35m-macosx_10_15_x86_64.whl", hash = "sha256:0731f0c661a3cb779d398803655494893c9f581f6488048b3fb629c2342b5394"},
+    {file = "pendulum-2.1.2-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:3481fad1dc3f6f6738bd575a951d3c15d4b4ce7c82dce37cf8ac1483fde6e8b0"},
+    {file = "pendulum-2.1.2-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:9702069c694306297ed362ce7e3c1ef8404ac8ede39f9b28b7c1a7ad8c3959e3"},
+    {file = "pendulum-2.1.2-cp35-cp35m-win_amd64.whl", hash = "sha256:fb53ffa0085002ddd43b6ca61a7b34f2d4d7c3ed66f931fe599e1a531b42af9b"},
+    {file = "pendulum-2.1.2-cp36-cp36m-macosx_10_15_x86_64.whl", hash = "sha256:c501749fdd3d6f9e726086bf0cd4437281ed47e7bca132ddb522f86a1645d360"},
+    {file = "pendulum-2.1.2-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:c807a578a532eeb226150d5006f156632df2cc8c5693d778324b43ff8c515dd0"},
+    {file = "pendulum-2.1.2-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:2d1619a721df661e506eff8db8614016f0720ac171fe80dda1333ee44e684087"},
+    {file = "pendulum-2.1.2-cp36-cp36m-win_amd64.whl", hash = "sha256:f888f2d2909a414680a29ae74d0592758f2b9fcdee3549887779cd4055e975db"},
+    {file = "pendulum-2.1.2-cp37-cp37m-macosx_10_15_x86_64.whl", hash = "sha256:e95d329384717c7bf627bf27e204bc3b15c8238fa8d9d9781d93712776c14002"},
+    {file = "pendulum-2.1.2-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:4c9c689747f39d0d02a9f94fcee737b34a5773803a64a5fdb046ee9cac7442c5"},
+    {file = "pendulum-2.1.2-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:1245cd0075a3c6d889f581f6325dd8404aca5884dea7223a5566c38aab94642b"},
+    {file = "pendulum-2.1.2-cp37-cp37m-win_amd64.whl", hash = "sha256:db0a40d8bcd27b4fb46676e8eb3c732c67a5a5e6bfab8927028224fbced0b40b"},
+    {file = "pendulum-2.1.2-cp38-cp38-macosx_10_15_x86_64.whl", hash = "sha256:f5e236e7730cab1644e1b87aca3d2ff3e375a608542e90fe25685dae46310116"},
+    {file = "pendulum-2.1.2-cp38-cp38-manylinux1_i686.whl", hash = "sha256:de42ea3e2943171a9e95141f2eecf972480636e8e484ccffaf1e833929e9e052"},
+    {file = "pendulum-2.1.2-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:7c5ec650cb4bec4c63a89a0242cc8c3cebcec92fcfe937c417ba18277d8560be"},
+    {file = "pendulum-2.1.2-cp38-cp38-win_amd64.whl", hash = "sha256:33fb61601083f3eb1d15edeb45274f73c63b3c44a8524703dc143f4212bf3269"},
+    {file = "pendulum-2.1.2-cp39-cp39-manylinux1_i686.whl", hash = "sha256:29c40a6f2942376185728c9a0347d7c0f07905638c83007e1d262781f1e6953a"},
+    {file = "pendulum-2.1.2-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:94b1fc947bfe38579b28e1cccb36f7e28a15e841f30384b5ad6c5e31055c85d7"},
+    {file = "pendulum-2.1.2.tar.gz", hash = "sha256:b06a0ca1bfe41c990bbf0c029f0b6501a7f2ec4e38bfec730712015e8860f207"},
+]
+
+[package.dependencies]
+python-dateutil = ">=2.6,<3.0"
+pytzdata = ">=2020.1"
+
 [[package]]
 name = "platformdirs"
 version = "3.10.0"
@@ -669,6 +784,17 @@ files = [
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.1)", "sphinx-autodoc-typehints (>=1.24)"]
 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"]
 
+[[package]]
+name = "pprintpp"
+version = "0.4.0"
+description = "A drop-in replacement for pprint that's actually pretty"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pprintpp-0.4.0-py2.py3-none-any.whl", hash = "sha256:b6b4dcdd0c0c0d75e4d7b2f21a9e933e5b2ce62b26e1a54537f9651ae5a5c01d"},
+    {file = "pprintpp-0.4.0.tar.gz", hash = "sha256:ea826108e2c7f49dc6d66c752973c3fc9749142a798d6b254e1e301cfdbc6403"},
+]
+
 [[package]]
 name = "pylint"
 version = "2.17.5"
@@ -697,6 +823,31 @@ tomlkit = ">=0.10.1"
 spelling = ["pyenchant (>=3.2,<4.0)"]
 testutils = ["gitpython (>3)"]
 
+[[package]]
+name = "python-dateutil"
+version = "2.8.2"
+description = "Extensions to the standard Python datetime module"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
+files = [
+    {file = "python-dateutil-2.8.2.tar.gz", hash = "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86"},
+    {file = "python_dateutil-2.8.2-py2.py3-none-any.whl", hash = "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"},
+]
+
+[package.dependencies]
+six = ">=1.5"
+
+[[package]]
+name = "pytzdata"
+version = "2020.1"
+description = "The Olson timezone database for Python."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "pytzdata-2020.1-py2.py3-none-any.whl", hash = "sha256:e1e14750bcf95016381e4d472bad004eef710f2d6417240904070b3d6654485f"},
+    {file = "pytzdata-2020.1.tar.gz", hash = "sha256:3efa13b335a00a8de1d345ae41ec78dd11c9f8807f522d39850f2dd828681540"},
+]
+
 [[package]]
 name = "ruff"
 version = "0.0.285"
@@ -739,6 +890,17 @@ docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments
 testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
+[[package]]
+name = "six"
+version = "1.16.0"
+description = "Python 2 and 3 compatibility utilities"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
+    {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
+]
+
 [[package]]
 name = "sympy"
 version = "1.12"
@@ -753,6 +915,29 @@ files = [
 [package.dependencies]
 mpmath = ">=0.19"
 
+[[package]]
+name = "tbm-utils"
+version = "2.6.0"
+description = "A commonly-used set of utilities used by me (thebigmunch)."
+optional = false
+python-versions = ">=3.6,<4.0"
+files = [
+    {file = "tbm-utils-2.6.0.tar.gz", hash = "sha256:235748cceeb22c042e32d2fdfd4d710021bac9b938c4f2c35e1fce1cfd58f7ec"},
+    {file = "tbm_utils-2.6.0-py3-none-any.whl", hash = "sha256:692b5cde2b810bb84e55ca0f5f6c055ca6ad321c4d5acc0cade98af97c5998e2"},
+]
+
+[package.dependencies]
+attrs = ">=18.2,<19.4"
+pendulum = ">=2.0,<2.0.5 || >2.0.5,<2.1.0 || >2.1.0,<=3.0"
+pprintpp = "<1.0.0"
+wrapt = ">=1.0,<2.0"
+
+[package.extras]
+dev = ["coverage[toml] (>=4.5,<6.0)", "flake8 (>=3.5,<4.0)", "flake8-builtins (>=1.0,<2.0)", "flake8-comprehensions (>=2.0,<=4.0)", "flake8-import-order (>=0.18,<0.19)", "flake8-import-order-tbm (>=1.0,<2.0)", "nox (>=2019,<2020)", "pytest (>=4.0,<6.0)", "sphinx (>=2.0,<3.0)", "sphinx-material (<1.0.0)"]
+doc = ["sphinx (>=2.0,<3.0)", "sphinx-material (<1.0.0)"]
+lint = ["flake8 (>=3.5,<4.0)", "flake8-builtins (>=1.0,<2.0)", "flake8-comprehensions (>=2.0,<=4.0)", "flake8-import-order (>=0.18,<0.19)", "flake8-import-order-tbm (>=1.0,<2.0)"]
+test = ["coverage[toml] (>=4.5,<6.0)", "nox (>=2019,<2020)", "pytest (>=4.0,<6.0)"]
+
 [[package]]
 name = "tokenizers"
 version = "0.13.3"
@@ -1096,4 +1281,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "6b42e36364178f1670267137f73e8d2b2f3fc1d534a2b198d4ca3f65457d55c2"
+content-hash = "992e0eb975f6fb490726bc9db470a682986c1a287078bec407a4a6dc96e45b3c"
diff --git a/pyproject.toml b/pyproject.toml
index 94f7553..dc136f2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -17,6 +17,7 @@ numpy = "^1.25.2"
 mido = "^1.3.0"
 tokenizers = "^0.13.3"
 click = "^8.1.7"
+audio-metadata = "^0.11.1"
 
 [tool.poetry.group.dev.dependencies]
 black = "^23.7.0"
diff --git a/swr2_asr/utils.py b/swr2_asr/utils.py
index 786fbcf..404661d 100644
--- a/swr2_asr/utils.py
+++ b/swr2_asr/utils.py
@@ -1,6 +1,7 @@
 """Class containing utils for the ASR system."""
 import os
 from enum import Enum
+from multiprocessing import Pool
 from typing import TypedDict
 
 import numpy as np
@@ -8,6 +9,8 @@ import torch
 import torchaudio
 from tokenizers import Tokenizer
 from torch.utils.data import Dataset
+from tqdm import tqdm
+import audio_metadata
 
 from swr2_asr.tokenizer import CharTokenizer, TokenizerType
 
@@ -133,11 +136,13 @@ class MLSDataset(Dataset):
                 for path, utterance in zip(identifier, utterances, strict=False)
             ]
 
+        self.max_spec_length = 0
+        self.max_utterance_length = 0
+
     def set_tokenizer(self, tokenizer: type[TokenizerType]):
         """Sets the tokenizer"""
         self.tokenizer = tokenizer
-
-        self.calc_paddings()
+        # self.calc_paddings()
 
     def _handle_download_dataset(self, download: bool):
         """Download the dataset"""
@@ -158,27 +163,73 @@ class MLSDataset(Dataset):
         if not os.path.exists(os.path.join(self.dataset_path, self.language, self.mls_split)):
             raise ValueError("Split not found in dataset")
 
-    def calc_paddings(self):
-        """Sets the maximum length of the spectrogram"""
+    def _calculate_max_length(self, chunk):
+        """Calculates the maximum length of the spectrogram and the utterance
+
+        to be called in a multiprocessing pool
+        """
+        max_spec_length = 0
+        max_utterance_length = 0
+
+        for sample in chunk:
+            audio_path = os.path.join(
+                self.dataset_path,
+                self.language,
+                self.mls_split,
+                "audio",
+                sample["speakerid"],
+                sample["bookid"],
+                "_".join(
+                    [
+                        sample["speakerid"],
+                        sample["bookid"],
+                        sample["chapterid"],
+                    ]
+                )
+                + self.file_ext,
+            )
+            metadata = audio_metadata.load(audio_path)
+            audio_duration = metadata.streaminfo.duration
+            sample_rate = metadata.streaminfo.sample_rate
+
+            max_spec_length = int(max(max_spec_length, (audio_duration * sample_rate) // 200))
+            max_utterance_length = max(max_utterance_length, len(self.tokenizer.encode(sample["utterance"]).ids))
+
+        return max_spec_length, max_utterance_length
+
+    def calc_paddings(self) -> None:
+        """Sets the maximum length of the spectrogram and the utterance"""
         # check if dataset has been loaded and tokenizer has been set
         if not self.dataset_lookup:
             raise ValueError("Dataset not loaded")
         if not self.tokenizer:
             raise ValueError("Tokenizer not set")
-
-        max_spec_length = 0
-        max_uterance_length = 0
-        for sample in self.dataset_lookup:
-            spec_length = sample["spectrogram"].shape[0]
-            if spec_length > max_spec_length:
-                max_spec_length = spec_length
-
-            utterance_length = sample["utterance"].shape[0]
-            if utterance_length > max_uterance_length:
-                max_uterance_length = utterance_length
-
-        self.max_spec_length = max_spec_length
-        self.max_utterance_length = max_uterance_length
+        # check if paddings have been calculated already
+        if os.path.isfile(os.path.join(self.dataset_path, self.language, self.mls_split, "paddings.txt")):
+            print("Paddings already calculated")
+            with open(os.path.join(self.dataset_path, self.language, self.mls_split, "paddings.txt"), "r") as f:
+                self.max_spec_length, self.max_utterance_length = [int(line.strip()) for line in f.readlines()]
+            return
+        else:
+            print("Calculating paddings...")
+
+        thread_count = os.cpu_count()
+        if thread_count is None:
+            thread_count = 4
+        chunk_size = len(self.dataset_lookup) // thread_count
+        chunks = [self.dataset_lookup[i : i + chunk_size] for i in range(0, len(self.dataset_lookup), chunk_size)]
+
+        with Pool(thread_count) as p:
+            results = list(p.imap(self._calculate_max_length, chunks))
+
+        for spec, utterance in results:
+            self.max_spec_length = max(self.max_spec_length, spec)
+            self.max_utterance_length = max(self.max_utterance_length, utterance)
+
+        # write to file
+        with open(os.path.join(self.dataset_path, self.language, self.mls_split, "paddings.txt"), "w") as f:
+            f.write(f"{self.max_spec_length}\n")
+            f.write(f"{self.max_utterance_length}")
 
     def __len__(self):
         """Returns the length of the dataset"""
@@ -208,18 +259,18 @@ class MLSDataset(Dataset):
         )
 
         waveform, sample_rate = torchaudio.load(audio_path)  # type: ignore
-        # TODO: figure out if we have to resample or not
-        # TODO: pad correctly (manually)
+
+        # resample if necessary
+        if sample_rate != 16000:
+            resampler = torchaudio.transforms.Resample(sample_rate, 16000)
+            waveform = resampler(waveform)
+            sample_rate = 16000
+
         spec = torchaudio.transforms.MelSpectrogram(sample_rate=16000, n_mels=128)(waveform).squeeze(0).transpose(0, 1)
-        print(f"spec.shape: {spec.shape}")
-        input_length = spec.shape[0] // 2
-        spec = (
-            torch.nn.functional.pad(spec, pad=(0, self.max_spec_length), mode="constant", value=0)
-            .unsqueeze(1)
-            .transpose(2, 3)
-        )
 
+        input_length = spec.shape[0] // 2
         utterance_length = len(utterance)
+
         self.tokenizer.enable_padding()
         utterance = self.tokenizer.encode(
             utterance,
@@ -260,4 +311,5 @@ if __name__ == "__main__":
     dataset.set_tokenizer(tok)
     dataset.calc_paddings()
 
-    print(dataset[41]["spectrogram"].shape)
+    print(f"Spectrogram shape: {dataset[41]['spectrogram'].shape}")
+    print(f"Utterance shape: {dataset[41]['utterance'].shape}")
-- 
cgit v1.2.3


From 33f09080aee10bddb4797a557d676ee1f7b8de31 Mon Sep 17 00:00:00 2001
From: Pherkel
Date: Sun, 3 Sep 2023 19:30:33 +0200
Subject: idk, hopefully this works

---
 poetry.lock                   | 685 +++++++++++++++++++++++++++++++++++++++++-
 pyproject.toml                |   3 +-
 swr2_asr/inference_test.py    |   4 +-
 swr2_asr/loss_scores.py       |   8 +-
 swr2_asr/model_deep_speech.py |  13 +-
 swr2_asr/tokenizer.py         |  17 +-
 swr2_asr/train.py             |  90 +++---
 swr2_asr/utils.py             |  85 +++---
 8 files changed, 807 insertions(+), 98 deletions(-)

(limited to 'pyproject.toml')

diff --git a/poetry.lock b/poetry.lock
index 77643f5..38cba87 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,15 @@
-# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+
+[[package]]
+name = "appnope"
+version = "0.1.3"
+description = "Disable App Nap on macOS >= 10.9"
+optional = false
+python-versions = "*"
+files = [
+    {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"},
+    {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
+]
 
 [[package]]
 name = "astroid"
@@ -19,6 +30,23 @@ wrapt = [
     {version = ">=1.14,<2", markers = "python_version >= \"3.11\""},
 ]
 
+[[package]]
+name = "asttokens"
+version = "2.3.0"
+description = "Annotate AST trees with source code positions"
+optional = false
+python-versions = "*"
+files = [
+    {file = "asttokens-2.3.0-py2.py3-none-any.whl", hash = "sha256:bef1a51bc256d349e9f94e7e40e44b705ed1162f55294220dd561d24583d9877"},
+    {file = "asttokens-2.3.0.tar.gz", hash = "sha256:2552a88626aaa7f0f299f871479fc755bd4e7c11e89078965e928fb7bb9a6afe"},
+]
+
+[package.dependencies]
+six = ">=1.12.0"
+
+[package.extras]
+test = ["astroid", "pytest"]
+
 [[package]]
 name = "attrs"
 version = "19.3.0"
@@ -78,6 +106,17 @@ url = "https://github.com/marvinborner/AudioLoader.git"
 reference = "HEAD"
 resolved_reference = "8fb829bf7fb98f26f8456dc22ef0fe2c7bb38ac2"
 
+[[package]]
+name = "backcall"
+version = "0.2.0"
+description = "Specifications for callback functions passed in to an API"
+optional = false
+python-versions = "*"
+files = [
+    {file = "backcall-0.2.0-py2.py3-none-any.whl", hash = "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"},
+    {file = "backcall-0.2.0.tar.gz", hash = "sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e"},
+]
+
 [[package]]
 name = "bidict"
 version = "0.22.1"
@@ -149,6 +188,82 @@ d = ["aiohttp (>=3.7.4)"]
 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
+[[package]]
+name = "cffi"
+version = "1.15.1"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = "*"
+files = [
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+    {file = "cffi-1.15.1-cp39-cp39-win_amd64.whl", hash = "sha256:70df4e3b545a17496c9b3f41f5115e69a4f2e77e94e1d2a8e1070bc0c38c8a3c"},
+    {file = "cffi-1.15.1.tar.gz", hash = "sha256:d400bfb9a37b1351253cb402671cea7e89bdecc294e8016a707f6d1d8ac934f9"},
+]
+
+[package.dependencies]
+pycparser = "*"
+
 [[package]]
 name = "click"
 version = "8.1.7"
@@ -203,6 +318,63 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "comm"
+version = "0.1.4"
+description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "comm-0.1.4-py3-none-any.whl", hash = "sha256:6d52794cba11b36ed9860999cd10fd02d6b2eac177068fdd585e1e2f8a96e67a"},
+    {file = "comm-0.1.4.tar.gz", hash = "sha256:354e40a59c9dd6db50c5cc6b4acc887d82e9603787f83b68c01a80a923984d15"},
+]
+
+[package.dependencies]
+traitlets = ">=4"
+
+[package.extras]
+lint = ["black (>=22.6.0)", "mdformat (>0.7)", "mdformat-gfm (>=0.3.5)", "ruff (>=0.0.156)"]
+test = ["pytest"]
+typing = ["mypy (>=0.990)"]
+
+[[package]]
+name = "debugpy"
+version = "1.6.7.post1"
+description = "An implementation of the Debug Adapter Protocol for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "debugpy-1.6.7.post1-cp310-cp310-macosx_11_0_x86_64.whl", hash = "sha256:903bd61d5eb433b6c25b48eae5e23821d4c1a19e25c9610205f5aeaccae64e32"},
+    {file = "debugpy-1.6.7.post1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d16882030860081e7dd5aa619f30dec3c2f9a421e69861125f83cc372c94e57d"},
+    {file = "debugpy-1.6.7.post1-cp310-cp310-win32.whl", hash = "sha256:eea8d8cfb9965ac41b99a61f8e755a8f50e9a20330938ad8271530210f54e09c"},
+    {file = "debugpy-1.6.7.post1-cp310-cp310-win_amd64.whl", hash = "sha256:85969d864c45f70c3996067cfa76a319bae749b04171f2cdeceebe4add316155"},
+    {file = "debugpy-1.6.7.post1-cp37-cp37m-macosx_11_0_x86_64.whl", hash = "sha256:890f7ab9a683886a0f185786ffbda3b46495c4b929dab083b8c79d6825832a52"},
+    {file = "debugpy-1.6.7.post1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d4ac7a4dba28801d184b7fc0e024da2635ca87d8b0a825c6087bb5168e3c0d28"},
+    {file = "debugpy-1.6.7.post1-cp37-cp37m-win32.whl", hash = "sha256:3370ef1b9951d15799ef7af41f8174194f3482ee689988379763ef61a5456426"},
+    {file = "debugpy-1.6.7.post1-cp37-cp37m-win_amd64.whl", hash = "sha256:65b28435a17cba4c09e739621173ff90c515f7b9e8ea469b92e3c28ef8e5cdfb"},
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+    {file = "debugpy-1.6.7.post1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:72f5d2ecead8125cf669e62784ef1e6300f4067b0f14d9f95ee00ae06fc7c4f7"},
+    {file = "debugpy-1.6.7.post1-cp38-cp38-win32.whl", hash = "sha256:f0851403030f3975d6e2eaa4abf73232ab90b98f041e3c09ba33be2beda43fcf"},
+    {file = "debugpy-1.6.7.post1-cp38-cp38-win_amd64.whl", hash = "sha256:3de5d0f97c425dc49bce4293df6a04494309eedadd2b52c22e58d95107e178d9"},
+    {file = "debugpy-1.6.7.post1-cp39-cp39-macosx_11_0_x86_64.whl", hash = "sha256:38651c3639a4e8bbf0ca7e52d799f6abd07d622a193c406be375da4d510d968d"},
+    {file = "debugpy-1.6.7.post1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:038c51268367c9c935905a90b1c2d2dbfe304037c27ba9d19fe7409f8cdc710c"},
+    {file = "debugpy-1.6.7.post1-cp39-cp39-win32.whl", hash = "sha256:4b9eba71c290852f959d2cf8a03af28afd3ca639ad374d393d53d367f7f685b2"},
+    {file = "debugpy-1.6.7.post1-cp39-cp39-win_amd64.whl", hash = "sha256:973a97ed3b434eab0f792719a484566c35328196540676685c975651266fccf9"},
+    {file = "debugpy-1.6.7.post1-py2.py3-none-any.whl", hash = "sha256:1093a5c541af079c13ac8c70ab8b24d1d35c8cacb676306cf11e57f699c02926"},
+    {file = "debugpy-1.6.7.post1.zip", hash = "sha256:fe87ec0182ef624855d05e6ed7e0b7cb1359d2ffa2a925f8ec2d22e98b75d0ca"},
+]
+
+[[package]]
+name = "decorator"
+version = "5.1.1"
+description = "Decorators for Humans"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "decorator-5.1.1-py3-none-any.whl", hash = "sha256:b8c3f85900b9dc423225913c5aace94729fe1fa9763b38939a95226f02d37186"},
+    {file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
+]
+
 [[package]]
 name = "dill"
 version = "0.3.7"
@@ -217,6 +389,34 @@ files = [
 [package.extras]
 graph = ["objgraph (>=1.7.2)"]
 
+[[package]]
+name = "exceptiongroup"
+version = "1.1.3"
+description = "Backport of PEP 654 (exception groups)"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
+    {file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
+]
+
+[package.extras]
+test = ["pytest (>=6)"]
+
+[[package]]
+name = "executing"
+version = "1.2.0"
+description = "Get the currently executing AST node of a frame, and other information"
+optional = false
+python-versions = "*"
+files = [
+    {file = "executing-1.2.0-py2.py3-none-any.whl", hash = "sha256:0314a69e37426e3608aada02473b4161d4caf5a4b244d1d0c48072b8fee7bacc"},
+    {file = "executing-1.2.0.tar.gz", hash = "sha256:19da64c18d2d851112f09c287f8d3dbbdf725ab0e569077efb6cdcbd3497c107"},
+]
+
+[package.extras]
+tests = ["asttokens", "littleutils", "pytest", "rich"]
+
 [[package]]
 name = "filelock"
 version = "3.12.2"
@@ -232,6 +432,78 @@ files = [
 docs = ["furo (>=2023.5.20)", "sphinx (>=7.0.1)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
 testing = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4.1)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
 
+[[package]]
+name = "ipykernel"
+version = "6.25.1"
+description = "IPython Kernel for Jupyter"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "ipykernel-6.25.1-py3-none-any.whl", hash = "sha256:c8a2430b357073b37c76c21c52184db42f6b4b0e438e1eb7df3c4440d120497c"},
+    {file = "ipykernel-6.25.1.tar.gz", hash = "sha256:050391364c0977e768e354bdb60cbbfbee7cbb943b1af1618382021136ffd42f"},
+]
+
+[package.dependencies]
+appnope = {version = "*", markers = "platform_system == \"Darwin\""}
+comm = ">=0.1.1"
+debugpy = ">=1.6.5"
+ipython = ">=7.23.1"
+jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+matplotlib-inline = ">=0.1"
+nest-asyncio = "*"
+packaging = "*"
+psutil = "*"
+pyzmq = ">=20"
+tornado = ">=6.1"
+traitlets = ">=5.4.0"
+
+[package.extras]
+cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
+pyqt5 = ["pyqt5"]
+pyside6 = ["pyside6"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "ipython"
+version = "8.15.0"
+description = "IPython: Productive Interactive Computing"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "ipython-8.15.0-py3-none-any.whl", hash = "sha256:45a2c3a529296870a97b7de34eda4a31bee16bc7bf954e07d39abe49caf8f887"},
+    {file = "ipython-8.15.0.tar.gz", hash = "sha256:2baeb5be6949eeebf532150f81746f8333e2ccce02de1c7eedde3f23ed5e9f1e"},
+]
+
+[package.dependencies]
+appnope = {version = "*", markers = "sys_platform == \"darwin\""}
+backcall = "*"
+colorama = {version = "*", markers = "sys_platform == \"win32\""}
+decorator = "*"
+exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+jedi = ">=0.16"
+matplotlib-inline = "*"
+pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
+pickleshare = "*"
+prompt-toolkit = ">=3.0.30,<3.0.37 || >3.0.37,<3.1.0"
+pygments = ">=2.4.0"
+stack-data = "*"
+traitlets = ">=5"
+
+[package.extras]
+all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.21)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
+black = ["black"]
+doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
+kernel = ["ipykernel"]
+nbconvert = ["nbconvert"]
+nbformat = ["nbformat"]
+notebook = ["ipywidgets", "notebook"]
+parallel = ["ipyparallel"]
+qtconsole = ["qtconsole"]
+test = ["pytest (<7.1)", "pytest-asyncio", "testpath"]
+test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"]
+
 [[package]]
 name = "isort"
 version = "5.12.0"
@@ -249,6 +521,25 @@ pipfile-deprecated-finder = ["pip-shims (>=0.5.2)", "pipreqs", "requirementslib"
 plugins = ["setuptools"]
 requirements-deprecated-finder = ["pip-api", "pipreqs"]
 
+[[package]]
+name = "jedi"
+version = "0.19.0"
+description = "An autocompletion tool for Python that can be used for text editors."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "jedi-0.19.0-py2.py3-none-any.whl", hash = "sha256:cb8ce23fbccff0025e9386b5cf85e892f94c9b822378f8da49970471335ac64e"},
+    {file = "jedi-0.19.0.tar.gz", hash = "sha256:bcf9894f1753969cbac8022a8c2eaee06bfa3724e4192470aaffe7eb6272b0c4"},
+]
+
+[package.dependencies]
+parso = ">=0.8.3,<0.9.0"
+
+[package.extras]
+docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
+qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
+testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
+
 [[package]]
 name = "jinja2"
 version = "3.1.2"
@@ -266,6 +557,48 @@ MarkupSafe = ">=2.0"
 [package.extras]
 i18n = ["Babel (>=2.7)"]
 
+[[package]]
+name = "jupyter-client"
+version = "8.3.1"
+description = "Jupyter protocol implementation and client libraries"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_client-8.3.1-py3-none-any.whl", hash = "sha256:5eb9f55eb0650e81de6b7e34308d8b92d04fe4ec41cd8193a913979e33d8e1a5"},
+    {file = "jupyter_client-8.3.1.tar.gz", hash = "sha256:60294b2d5b869356c893f57b1a877ea6510d60d45cf4b38057f1672d85699ac9"},
+]
+
+[package.dependencies]
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+python-dateutil = ">=2.8.2"
+pyzmq = ">=23.0"
+tornado = ">=6.2"
+traitlets = ">=5.3"
+
+[package.extras]
+docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
+
+[[package]]
+name = "jupyter-core"
+version = "5.3.1"
+description = "Jupyter core package. A base package on which Jupyter projects rely."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_core-5.3.1-py3-none-any.whl", hash = "sha256:ae9036db959a71ec1cac33081eeb040a79e681f08ab68b0883e9a676c7a90dce"},
+    {file = "jupyter_core-5.3.1.tar.gz", hash = "sha256:5ba5c7938a7f97a6b0481463f7ff0dbac7c15ba48cf46fa4035ca6e838aa1aba"},
+]
+
+[package.dependencies]
+platformdirs = ">=2.5"
+pywin32 = {version = ">=300", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""}
+traitlets = ">=5.3"
+
+[package.extras]
+docs = ["myst-parser", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
+test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
+
 [[package]]
 name = "lazy-object-proxy"
 version = "1.9.0"
@@ -380,6 +713,20 @@ files = [
     {file = "MarkupSafe-2.1.3.tar.gz", hash = "sha256:af598ed32d6ae86f1b747b82783958b1a4ab8f617b06fe68795c7f026abbdcad"},
 ]
 
+[[package]]
+name = "matplotlib-inline"
+version = "0.1.6"
+description = "Inline Matplotlib backend for Jupyter"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "matplotlib-inline-0.1.6.tar.gz", hash = "sha256:f887e5f10ba98e8d2b150ddcf4702c1e5f8b3a20005eb0f74bfdbd360ee6f304"},
+    {file = "matplotlib_inline-0.1.6-py3-none-any.whl", hash = "sha256:f1f41aab5328aa5aaea9b16d083b128102f8712542f819fe7e6a420ff581b311"},
+]
+
+[package.dependencies]
+traitlets = "*"
+
 [[package]]
 name = "mccabe"
 version = "0.7.0"
@@ -503,6 +850,17 @@ files = [
     {file = "mypy_extensions-1.0.0.tar.gz", hash = "sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782"},
 ]
 
+[[package]]
+name = "nest-asyncio"
+version = "1.5.7"
+description = "Patch asyncio to allow nested event loops"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "nest_asyncio-1.5.7-py3-none-any.whl", hash = "sha256:5301c82941b550b3123a1ea772ba9a1c80bad3a182be8c1a5ae6ad3be57a9657"},
+    {file = "nest_asyncio-1.5.7.tar.gz", hash = "sha256:6a80f7b98f24d9083ed24608977c09dd608d83f91cccc24c9d2cba6d10e01c10"},
+]
+
 [[package]]
 name = "networkx"
 version = "3.1"
@@ -724,6 +1082,21 @@ files = [
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
 ]
 
+[[package]]
+name = "parso"
+version = "0.8.3"
+description = "A Python Parser"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "parso-0.8.3-py2.py3-none-any.whl", hash = "sha256:c001d4636cd3aecdaf33cbb40aebb59b094be2a74c556778ef5576c175e19e75"},
+    {file = "parso-0.8.3.tar.gz", hash = "sha256:8c07be290bb59f03588915921e29e8a50002acaf2cdc5fa0e0114f91709fafa0"},
+]
+
+[package.extras]
+qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
+testing = ["docopt", "pytest (<6.0.0)"]
+
 [[package]]
 name = "pathspec"
 version = "0.11.2"
@@ -769,6 +1142,31 @@ files = [
 python-dateutil = ">=2.6,<3.0"
 pytzdata = ">=2020.1"
 
+[[package]]
+name = "pexpect"
+version = "4.8.0"
+description = "Pexpect allows easy control of interactive console applications."
+optional = false
+python-versions = "*"
+files = [
+    {file = "pexpect-4.8.0-py2.py3-none-any.whl", hash = "sha256:0b48a55dcb3c05f3329815901ea4fc1537514d6ba867a152b581d69ae3710937"},
+    {file = "pexpect-4.8.0.tar.gz", hash = "sha256:fc65a43959d153d0114afe13997d439c22823a27cefceb5ff35c2178c6784c0c"},
+]
+
+[package.dependencies]
+ptyprocess = ">=0.5"
+
+[[package]]
+name = "pickleshare"
+version = "0.7.5"
+description = "Tiny 'shelve'-like database with concurrency support"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pickleshare-0.7.5-py2.py3-none-any.whl", hash = "sha256:9649af414d74d4df115d5d718f82acb59c9d418196b7b4290ed47a12ce62df56"},
+    {file = "pickleshare-0.7.5.tar.gz", hash = "sha256:87683d47965c1da65cdacaf31c8441d12b8044cdec9aca500cd78fc2c683afca"},
+]
+
 [[package]]
 name = "platformdirs"
 version = "3.10.0"
@@ -795,6 +1193,96 @@ files = [
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+    {file = "pyzmq-25.1.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:11c1d2aed9079c6b0c9550a7257a836b4a637feb334904610f06d70eb44c56d2"},
+    {file = "pyzmq-25.1.1-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:e8a701123029cc240cea61dd2d16ad57cab4691804143ce80ecd9286b464d180"},
+    {file = "pyzmq-25.1.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:61706a6b6c24bdece85ff177fec393545a3191eeda35b07aaa1458a027ad1304"},
+    {file = "pyzmq-25.1.1.tar.gz", hash = "sha256:259c22485b71abacdfa8bf79720cd7bcf4b9d128b30ea554f01ae71fdbfdaa23"},
+]
+
+[package.dependencies]
+cffi = {version = "*", markers = "implementation_name == \"pypy\""}
+
 [[package]]
 name = "ruff"
 version = "0.0.285"
@@ -901,6 +1517,25 @@ files = [
     {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
 ]
 
+[[package]]
+name = "stack-data"
+version = "0.6.2"
+description = "Extract data from python stack frames and tracebacks for informative displays"
+optional = false
+python-versions = "*"
+files = [
+    {file = "stack_data-0.6.2-py3-none-any.whl", hash = "sha256:cbb2a53eb64e5785878201a97ed7c7b94883f48b87bfb0bbe8b623c74679e4a8"},
+    {file = "stack_data-0.6.2.tar.gz", hash = "sha256:32d2dd0376772d01b6cb9fc996f3c8b57a357089dec328ed4b6553d037eaf815"},
+]
+
+[package.dependencies]
+asttokens = ">=2.1.0"
+executing = ">=1.2.0"
+pure-eval = "*"
+
+[package.extras]
+tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
+
 [[package]]
 name = "sympy"
 version = "1.12"
@@ -1101,6 +1736,26 @@ files = [
 [package.dependencies]
 torch = "2.0.0"
 
+[[package]]
+name = "tornado"
+version = "6.3.3"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
+optional = false
+python-versions = ">= 3.8"
+files = [
+    {file = "tornado-6.3.3-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:502fba735c84450974fec147340016ad928d29f1e91f49be168c0a4c18181e1d"},
+    {file = "tornado-6.3.3-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:805d507b1f588320c26f7f097108eb4023bbaa984d63176d1652e184ba24270a"},
+    {file = "tornado-6.3.3-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1bd19ca6c16882e4d37368e0152f99c099bad93e0950ce55e71daed74045908f"},
+    {file = "tornado-6.3.3-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ac51f42808cca9b3613f51ffe2a965c8525cb1b00b7b2d56828b8045354f76a"},
+    {file = "tornado-6.3.3-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:71a8db65160a3c55d61839b7302a9a400074c9c753040455494e2af74e2501f2"},
+    {file = "tornado-6.3.3-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:ceb917a50cd35882b57600709dd5421a418c29ddc852da8bcdab1f0db33406b0"},
+    {file = "tornado-6.3.3-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:7d01abc57ea0dbb51ddfed477dfe22719d376119844e33c661d873bf9c0e4a16"},
+    {file = "tornado-6.3.3-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:9dc4444c0defcd3929d5c1eb5706cbe1b116e762ff3e0deca8b715d14bf6ec17"},
+    {file = "tornado-6.3.3-cp38-abi3-win32.whl", hash = "sha256:65ceca9500383fbdf33a98c0087cb975b2ef3bfb874cb35b8de8740cf7f41bd3"},
+    {file = "tornado-6.3.3-cp38-abi3-win_amd64.whl", hash = "sha256:22d3c2fa10b5793da13c807e6fc38ff49a4f6e1e3868b0a6f4164768bb8e20f5"},
+    {file = "tornado-6.3.3.tar.gz", hash = "sha256:e7d8db41c0181c80d76c982aacc442c0783a2c54d6400fe028954201a2e032fe"},
+]
+
 [[package]]
 name = "tqdm"
 version = "4.66.1"
@@ -1121,6 +1776,21 @@ notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
 
+[[package]]
+name = "traitlets"
+version = "5.9.0"
+description = "Traitlets Python configuration system"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "traitlets-5.9.0-py3-none-any.whl", hash = "sha256:9e6ec080259b9a5940c797d58b613b5e31441c2257b87c2e795c5228ae80d2d8"},
+    {file = "traitlets-5.9.0.tar.gz", hash = "sha256:f6cde21a9c68cf756af02035f72d5a723bf607e862e7be33ece505abf4a3bad9"},
+]
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
+
 [[package]]
 name = "triton"
 version = "2.0.0"
@@ -1180,6 +1850,17 @@ files = [
     {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"},
 ]
 
+[[package]]
+name = "wcwidth"
+version = "0.2.6"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = "*"
+files = [
+    {file = "wcwidth-0.2.6-py2.py3-none-any.whl", hash = "sha256:795b138f6875577cd91bba52baf9e445cd5118fd32723b460e30a0af30ea230e"},
+    {file = "wcwidth-0.2.6.tar.gz", hash = "sha256:a5220780a404dbe3353789870978e472cfe477761f06ee55077256e509b156d0"},
+]
+
 [[package]]
 name = "wheel"
 version = "0.41.1"
@@ -1281,4 +1962,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "992e0eb975f6fb490726bc9db470a682986c1a287078bec407a4a6dc96e45b3c"
+content-hash = "48badc3ebe08af723b455abd9067ab0e72d990ffaf686509dd3fc04529dfd508"
diff --git a/pyproject.toml b/pyproject.toml
index dc136f2..2e69211 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,6 +25,7 @@ mypy = "^1.5.1"
 pylint = "^2.17.5"
 ruff = "^0.0.285"
 types-tqdm = "^4.66.0.1"
+ipykernel = "^6.25.1"
 
 [tool.ruff]
 select = ["E", "F", "B", "I"]
@@ -33,7 +34,7 @@ line-length = 120
 target-version = "py310"
 
 [tool.black]
-line-length = 120
+line-length = 100
 
 [tool.poetry.scripts]
 train = "swr2_asr.train:run_cli"
diff --git a/swr2_asr/inference_test.py b/swr2_asr/inference_test.py
index a6b0010..16bd54b 100644
--- a/swr2_asr/inference_test.py
+++ b/swr2_asr/inference_test.py
@@ -44,9 +44,7 @@ def main() -> None:
     print(model.__class__)
 
     # only do all things for one single sample
-    dataset = MultilingualLibriSpeech(
-        "data", "mls_german_opus", split="train", download=True
-    )
+    dataset = MultilingualLibriSpeech("data", "mls_german_opus", split="train", download=True)
 
     print(dataset[0])
 
diff --git a/swr2_asr/loss_scores.py b/swr2_asr/loss_scores.py
index c49cc15..ef37b0a 100644
--- a/swr2_asr/loss_scores.py
+++ b/swr2_asr/loss_scores.py
@@ -54,9 +54,7 @@ def _levenshtein_distance(ref, hyp):
     return distance[len_ref % 2][len_hyp]
 
 
-def word_errors(
-    reference: str, hypothesis: str, ignore_case: bool = False, delimiter: str = " "
-):
+def word_errors(reference: str, hypothesis: str, ignore_case: bool = False, delimiter: str = " "):
     """Compute the levenshtein distance between reference sequence and
     hypothesis sequence in word-level.
     :param reference: The reference sentence.
@@ -176,9 +174,7 @@ def cer(reference, hypothesis, ignore_case=False, remove_space=False):
     :rtype: float
     :raises ValueError: If the reference length is zero.
     """
-    edit_distance, ref_len = char_errors(
-        reference, hypothesis, ignore_case, remove_space
-    )
+    edit_distance, ref_len = char_errors(reference, hypothesis, ignore_case, remove_space)
 
     if ref_len == 0:
         raise ValueError("Length of reference should be greater than 0.")
diff --git a/swr2_asr/model_deep_speech.py b/swr2_asr/model_deep_speech.py
index f00ebd4..dd07ff9 100644
--- a/swr2_asr/model_deep_speech.py
+++ b/swr2_asr/model_deep_speech.py
@@ -1,3 +1,4 @@
+"""Main definition of model"""
 import torch.nn.functional as F
 from torch import nn
 
@@ -30,9 +31,7 @@ class ResidualCNN(nn.Module):
     ):
         super().__init__()
 
-        self.cnn1 = nn.Conv2d(
-            in_channels, out_channels, kernel, stride, padding=kernel // 2
-        )
+        self.cnn1 = nn.Conv2d(in_channels, out_channels, kernel, stride, padding=kernel // 2)
         self.cnn2 = nn.Conv2d(
             out_channels,
             out_channels,
@@ -110,9 +109,7 @@ class SpeechRecognitionModel(nn.Module):
         # n residual cnn layers with filter size of 32
         self.rescnn_layers = nn.Sequential(
             *[
-                ResidualCNN(
-                    32, 32, kernel=3, stride=1, dropout=dropout, n_feats=n_feats
-                )
+                ResidualCNN(32, 32, kernel=3, stride=1, dropout=dropout, n_feats=n_feats)
                 for _ in range(n_cnn_layers)
             ]
         )
@@ -140,9 +137,7 @@ class SpeechRecognitionModel(nn.Module):
         data = self.cnn(data)
         data = self.rescnn_layers(data)
         sizes = data.size()
-        data = data.view(
-            sizes[0], sizes[1] * sizes[2], sizes[3]
-        )  # (batch, feature, time)
+        data = data.view(sizes[0], sizes[1] * sizes[2], sizes[3])  # (batch, feature, time)
         data = data.transpose(1, 2)  # (batch, time, feature)
         data = self.fully_connected(data)
         data = self.birnn_layers(data)
diff --git a/swr2_asr/tokenizer.py b/swr2_asr/tokenizer.py
index 8e3bf09..c8d3793 100644
--- a/swr2_asr/tokenizer.py
+++ b/swr2_asr/tokenizer.py
@@ -14,16 +14,24 @@ from tqdm import tqdm
 
 
 class TokenizerType:
+    """Base class for tokenizers.
+
+    exposes the same interface as tokenizers from the huggingface library"""
+
     def encode(self, sequence: str) -> list[int]:
+        """Encode a sequence to a list of integer labels"""
         raise NotImplementedError
 
     def decode(self, labels: list[int], remove_special_tokens: bool) -> str:
+        """Decode a list of integer labels to a sequence"""
         raise NotImplementedError
 
     def decode_batch(self, labels: list[list[int]]) -> list[str]:
+        """Decode a batch of integer labels to a list of sequences"""
         raise NotImplementedError
 
     def get_vocab_size(self) -> int:
+        """Get the size of the vocabulary"""
         raise NotImplementedError
 
     def enable_padding(
@@ -34,17 +42,20 @@ class TokenizerType:
         pad_type_id: int = 0,
         pad_token: str = "[PAD]",
     ) -> None:
+        """Enable padding for the tokenizer"""
         raise NotImplementedError
 
     def save(self, path: str) -> None:
+        """Save the tokenizer to a file"""
         raise NotImplementedError
 
     @staticmethod
     def from_file(path: str) -> "TokenizerType":
+        """Load the tokenizer from a file"""
         raise NotImplementedError
 
 
-tokenizer_type = Type[TokenizerType]
+MyTokenizerType = Type[TokenizerType]
 
 
 @dataclass
@@ -52,6 +63,7 @@ class Encoding:
     """Simple dataclass to represent an encoding"""
 
     ids: list[int]
+    tokens: list[str]
 
 
 class CharTokenizer(TokenizerType):
@@ -137,7 +149,7 @@ class CharTokenizer(TokenizerType):
             else:
                 mapped_char = self.char_map[char]
             int_sequence.append(mapped_char)
-        return Encoding(ids=int_sequence)
+        return Encoding(ids=int_sequence, tokens=list(sequence))
 
     def decode(self, labels: list[int], remove_special_tokens: bool = True):
         """Use a character map and convert integer labels to an text sequence
@@ -256,6 +268,7 @@ def train_bpe_tokenizer(
     bpe_tokenizer = Tokenizer(BPE(unk_token="[UNK]"))
 
     initial_alphabet = [
+        " ",
         "a",
         "b",
         "c",
diff --git a/swr2_asr/train.py b/swr2_asr/train.py
index f3efd69..95038c2 100644
--- a/swr2_asr/train.py
+++ b/swr2_asr/train.py
@@ -5,19 +5,19 @@ from typing import TypedDict
 import click
 import torch
 import torch.nn.functional as F
-from tokenizers import Tokenizer
 from torch import nn, optim
 from torch.utils.data import DataLoader
 from tqdm import tqdm
 
 from swr2_asr.model_deep_speech import SpeechRecognitionModel
-from swr2_asr.tokenizer import train_bpe_tokenizer
+from swr2_asr.tokenizer import CharTokenizer, train_char_tokenizer
 from swr2_asr.utils import MLSDataset, Split, collate_fn
 
 from .loss_scores import cer, wer
 
 # TODO: improve naming of functions
 
+
 class HParams(TypedDict):
     """Type for the hyperparameters of the model."""
 
@@ -33,10 +33,11 @@ class HParams(TypedDict):
     epochs: int
 
 
-# TODO: get blank label from tokenizer
-def greedy_decoder(output, tokenizer, labels, label_lengths, blank_label=28, collapse_repeated=True):
+def greedy_decoder(output, tokenizer, labels, label_lengths, collapse_repeated=True):
     """Greedily decode a sequence."""
+    print("output shape", output.shape)
     arg_maxes = torch.argmax(output, dim=2)  # pylint: disable=no-member
+    blank_label = tokenizer.encode(" ").ids[0]
     decodes = []
     targets = []
     for i, args in enumerate(arg_maxes):
@@ -81,28 +82,27 @@ def train(
     print(f"Epoch: {epoch}")
     losses = []
     for _data in tqdm(train_loader, desc="batches"):
-        spectrograms, labels = _data['spectrogram'].to(device), _data['utterance'].to(device)
+        spectrograms, labels = _data["spectrogram"].to(device), _data["utterance"].to(device)
         optimizer.zero_grad()
 
         output = model(spectrograms)  # (batch, time, n_class)
         output = F.log_softmax(output, dim=2)
         output = output.transpose(0, 1)  # (time, batch, n_class)
 
-        loss = criterion(output, labels, _data['input_length'], _data["utterance_length"])
+        loss = criterion(output, labels, _data["input_length"], _data["utterance_length"])
         loss.backward()
 
         optimizer.step()
         scheduler.step()
         iter_meter.step()
-        
+
         losses.append(loss.item())
 
     print(f"loss in epoch {epoch}: {sum(losses) / len(losses)}")
     return sum(losses) / len(losses)
 
-# TODO: profile this function call
-# TODO: only calculate wer and cer at the end, or less often
-# TODO: change this to only be a sanity check and calculate measures after training
+
+
 def test(model, device, test_loader, criterion, tokenizer):
     """Test"""
     print("\nevaluating...")
@@ -111,21 +111,21 @@ def test(model, device, test_loader, criterion, tokenizer):
     test_cer, test_wer = [], []
     with torch.no_grad():
         for _data in test_loader:
-            spectrograms, labels = _data['spectrogram'].to(device), _data['utterance'].to(device)
+            spectrograms, labels = _data["spectrogram"].to(device), _data["utterance"].to(device)
 
             output = model(spectrograms)  # (batch, time, n_class)
             output = F.log_softmax(output, dim=2)
             output = output.transpose(0, 1)  # (time, batch, n_class)
 
-            # TODO: get rid of this
-            loss = criterion(output, labels, _data['input_length'], _data["utterance_length"])
+            loss = criterion(output, labels, _data["input_length"], _data["utterance_length"])
             test_loss += loss.item() / len(test_loader)
 
             decoded_preds, decoded_targets = greedy_decoder(
-                output = output.transpose(0, 1), 
-                labels = labels, 
-                label_lengths= _data["utterance_length"], 
-                tokenizer=tokenizer)
+                output=output.transpose(0, 1),
+                labels=labels,
+                label_lengths=_data["utterance_length"],
+                tokenizer=tokenizer,
+            )
             for j, pred in enumerate(decoded_preds):
                 test_cer.append(cer(decoded_targets[j], pred))
                 test_wer.append(wer(decoded_targets[j], pred))
@@ -135,9 +135,11 @@ def test(model, device, test_loader, criterion, tokenizer):
 
     print(
         f"Test set: Average loss:\
-            {test_loss}, Average CER: {avg_cer} Average WER: {avg_wer}\n"
+            {test_loss}, Average CER: {None} Average WER: {None}\n"
     )
 
+    return test_loss, avg_cer, avg_wer
+
 
 def run(
     learning_rate: float,
@@ -152,33 +154,34 @@ def run(
     use_cuda = torch.cuda.is_available()
     torch.manual_seed(42)
     device = torch.device("cuda" if use_cuda else "cpu")  # pylint: disable=no-member
-    device = torch.device("mps")
+    # device = torch.device("mps")
 
     # load dataset
-    # TODO: change this from dev split to train split again (was faster for development)
-    train_dataset = MLSDataset(dataset_path, language, Split.dev, download=True, spectrogram_hparams=None)
-    valid_dataset = MLSDataset(dataset_path, language, Split.dev, download=True, spectrogram_hparams=None)
-    test_dataset = MLSDataset(dataset_path, language, Split.test, download=True, spectrogram_hparams=None)
+    train_dataset = MLSDataset(
+        dataset_path, language, Split.TRAIN, download=True, spectrogram_hparams=None
+    )
+    valid_dataset = MLSDataset(
+        dataset_path, language, Split.VALID, download=True, spectrogram_hparams=None
+    )
 
-    # load tokenizer (bpe by default):    
-    if not os.path.isfile("data/tokenizers/bpe_tokenizer_german_3000.json"):
+    # load tokenizer (bpe by default):
+    if not os.path.isfile("data/tokenizers/char_tokenizer_german.json"):
         print("There is no tokenizer available. Do you want to train it on the dataset?")
         input("Press Enter to continue...")
-        train_bpe_tokenizer(
+        train_char_tokenizer(
             dataset_path=dataset_path,
             language=language,
             split="all",
             download=False,
-            out_path="data/tokenizers/bpe_tokenizer_german_3000.json",
+            out_path="data/tokenizers/char_tokenizer_german.json",
             vocab_size=3000,
         )
-    
-    tokenizer = Tokenizer.from_file("data/tokenizers/bpe_tokenizer_german_3000.json")
-    
-    train_dataset.set_tokenizer(tokenizer)
-    valid_dataset.set_tokenizer(tokenizer)
-    test_dataset.set_tokenizer(tokenizer)
-    
+
+    tokenizer = CharTokenizer.from_file("data/tokenizers/char_tokenizer_german.json")
+
+    train_dataset.set_tokenizer(tokenizer)  # type: ignore
+    valid_dataset.set_tokenizer(tokenizer)  # type: ignore
+
     print(f"Waveform shape: {train_dataset[0]['waveform'].shape}")
 
     hparams = HParams(
@@ -221,10 +224,10 @@ def run(
         hparams["stride"],
         hparams["dropout"],
     ).to(device)
-
+    print(tokenizer.encode(" "))
     print("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)
+    criterion = nn.CTCLoss(tokenizer.encode(" ").ids[0]).to(device)
     if load:
         checkpoint = torch.load(path)
         model.load_state_dict(checkpoint["model_state_dict"])
@@ -240,7 +243,7 @@ def run(
     )
 
     iter_meter = IterMeter()
-    for epoch in range(1, epochs +  1):
+    for epoch in range(1, epochs + 1):
         loss = train(
             model,
             device,
@@ -252,7 +255,13 @@ def run(
             iter_meter,
         )
 
-        test(model=model, device=device, test_loader=valid_loader, criterion=criterion, tokenizer = tokenizer)
+        test(
+            model=model,
+            device=device,
+            test_loader=valid_loader,
+            criterion=criterion,
+            tokenizer=tokenizer,
+        )
         print("saving epoch", str(epoch))
         torch.save(
             {"epoch": epoch, "model_state_dict": model.state_dict(), "loss": loss},
@@ -295,5 +304,6 @@ def run_cli(
         language="mls_german_opus",
     )
 
-if __name__  == "__main__":
-    run(1e-3, 10, 1, False, "", "/Volumes/pherkel/SWR2-ASR", "mls_german_opus")
\ No newline at end of file
+
+if __name__ == "__main__":
+    run(1e-3, 10, 1, False, "", "/Volumes/pherkel/SWR2-ASR", "mls_german_opus")
diff --git a/swr2_asr/utils.py b/swr2_asr/utils.py
index 3b9b3ca..efecb56 100644
--- a/swr2_asr/utils.py
+++ b/swr2_asr/utils.py
@@ -8,7 +8,6 @@ import torch
 import torchaudio
 from tokenizers import Tokenizer
 from torch.utils.data import Dataset
-from tqdm import tqdm
 
 from swr2_asr.tokenizer import TokenizerType
 
@@ -24,26 +23,26 @@ class MLSSplit(str, Enum):
     """Enum specifying dataset as they are defined in the
     Multilingual LibriSpeech dataset"""
 
-    train = "train"
-    test = "test"
-    dev = "dev"
+    TRAIN = "train"
+    TEST = "test"
+    DEV = "dev"
 
 
 class Split(str, Enum):
     """Extending the MLSSplit class to allow for a custom validatio split"""
 
-    train = "train"
-    valid = "valid"
-    test = "test"
-    dev = "dev"
+    TRAIN = "train"
+    VALID = "valid"
+    TEST = "test"
+    DEV = "dev"
 
 
-def split_to_mls_split(split: Split) -> MLSSplit:
+def split_to_mls_split(split_name: Split) -> MLSSplit:
     """Converts the custom split to a MLSSplit"""
-    if split == Split.valid:
-        return MLSSplit.train
+    if split_name == Split.VALID:
+        return MLSSplit.TRAIN
     else:
-        return split  # type: ignore
+        return split_name  # type: ignore
 
 
 class Sample(TypedDict):
@@ -89,14 +88,21 @@ class MLSDataset(Dataset):
         <speakerid>_<bookid>_<chapterid> <utterance>
     """
 
-    def __init__(self, dataset_path: str, language: str, split: Split, download: bool, spectrogram_hparams: dict | None):
+    def __init__(
+        self,
+        dataset_path: str,
+        language: str,
+        split: Split,
+        download: bool,
+        spectrogram_hparams: dict | None,
+    ):
         """Initializes the dataset"""
         self.dataset_path = dataset_path
         self.language = language
         self.file_ext = ".opus" if "opus" in language else ".flac"
         self.mls_split: MLSSplit = split_to_mls_split(split)  # split path on disk
         self.split: Split = split  # split used internally
-        
+
         if spectrogram_hparams is None:
             self.spectrogram_hparams = {
                 "sample_rate": 16000,
@@ -110,7 +116,7 @@ class MLSDataset(Dataset):
             }
         else:
             self.spectrogram_hparams = spectrogram_hparams
-        
+
         self.dataset_lookup = []
         self.tokenizer: type[TokenizerType]
 
@@ -118,13 +124,14 @@ class MLSDataset(Dataset):
         self._validate_local_directory()
         self.initialize()
 
-            
     def initialize(self) -> None:
         """Initializes the dataset
-        
+
         Reads the transcripts.txt file and creates a lookup table
         """
-        transcripts_path = os.path.join(self.dataset_path, self.language, self.mls_split, "transcripts.txt")
+        transcripts_path = os.path.join(
+            self.dataset_path, self.language, self.mls_split, "transcripts.txt"
+        )
 
         with open(transcripts_path, "r", encoding="utf-8") as script_file:
             # read all lines in transcripts.txt
@@ -135,12 +142,12 @@ class MLSDataset(Dataset):
             identifier = [identifier.strip() for identifier, _ in transcripts]  # type: ignore
             identifier = [path.split("_") for path in identifier]
 
-            if self.split == Split.valid:
+            if self.split == Split.VALID:
                 np.random.seed(42)
                 indices = np.random.choice(len(utterances), int(len(utterances) * 0.2))
                 utterances = [utterances[i] for i in indices]
                 identifier = [identifier[i] for i in indices]
-            elif self.split == Split.train:
+            elif self.split == Split.TRAIN:
                 np.random.seed(42)
                 indices = np.random.choice(len(utterances), int(len(utterances) * 0.8))
                 utterances = [utterances[i] for i in indices]
@@ -212,13 +219,19 @@ class MLSDataset(Dataset):
 
         # resample if necessary
         if sample_rate != self.spectrogram_hparams["sample_rate"]:
-            resampler = torchaudio.transforms.Resample(sample_rate, self.spectrogram_hparams["sample_rate"])
+            resampler = torchaudio.transforms.Resample(
+                sample_rate, self.spectrogram_hparams["sample_rate"]
+            )
             waveform = resampler(waveform)
 
-        spec = torchaudio.transforms.MelSpectrogram(**self.spectrogram_hparams)(waveform).squeeze(0).transpose(0, 1)
+        spec = (
+            torchaudio.transforms.MelSpectrogram(**self.spectrogram_hparams)(waveform)
+            .squeeze(0)
+            .transpose(0, 1)
+        )
 
         input_length = spec.shape[0] // 2
-        
+
         utterance_length = len(utterance)
 
         utterance = self.tokenizer.encode(utterance)
@@ -236,11 +249,11 @@ class MLSDataset(Dataset):
             book_id=self.dataset_lookup[idx]["bookid"],
             chapter_id=self.dataset_lookup[idx]["chapterid"],
         )
-        
+
 
 def collate_fn(samples: list[Sample]) -> dict:
     """Collate function for the dataloader
-    
+
     pads all tensors within a batch to the same dimensions
     """
     waveforms = []
@@ -248,18 +261,20 @@ def collate_fn(samples: list[Sample]) -> dict:
     labels = []
     input_lengths = []
     label_lengths = []
-    
+
     for sample in samples:
         waveforms.append(sample["waveform"].transpose(0, 1))
         spectrograms.append(sample["spectrogram"])
         labels.append(sample["utterance"])
         input_lengths.append(sample["spectrogram"].shape[0] // 2)
         label_lengths.append(len(sample["utterance"]))
-    
+
     waveforms = torch.nn.utils.rnn.pad_sequence(waveforms, batch_first=True)
-    spectrograms = torch.nn.utils.rnn.pad_sequence(spectrograms, batch_first=True).unsqueeze(1).transpose(2,3)
+    spectrograms = (
+        torch.nn.utils.rnn.pad_sequence(spectrograms, batch_first=True).unsqueeze(1).transpose(2, 3)
+    )
     labels = torch.nn.utils.rnn.pad_sequence(labels, batch_first=True)
-    
+
     return {
         "waveform": waveforms,
         "spectrogram": spectrograms,
@@ -267,15 +282,15 @@ def collate_fn(samples: list[Sample]) -> dict:
         "utterance": labels,
         "utterance_length": label_lengths,
     }
-    
+
 
 if __name__ == "__main__":
-    dataset_path = "/Volumes/pherkel/SWR2-ASR"
-    language = "mls_german_opus"
-    split = Split.train
-    download = False
+    DATASET_PATH = "/Volumes/pherkel/SWR2-ASR"
+    LANGUAGE = "mls_german_opus"
+    split = Split.TRAIN
+    DOWNLOAD = False
 
-    dataset = MLSDataset(dataset_path, language, split, download, None)
+    dataset = MLSDataset(DATASET_PATH, LANGUAGE, split, DOWNLOAD, None)
 
     tok = Tokenizer.from_file("data/tokenizers/bpe_tokenizer_german_3000.json")
     dataset.set_tokenizer(tok)
-- 
cgit v1.2.3


From 6a73a1ed117d9ace8546aa5114daada91e69b069 Mon Sep 17 00:00:00 2001
From: Pherkel
Date: Sun, 3 Sep 2023 19:44:27 +0200
Subject: reformat, remove deps

---
 poetry.lock                | 904 +--------------------------------------------
 pyproject.toml             |   3 -
 swr2_asr/inference_test.py |   7 +-
 swr2_asr/tokenizer.py      |   1 -
 swr2_asr/train.py          |   1 -
 5 files changed, 18 insertions(+), 898 deletions(-)

(limited to 'pyproject.toml')

diff --git a/poetry.lock b/poetry.lock
index 38cba87..c322398 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,16 +1,5 @@
 # This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
-[[package]]
-name = "appnope"
-version = "0.1.3"
-description = "Disable App Nap on macOS >= 10.9"
-optional = false
-python-versions = "*"
-files = [
-    {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"},
-    {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
-]
-
 [[package]]
 name = "astroid"
 version = "2.15.6"
@@ -30,119 +19,6 @@ wrapt = [
     {version = ">=1.14,<2", markers = "python_version >= \"3.11\""},
 ]
 
-[[package]]
-name = "asttokens"
-version = "2.3.0"
-description = "Annotate AST trees with source code positions"
-optional = false
-python-versions = "*"
-files = [
-    {file = "asttokens-2.3.0-py2.py3-none-any.whl", hash = "sha256:bef1a51bc256d349e9f94e7e40e44b705ed1162f55294220dd561d24583d9877"},
-    {file = "asttokens-2.3.0.tar.gz", hash = "sha256:2552a88626aaa7f0f299f871479fc755bd4e7c11e89078965e928fb7bb9a6afe"},
-]
-
-[package.dependencies]
-six = ">=1.12.0"
-
-[package.extras]
-test = ["astroid", "pytest"]
-
-[[package]]
-name = "attrs"
-version = "19.3.0"
-description = "Classes Without Boilerplate"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
-    {file = "attrs-19.3.0-py2.py3-none-any.whl", hash = "sha256:08a96c641c3a74e44eb59afb61a24f2cb9f4d7188748e76ba4bb5edfa3cb7d1c"},
-    {file = "attrs-19.3.0.tar.gz", hash = "sha256:f7b7ce16570fe9965acd6d30101a28f62fb4a7f9e926b3bbc9b61f8b04247e72"},
-]
-
-[package.extras]
-azure-pipelines = ["coverage", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-azurepipelines", "six", "zope.interface"]
-dev = ["coverage", "hypothesis", "pre-commit", "pympler", "pytest (>=4.3.0)", "six", "sphinx", "zope.interface"]
-docs = ["sphinx", "zope.interface"]
-tests = ["coverage", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "zope.interface"]
-
-[[package]]
-name = "audio-metadata"
-version = "0.11.1"
-description = "A library for reading and, in the future, writing metadata from audio files."
-optional = false
-python-versions = ">=3.6,<4.0"
-files = [
-    {file = "audio-metadata-0.11.1.tar.gz", hash = "sha256:9e7ba79d49cf048a911d5f7d55bb2715c10be5c127fe5db0987c5fe1aa7335eb"},
-    {file = "audio_metadata-0.11.1-py3-none-any.whl", hash = "sha256:f5b85ad087324c255f8d1223574c3e7d3c27b649e411d1dd54aa3bf342fe93fb"},
-]
-
-[package.dependencies]
-attrs = ">=18.2,<19.4"
-bidict = "<1.0.0"
-bitstruct = ">=6.0,<9.0"
-more-itertools = ">=4.0,<9.0"
-pendulum = ">=2.0,<2.0.5 || >2.0.5,<2.1.0 || >2.1.0,<=3.0"
-pprintpp = "<1.0.0"
-tbm-utils = ">=2.3,<3.0"
-wrapt = ">=1.0,<2.0"
-
-[package.extras]
-dev = ["coverage[toml] (>=5.0,<6.0)", "flake8 (>=3.5,<4.0)", "flake8-builtins (>=1.0,<2.0)", "flake8-comprehensions (>=2.0,<=4.0)", "flake8-import-order (>=0.18,<0.19)", "flake8-import-order-tbm (>=1.0,<2.0)", "nox (>=2019,<2020)", "sphinx (>=2.0,<3.0)", "sphinx-material (<1.0.0)", "ward (>=0.42.0-beta.0)"]
-doc = ["sphinx (>=2.0,<3.0)", "sphinx-material (<1.0.0)"]
-lint = ["flake8 (>=3.5,<4.0)", "flake8-builtins (>=1.0,<2.0)", "flake8-comprehensions (>=2.0,<=4.0)", "flake8-import-order (>=0.18,<0.19)", "flake8-import-order-tbm (>=1.0,<2.0)"]
-test = ["coverage[toml] (>=5.0,<6.0)", "nox (>=2019,<2020)", "ward (>=0.42.0-beta.0)"]
-
-[[package]]
-name = "AudioLoader"
-version = "0.1.4"
-description = "A collection of PyTorch audio datasets for speech and music applications"
-optional = false
-python-versions = ">=3.6"
-files = []
-develop = false
-
-[package.source]
-type = "git"
-url = "https://github.com/marvinborner/AudioLoader.git"
-reference = "HEAD"
-resolved_reference = "8fb829bf7fb98f26f8456dc22ef0fe2c7bb38ac2"
-
-[[package]]
-name = "backcall"
-version = "0.2.0"
-description = "Specifications for callback functions passed in to an API"
-optional = false
-python-versions = "*"
-files = [
-    {file = "backcall-0.2.0-py2.py3-none-any.whl", hash = "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"},
-    {file = "backcall-0.2.0.tar.gz", hash = "sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e"},
-]
-
-[[package]]
-name = "bidict"
-version = "0.22.1"
-description = "The bidirectional mapping library for Python."
-optional = false
-python-versions = ">=3.7"
-files = [
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-
-[[package]]
-name = "decorator"
-version = "5.1.1"
-description = "Decorators for Humans"
-optional = false
-python-versions = ">=3.5"
-files = [
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-]
-
 [[package]]
 name = "dill"
 version = "0.3.7"
@@ -389,120 +132,23 @@ files = [
 [package.extras]
 graph = ["objgraph (>=1.7.2)"]
 
-[[package]]
-name = "exceptiongroup"
-version = "1.1.3"
-description = "Backport of PEP 654 (exception groups)"
-optional = false
-python-versions = ">=3.7"
-files = [
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-]
-
-[package.extras]
-test = ["pytest (>=6)"]
-
-[[package]]
-name = "executing"
-version = "1.2.0"
-description = "Get the currently executing AST node of a frame, and other information"
-optional = false
-python-versions = "*"
-files = [
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-]
-
-[package.extras]
-tests = ["asttokens", "littleutils", "pytest", "rich"]
-
 [[package]]
 name = "filelock"
-version = "3.12.2"
+version = "3.12.3"
 description = "A platform independent file lock."
 optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "filelock-3.12.2-py3-none-any.whl", hash = "sha256:cbb791cdea2a72f23da6ac5b5269ab0a0d161e9ef0100e653b69049a7706d1ec"},
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-[package.extras]
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-
-[[package]]
-name = "ipykernel"
-version = "6.25.1"
-description = "IPython Kernel for Jupyter"
-optional = false
 python-versions = ">=3.8"
 files = [
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-comm = ">=0.1.1"
-debugpy = ">=1.6.5"
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-packaging = "*"
-psutil = "*"
-pyzmq = ">=20"
-tornado = ">=6.1"
-traitlets = ">=5.4.0"
+typing-extensions = {version = ">=4.7.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
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-pyside6 = ["pyside6"]
-test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"]
-
-[[package]]
-name = "ipython"
-version = "8.15.0"
-description = "IPython: Productive Interactive Computing"
-optional = false
-python-versions = ">=3.9"
-files = [
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-
-[package.dependencies]
-appnope = {version = "*", markers = "sys_platform == \"darwin\""}
-backcall = "*"
-colorama = {version = "*", markers = "sys_platform == \"win32\""}
-decorator = "*"
-exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
-jedi = ">=0.16"
-matplotlib-inline = "*"
-pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
-pickleshare = "*"
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-pygments = ">=2.4.0"
-stack-data = "*"
-traitlets = ">=5"
-
-[package.extras]
-all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.21)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
-black = ["black"]
-doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
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-nbconvert = ["nbconvert"]
-nbformat = ["nbformat"]
-notebook = ["ipywidgets", "notebook"]
-parallel = ["ipyparallel"]
-qtconsole = ["qtconsole"]
-test = ["pytest (<7.1)", "pytest-asyncio", "testpath"]
-test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"]
+docs = ["furo (>=2023.7.26)", "sphinx (>=7.1.2)", "sphinx-autodoc-typehints (>=1.24)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3)", "diff-cover (>=7.7)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)", "pytest-timeout (>=2.1)"]
 
 [[package]]
 name = "isort"
@@ -521,25 +167,6 @@ pipfile-deprecated-finder = ["pip-shims (>=0.5.2)", "pipreqs", "requirementslib"
 plugins = ["setuptools"]
 requirements-deprecated-finder = ["pip-api", "pipreqs"]
 
-[[package]]
-name = "jedi"
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-description = "An autocompletion tool for Python that can be used for text editors."
-optional = false
-python-versions = ">=3.6"
-files = [
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-
-[package.dependencies]
-parso = ">=0.8.3,<0.9.0"
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-[package.extras]
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-
 [[package]]
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 version = "3.1.2"
@@ -557,48 +184,6 @@ MarkupSafe = ">=2.0"
 [package.extras]
 i18n = ["Babel (>=2.7)"]
 
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-
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-
 [[package]]
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@@ -713,20 +298,6 @@ files = [
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 [[package]]
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@@ -765,17 +336,6 @@ ports-rtmidi-python = ["rtmidi-python (>=0.2.2,<0.3.0)"]
 release = ["twine (>=4.0.2,<4.1.0)"]
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@@ -1082,21 +631,6 @@ files = [
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-testing = ["docopt", "pytest (<6.0.0)"]
-
 [[package]]
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@@ -1108,65 +642,6 @@ files = [
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-python-versions = ">=3.7"
-files = [
-    {file = "traitlets-5.9.0-py3-none-any.whl", hash = "sha256:9e6ec080259b9a5940c797d58b613b5e31441c2257b87c2e795c5228ae80d2d8"},
-    {file = "traitlets-5.9.0.tar.gz", hash = "sha256:f6cde21a9c68cf756af02035f72d5a723bf607e862e7be33ece505abf4a3bad9"},
-]
-
-[package.extras]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
-test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
-
 [[package]]
 name = "triton"
 version = "2.0.0"
@@ -1830,13 +963,13 @@ tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "types-tqdm"
-version = "4.66.0.1"
+version = "4.66.0.2"
 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"},
+    {file = "types-tqdm-4.66.0.2.tar.gz", hash = "sha256:9553a5e44c1d485fce19f505b8bd65c0c3e87e870678d1f2ed764ae59a55d45f"},
+    {file = "types_tqdm-4.66.0.2-py3-none-any.whl", hash = "sha256:13dddd38908834abdf0acdc2b70cab7ac4bcc5ad7356ced450471662e58a0ffc"},
 ]
 
 [[package]]
@@ -1850,26 +983,15 @@ files = [
     {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"},
 ]
 
-[[package]]
-name = "wcwidth"
-version = "0.2.6"
-description = "Measures the displayed width of unicode strings in a terminal"
-optional = false
-python-versions = "*"
-files = [
-    {file = "wcwidth-0.2.6-py2.py3-none-any.whl", hash = "sha256:795b138f6875577cd91bba52baf9e445cd5118fd32723b460e30a0af30ea230e"},
-    {file = "wcwidth-0.2.6.tar.gz", hash = "sha256:a5220780a404dbe3353789870978e472cfe477761f06ee55077256e509b156d0"},
-]
-
 [[package]]
 name = "wheel"
-version = "0.41.1"
+version = "0.41.2"
 description = "A built-package format for Python"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "wheel-0.41.1-py3-none-any.whl", hash = "sha256:473219bd4cbedc62cea0cb309089b593e47c15c4a2531015f94e4e3b9a0f6981"},
-    {file = "wheel-0.41.1.tar.gz", hash = "sha256:12b911f083e876e10c595779709f8a88a59f45aacc646492a67fe9ef796c1b47"},
+    {file = "wheel-0.41.2-py3-none-any.whl", hash = "sha256:75909db2664838d015e3d9139004ee16711748a52c8f336b52882266540215d8"},
+    {file = "wheel-0.41.2.tar.gz", hash = "sha256:0c5ac5ff2afb79ac23ab82bab027a0be7b5dbcf2e54dc50efe4bf507de1f7985"},
 ]
 
 [package.extras]
@@ -1962,4 +1084,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "48badc3ebe08af723b455abd9067ab0e72d990ffaf686509dd3fc04529dfd508"
+content-hash = "a65a10595cd1536a6d09b3fcf6e95c29b03f7fab4574522f241dfdc8c6455b70"
diff --git a/pyproject.toml b/pyproject.toml
index 2e69211..57c60c9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -11,13 +11,11 @@ packages = [{include = "swr2_asr"}]
 python = "^3.10"
 torch = "2.0.0"
 torchaudio = "2.0.1"
-audioloader = {git = "https://github.com/marvinborner/AudioLoader.git"}
 tqdm = "^4.66.1"
 numpy = "^1.25.2"
 mido = "^1.3.0"
 tokenizers = "^0.13.3"
 click = "^8.1.7"
-audio-metadata = "^0.11.1"
 
 [tool.poetry.group.dev.dependencies]
 black = "^23.7.0"
@@ -25,7 +23,6 @@ mypy = "^1.5.1"
 pylint = "^2.17.5"
 ruff = "^0.0.285"
 types-tqdm = "^4.66.0.1"
-ipykernel = "^6.25.1"
 
 [tool.ruff]
 select = ["E", "F", "B", "I"]
diff --git a/swr2_asr/inference_test.py b/swr2_asr/inference_test.py
index 16bd54b..96277fd 100644
--- a/swr2_asr/inference_test.py
+++ b/swr2_asr/inference_test.py
@@ -1,11 +1,12 @@
 """Training script for the ASR model."""
-from AudioLoader.speech.mls import MultilingualLibriSpeech
 import torch
 import torchaudio
 import torchaudio.functional as F
 
 
 class GreedyCTCDecoder(torch.nn.Module):
+    """Greedy CTC decoder for the wav2vec2 model."""
+
     def __init__(self, labels, blank=0) -> None:
         super().__init__()
         self.labels = labels
@@ -25,6 +26,8 @@ class GreedyCTCDecoder(torch.nn.Module):
         return "".join([self.labels[i] for i in indices])
 
 
+'''
+Sorry marvin, Please fix this to use the new dataset
 def main() -> None:
     """Main function."""
     # choose between cuda, cpu and mps devices
@@ -66,7 +69,7 @@ def main() -> None:
     transcript = decoder(emission[0])
 
     print(transcript)
-
+'''
 
 if __name__ == "__main__":
     main()
diff --git a/swr2_asr/tokenizer.py b/swr2_asr/tokenizer.py
index c8d3793..f02d4f5 100644
--- a/swr2_asr/tokenizer.py
+++ b/swr2_asr/tokenizer.py
@@ -5,7 +5,6 @@ from dataclasses import dataclass
 from typing import Type
 
 import click
-from AudioLoader.speech import MultilingualLibriSpeech
 from tokenizers import Tokenizer, normalizers
 from tokenizers.models import BPE
 from tokenizers.pre_tokenizers import Whitespace
diff --git a/swr2_asr/train.py b/swr2_asr/train.py
index 95038c2..8fc0b78 100644
--- a/swr2_asr/train.py
+++ b/swr2_asr/train.py
@@ -102,7 +102,6 @@ def train(
     return sum(losses) / len(losses)
 
 
-
 def test(model, device, test_loader, criterion, tokenizer):
     """Test"""
     print("\nevaluating...")
-- 
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