From 71e68380f1a522e7e454d79bc2bfbfcb0e3ca2e9 Mon Sep 17 00:00:00 2001
From: Franklin <41602287+fcogidi@users.noreply.github.com>
Date: Mon, 19 Aug 2024 19:03:22 -0400
Subject: [PATCH] Fix pip extras (#4)

---
 .pre-commit-config.yaml             |  11 +-
 README.md                           | 101 +++-
 mmlearn/datasets/__init__.py        |   2 -
 mmlearn/datasets/ego4d.py           | 126 -----
 poetry.lock                         | 740 ++++++++++------------------
 projects/med_benchmarking/README.md |   2 +-
 pyproject.toml                      |  25 +-
 7 files changed, 374 insertions(+), 633 deletions(-)
 delete mode 100644 mmlearn/datasets/ego4d.py

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 36167e3..bf0457e 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -22,7 +22,7 @@ repos:
         args: [--lock]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.5.7
+    rev: v0.6.1
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]
@@ -40,9 +40,10 @@ repos:
     rev: v1.11.1
     hooks:
       - id: mypy
-        entry: python3 -m mypy --show-error-codes --pretty --config-file pyproject.toml
-        types: [python]
-        exclude: "tests"
+        entry: mypy
+        args: ["--config-file=pyproject.toml", "--show-error-codes", "--pretty"]
+        types_or: [python, pyi]
+        exclude: tests|projects
 
   - repo: https://github.com/nbQA-dev/nbQA
     rev: 1.8.7
@@ -58,5 +59,3 @@ repos:
       entry: python3 -m pytest -m "not integration_test"
       pass_filenames: false
       always_run: true
-
-exclude: "projects"
diff --git a/README.md b/README.md
index 4822062..713ccc3 100644
--- a/README.md
+++ b/README.md
@@ -16,6 +16,63 @@ python3 -m venv /path/to/new/virtual/environment
 source /path/to/new/virtual/environment/bin/activate
 ```
 
+<details>
+<summary><b>Installation Options</b></summary>
+You can install optional dependencies to enable additional features. Use one or more of the pip extras listed below to
+install the desired dependencies.
+
+<table>
+<tr>
+<th style="text-align: left; width: 150px"> pip extra </th>
+<th style="text-align: center"> Dependencies </th>
+<th style="text-align: center"> Notes </th>
+</tr>
+
+<tr>
+<td>
+vision
+</td>
+<td>
+"torchvision", "opencv-python", "timm"
+</td>
+<td>
+Enables image processing and vision tasks.
+</td>
+</tr>
+
+<tr>
+<td>
+audio
+</td>
+<td>
+"torchaudio"
+</td>
+<td>
+Enables audio processing and tasks.
+</td>
+</tr>
+
+<tr>
+<td>
+peft
+</td>
+<td>
+"peft"
+</td>
+<td>
+Uses the <a href=https://huggingface.co/docs/peft/index>PEFT</a> library to enable parameter-efficient fine-tuning.
+</td>
+</tr>
+
+</table>
+
+For example, to install the library with the `vision` and `audio` extras, run:
+```bash
+python3 -m pip install mmlearn[vision,audio]
+```
+
+</details>
+
 #### Installing binaries
 To install the pre-built binaries, run:
 ```bash
@@ -32,25 +89,31 @@ python3 -m pip install -e .
 ```
 
 ### Running Experiments
-To run an experiment, create a folder with a similar structure as the [`configs`](configs/) folder.
-Then, use the `mmlearn_run` command to run the experiment as defined in a `.yaml` file under the `experiment` folder, like so:
+We use [Hydra](https://hydra.cc/docs/intro/) and [hydra-zen](https://mit-ll-responsible-ai.github.io/hydra-zen/) to manage configurations
+in the library.
+
+For new experiments, it is recommended to create a new directory to store the configuration files. The directory should
+have an `__init__.py` file to make it a Python package and an `experiment` folder to store the experiment configuration files.
+This format allows the use of `.yaml` configuration files as well as Python modules (using [structured configs](https://hydra.cc/docs/tutorials/structured_config/intro/) or [hydra-zen](https://mit-ll-responsible-ai.github.io/hydra-zen/)) to define the experiment configurations.
+
+To run an experiment, use the following command:
 ```bash
-mmlearn_run --config-dir /path/to/config/dir +experiment=<name_of_experiment_config> experiment=your_experiment_name
+mmlearn_run 'hydra.searchpath=[pkg://path.to.config.directory]' +experiment=<name_of_experiment_yaml_file> experiment=your_experiment_name
 ```
-Notice that the config directory refers to the top-level directory containing the `experiment` folder. The experiment
-name is the name of the `.yaml` file under the `experiment` folder, without the extension.
+Hydra will compose the experiment configuration from all the configurations in the specified directory as well as all the
+configurations in the `mmlearn` package. *Note the dot-separated path to the directory containing the experiment configuration
+files.*
 
-We use [Hydra](https://hydra.cc/docs/intro/) to manage configurations, so you can override any configuration parameter
-from the command line. To see the available options and other information, run:
+Hydra also allows for overriding configurations parameters from the command line. To see the available options and other information, run:
 ```bash
-mmlearn_run --config-dir /path/to/config/dir +experiment=<name_of_experiment> --help
+mmlearn_run 'hydra.searchpath=[pkg://path.to.config.directory]' +experiment=<name_of_experiment_yaml_file> --help
 ```
 
 By default, the `mmlearn_run` command will run the experiment locally. To run the experiment on a SLURM cluster, we use
 the [submitit launcher](https://hydra.cc/docs/plugins/submitit_launcher/) plugin built into Hydra. The following is an example
 of how to run an experiment on a SLURM cluster:
 ```bash
-mmlearn_run --multirun hydra.launcher.mem_gb=32 hydra.launcher.qos=your_qos hydra.launcher.partition=your_partition hydra.launcher.gres=gpu:4 hydra.launcher.cpus_per_task=8 hydra.launcher.tasks_per_node=4 hydra.launcher.nodes=1 hydra.launcher.stderr_to_stdout=true hydra.launcher.timeout_min=60 '+hydra.launcher.additional_parameters={export: ALL}' --config-dir /path/to/config/dir +experiment=<name_of_experiment_config> experiment=your_experiment_name
+mmlearn_run --multirun hydra.launcher.mem_gb=32 hydra.launcher.qos=your_qos hydra.launcher.partition=your_partition hydra.launcher.gres=gpu:4 hydra.launcher.cpus_per_task=8 hydra.launcher.tasks_per_node=4 hydra.launcher.nodes=1 hydra.launcher.stderr_to_stdout=true hydra.launcher.timeout_min=60 '+hydra.launcher.additional_parameters={export: ALL}' 'hydra.searchpath=[pkg://path.to.config.directory]' +experiment=<name_of_experiment_yaml_file> experiment=your_experiment_name
 ```
 This will submit a job to the SLURM cluster with the specified resources.
 
@@ -93,20 +156,18 @@ using recall@k metric. This is applicable to any number of pairs of modalities a
 
 ## Components
 ### Datasets
-Every dataset object must return an instance of [`Example`](mmlearn/datasets/core/example.py) with one or more keys/attributes
-corresponding to a modality name as specified in the [`Modalities registry`](mmlearn/datasets/core/modalities.py).
-The `Example` object must also include an `example_index` attribute/key, which is used, in addition to the dataset index,
-to uniquely identify the example.
+Every dataset object must return an instance of `Example` with one or more keys/attributes corresponding to a modality name
+as specified in the `Modalities` registry. The `Example` object must also include an `example_index` attribute/key, which
+is used, in addition to the dataset index, to uniquely identify the example.
 
 <details>
 <summary><b>CombinedDataset</b></summary>
 
-The [`CombinedDataset`](mmlearn/datasets/core/combined_dataset.py) object is used to combine multiple datasets into one. It
-accepts an iterable of `torch.utils.data.Dataset` and/or `torch.utils.data.IterableDataset` objects and returns an `Example`
-object from one of the datasets, given an index. Conceptually, the `CombinedDataset` object is a concatenation of the
-datasets in the input iterable, so the given index can be mapped to a specific dataset based on the size of the datasets.
-As iterable-style datasets do not support random access, the examples from these datasets are returned in order as they
-are iterated over.
+The `CombinedDataset` object is used to combine multiple datasets into one. It accepts an iterable of `torch.utils.data.Dataset`
+and/or `torch.utils.data.IterableDataset` objects and returns an `Example` object from one of the datasets, given an index.
+Conceptually, the `CombinedDataset` object is a concatenation of the datasets in the input iterable, so the given index
+can be mapped to a specific dataset based on the size of the datasets. As iterable-style datasets do not support random access,
+the examples from these datasets are returned in order as they are iterated over.
 
 The `CombinedDataset` object also adds a `dataset_index` attribute to the `Example` object, corresponding to the index of
 the dataset in the input iterable. Every example returned by the `CombinedDataset` will have an `example_ids` attribute,
@@ -116,7 +177,7 @@ which is instance of `Example` containing the same keys/attributes as the origin
 
 ### Dataloading
 When dealing with multiple datasets with different modalities, the default `collate_fn` of `torch.utils.data.DataLoader`
-may not work, as it assumes that all examples have the same keys/attributes. In that case, the [`collate_example_list`](mmlearn/datasets/core/example.py)
+may not work, as it assumes that all examples have the same keys/attributes. In that case, the `collate_example_list`
 function can be used as the `collate_fn` argument of `torch.utils.data.DataLoader`. This function takes a list of `Example`
 objects and returns a dictionary of tensors, with all the keys/attributes of the `Example` objects.
 
diff --git a/mmlearn/datasets/__init__.py b/mmlearn/datasets/__init__.py
index be2484a..ca39e14 100644
--- a/mmlearn/datasets/__init__.py
+++ b/mmlearn/datasets/__init__.py
@@ -1,7 +1,6 @@
 """Datasets."""
 
 from mmlearn.datasets.chexpert import CheXpert
-from mmlearn.datasets.ego4d import Ego4DDataset
 from mmlearn.datasets.imagenet import ImageNet
 from mmlearn.datasets.librispeech import LibriSpeech
 from mmlearn.datasets.llvip import LLVIPDataset
@@ -12,7 +11,6 @@
 
 __all__ = [
     "CheXpert",
-    "Ego4DDataset",
     "ImageNet",
     "LibriSpeech",
     "LLVIPDataset",
diff --git a/mmlearn/datasets/ego4d.py b/mmlearn/datasets/ego4d.py
deleted file mode 100644
index 896f741..0000000
--- a/mmlearn/datasets/ego4d.py
+++ /dev/null
@@ -1,126 +0,0 @@
-"""Ego4D dataset."""
-
-import glob
-import os
-from typing import Any, Callable, List, Optional, Tuple
-
-import torch
-from hydra_zen import MISSING, store
-from pytorchvideo import transforms as pv_transforms
-from pytorchvideo.data.clip_sampling import ConstantClipsPerVideoSampler
-from pytorchvideo.data.encoded_video import EncodedVideo
-from torch.utils.data import Dataset
-from torchvision import transforms
-
-from mmlearn.constants import EXAMPLE_INDEX_KEY
-from mmlearn.datasets.core import Modalities
-from mmlearn.datasets.core.example import Example
-
-
-@store(
-    name="Ego4D",
-    group="datasets",
-    provider="mmlearn",
-    root_dir=os.getenv("EGO4D_ROOT_DIR", MISSING),
-)
-class Ego4DDataset(Dataset[Example]):
-    """A PyTorch Dataset for loading and processing videos from the Ego4D dataset.
-
-    Parameters
-    ----------
-    root_dir : List[str]
-        Path to the root directory containing the video files.
-    clip_duration : int
-        Duration of each video clip in seconds.
-    clips_per_video : int
-        Number of clips to sample from each video.
-    sample_rate : int
-        Sample rate for audio processing.
-    video_transform : Optional[Callable], default=None
-        A callable that takes in a video clip and returns a transformed version of it.
-    """
-
-    def __init__(
-        self,
-        root_dir: str,
-        clip_duration: int = 2,
-        clips_per_video: int = 5,
-        sample_rate: int = 16000,
-        video_transform: Optional[Callable[..., Any]] = None,
-    ) -> None:
-        """Initialize the dataset."""
-        self.video_paths = glob.glob(os.path.join(root_dir, "*.mp4"))
-        self.clip_duration = clip_duration
-        self.clips_per_video = clips_per_video
-        self.sample_rate = sample_rate
-
-        if video_transform is not None:
-            self.video_transform = video_transform
-        else:
-            self.video_transform = transforms.Compose(
-                [
-                    pv_transforms.ShortSideScale(224),
-                    pv_transforms.Normalize(
-                        mean=(0.48145466, 0.4578275, 0.40821073),
-                        std=(0.26862954, 0.26130258, 0.27577711),
-                    ),
-                ],
-            )
-
-    def __len__(self) -> int:
-        """Return the length of the dataset."""
-        return len(self.video_paths)
-
-    def __getitem__(self, idx: int) -> Example:
-        """Return a video clip from the dataset."""
-        video_path = self.video_paths[idx]
-        video = EncodedVideo.from_path(video_path, decoder="decord", decode_audio=False)
-
-        clip_sampler = ConstantClipsPerVideoSampler(
-            clip_duration=self.clip_duration,
-            clips_per_video=self.clips_per_video,
-        )
-        all_clips_timepoints = self._get_clip_timepoints(clip_sampler, video.duration)
-
-        all_video = []
-        for start, end in all_clips_timepoints:
-            clip = video.get_clip(start, end)
-            if clip is None:
-                raise ValueError("No clip found")
-            video_clip = clip["video"] / 255.0  # Normalizing
-            video_clip = self.video_transform(video_clip)
-            all_video.append(video_clip)
-
-        all_video = torch.stack(all_video, dim=0)
-        return Example({Modalities.VIDEO: all_video, EXAMPLE_INDEX_KEY: idx})
-
-    def _get_clip_timepoints(
-        self,
-        clip_sampler: ConstantClipsPerVideoSampler,
-        duration: float,
-    ) -> List[Tuple[float, float]]:
-        """Calculate the start and end timepoints for each video clip.
-
-        Parameters
-        ----------
-        clip_sampler
-            The clip sampler instance.
-        duration : int
-            Total duration of the video.
-
-        Returns
-        -------
-        list of tuples
-            List of tuples containing start and end timepoints of each clip.
-        """
-        all_clips_timepoints = []
-        is_last_clip = False
-        end = 0.0
-        while not is_last_clip:
-            start, end, _, _, is_last_clip = clip_sampler(
-                end,
-                duration,
-                annotation=None,
-            )
-            all_clips_timepoints.append((start, end))
-        return all_clips_timepoints
diff --git a/poetry.lock b/poetry.lock
index 8c832f1..d6221f9 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -33,98 +33,113 @@ testing = ["bitsandbytes", "datasets", "diffusers", "evaluate", "parameterized",
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.3.5"
+version = "2.4.0"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohappyeyeballs-2.3.5-py3-none-any.whl", hash = "sha256:4d6dea59215537dbc746e93e779caea8178c866856a721c9c660d7a5a7b8be03"},
-    {file = "aiohappyeyeballs-2.3.5.tar.gz", hash = "sha256:6fa48b9f1317254f122a07a131a86b71ca6946ca989ce6326fff54a99a920105"},
+    {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"},
+    {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"},
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.10.2"
+version = "3.10.5"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohttp-3.10.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:95213b3d79c7e387144e9cb7b9d2809092d6ff2c044cb59033aedc612f38fb6d"},
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-    {file = "av-12.3.0.tar.gz", hash = "sha256:04b1892562aff3277efc79f32bd8f1d0cbb64ed011241cb3e96f9ad471816c22"},
-]
-
 [[package]]
 name = "black"
 version = "24.8.0"
@@ -656,13 +613,13 @@ test = ["pytest"]
 
 [[package]]
 name = "cyclonedx-python-lib"
-version = "7.5.1"
+version = "7.6.0"
 description = "Python library for CycloneDX"
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "cyclonedx_python_lib-7.5.1-py3-none-any.whl", hash = "sha256:9fc2c2e5facfd9530ede1f4525c903d29d91945688c5689b6d5fab46381dcab9"},
-    {file = "cyclonedx_python_lib-7.5.1.tar.gz", hash = "sha256:00cfe1e58452698650ae08b8f4389f7b1ec203a3e1c50cbf6ca6d320941dfb3f"},
+    {file = "cyclonedx_python_lib-7.6.0-py3-none-any.whl", hash = "sha256:30655e89e5f987dc8d57835919748d71589fafeb33ff1dec45048eb72eda3cf9"},
+    {file = "cyclonedx_python_lib-7.6.0.tar.gz", hash = "sha256:fa481d5f0d82728cb6a32e55f8ba9c666ba75a2bd99eb643228e3011c56bb5c4"},
 ]
 
 [package.dependencies]
@@ -718,23 +675,6 @@ files = [
     {file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
 ]
 
-[[package]]
-name = "decord"
-version = "0.6.0"
-description = "Decord Video Loader"
-optional = false
-python-versions = "*"
-files = [
-    {file = "decord-0.6.0-cp36-cp36m-macosx_10_15_x86_64.whl", hash = "sha256:85ef90d2f872384657d7774cc486c237c5b12df62d4ac5cb5c8d6001fa611323"},
-    {file = "decord-0.6.0-cp37-cp37m-macosx_10_15_x86_64.whl", hash = "sha256:9c20674964fb1490c677bd911d2023d2a09fec7a58a4bb0b7ddf1ccc269f107a"},
-    {file = "decord-0.6.0-cp38-cp38-macosx_10_15_x86_64.whl", hash = "sha256:a0eb1258beade34dceb29d97856a7764d179db1b5182899b61874f3418a1abc8"},
-    {file = "decord-0.6.0-py3-none-manylinux2010_x86_64.whl", hash = "sha256:51997f20be8958e23b7c4061ba45d0efcd86bffd5fe81c695d0befee0d442976"},
-    {file = "decord-0.6.0-py3-none-win_amd64.whl", hash = "sha256:02665d7c4f1193a330205a791bc128f7e108eb6ae5b67144437a02f700943bad"},
-]
-
-[package.dependencies]
-numpy = ">=1.14.0"
-
 [[package]]
 name = "defusedxml"
 version = "0.7.1"
@@ -988,29 +928,6 @@ test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,
 test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
 tqdm = ["tqdm"]
 
-[[package]]
-name = "fvcore"
-version = "0.1.5.post20221221"
-description = "Collection of common code shared among different research projects in FAIR computer vision team"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "fvcore-0.1.5.post20221221.tar.gz", hash = "sha256:f2fb0bb90572ae651c11c78e20493ed19b2240550a7e4bbb2d6de87bdd037860"},
-]
-
-[package.dependencies]
-iopath = ">=0.1.7"
-numpy = "*"
-Pillow = "*"
-pyyaml = ">=5.1"
-tabulate = "*"
-termcolor = ">=1.1"
-tqdm = "*"
-yacs = ">=0.1.6"
-
-[package.extras]
-all = ["shapely"]
-
 [[package]]
 name = "gitdb"
 version = "4.0.11"
@@ -1066,13 +983,13 @@ lxml = ["lxml"]
 
 [[package]]
 name = "huggingface-hub"
-version = "0.24.5"
+version = "0.24.6"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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+    {file = "huggingface_hub-0.24.6-py3-none-any.whl", hash = "sha256:a990f3232aa985fe749bc9474060cbad75e8b2f115f6665a9fda5b9c97818970"},
+    {file = "huggingface_hub-0.24.6.tar.gz", hash = "sha256:cc2579e761d070713eaa9c323e3debe39d5b464ae3a7261c39a9195b27bb8000"},
 ]
 
 [package.dependencies]
@@ -1177,13 +1094,13 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "8.2.0"
+version = "8.3.0"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "importlib_metadata-8.2.0-py3-none-any.whl", hash = "sha256:11901fa0c2f97919b288679932bb64febaeacf289d18ac84dd68cb2e74213369"},
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+    {file = "importlib_metadata-8.3.0-py3-none-any.whl", hash = "sha256:42817a4a0be5845d22c6e212db66a94ad261e2318d80b3e0d363894a79df2b67"},
+    {file = "importlib_metadata-8.3.0.tar.gz", hash = "sha256:9c8fa6e8ea0f9516ad5c8db9246a731c948193c7754d3babb0114a05b27dd364"},
 ]
 
 [package.dependencies]
@@ -1219,24 +1136,6 @@ files = [
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 ]
 
-[[package]]
-name = "iopath"
-version = "0.1.10"
-description = "A library for providing I/O abstraction."
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "iopath-0.1.10.tar.gz", hash = "sha256:3311c16a4d9137223e20f141655759933e1eda24f8bff166af834af3c645ef01"},
-]
-
-[package.dependencies]
-portalocker = "*"
-tqdm = "*"
-typing_extensions = "*"
-
-[package.extras]
-aws = ["boto3"]
-
 [[package]]
 name = "ipykernel"
 version = "6.29.5"
@@ -1480,13 +1379,13 @@ test-ui = ["calysto-bash"]
 
 [[package]]
 name = "license-expression"
-version = "30.3.0"
+version = "30.3.1"
 description = "license-expression is a comprehensive utility library to parse, compare, simplify and normalize license expressions (such as SPDX license expressions) using boolean logic."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "license-expression-30.3.0.tar.gz", hash = "sha256:1295406f736b4f395ff069aec1cebfad53c0fcb3cf57df0f5ec58fc7b905aea5"},
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+    {file = "license_expression-30.3.1-py3-none-any.whl", hash = "sha256:97904b9185c7bbb1e98799606fa7424191c375e70ba63a524b6f7100e42ddc46"},
+    {file = "license_expression-30.3.1.tar.gz", hash = "sha256:60d5bec1f3364c256a92b9a08583d7ea933c7aa272c8d36d04144a89a3858c01"},
 ]
 
 [package.dependencies]
@@ -2285,11 +2184,11 @@ files = [
 [package.dependencies]
 numpy = [
     {version = ">=1.21.0", markers = "python_version == \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
-    {version = ">=1.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"aarch64\" and python_version >= \"3.8\" and python_version < \"3.10\" or python_version > \"3.9\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_system != \"Darwin\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_machine != \"arm64\" and python_version < \"3.10\""},
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     {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
+    {version = ">=1.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"aarch64\" and python_version >= \"3.8\" and python_version < \"3.10\" or python_version > \"3.9\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_system != \"Darwin\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_machine != \"arm64\" and python_version < \"3.10\""},
 ]
 
 [[package]]
@@ -2393,20 +2292,6 @@ sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-d
 test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
 xml = ["lxml (>=4.9.2)"]
 
-[[package]]
-name = "parameterized"
-version = "0.9.0"
-description = "Parameterized testing with any Python test framework"
-optional = false
-python-versions = ">=3.7"
-files = [
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-]
-
-[package.extras]
-dev = ["jinja2"]
-
 [[package]]
 name = "parso"
 version = "0.8.4"
@@ -2676,25 +2561,6 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
-[[package]]
-name = "portalocker"
-version = "2.10.1"
-description = "Wraps the portalocker recipe for easy usage"
-optional = false
-python-versions = ">=3.8"
-files = [
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-
-[package.dependencies]
-pywin32 = {version = ">=226", markers = "platform_system == \"Windows\""}
-
-[package.extras]
-docs = ["sphinx (>=1.7.1)"]
-redis = ["redis"]
-tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "pytest-timeout (>=2.1.0)", "redis", "sphinx (>=6.0.0)", "types-redis"]
-
 [[package]]
 name = "pre-commit"
 version = "3.8.0"
@@ -2972,33 +2838,6 @@ extra = ["bitsandbytes (>=0.42.0)", "hydra-core (>=1.2.0)", "jsonargparse[signat
 strategies = ["deepspeed (>=0.8.2,<=0.9.3)"]
 test = ["cloudpickle (>=1.3)", "coverage (==7.3.1)", "fastapi", "numpy (>=1.17.2)", "onnx (>=1.12.0)", "onnxruntime (>=1.12.0)", "pandas (>1.0)", "psutil (<5.9.6)", "pytest (==7.4.0)", "pytest-cov (==4.1.0)", "pytest-random-order (==1.1.0)", "pytest-rerunfailures (==12.0)", "pytest-timeout (==2.1.0)", "scikit-learn (>0.22.1)", "tensorboard (>=2.9.1)", "uvicorn"]
 
-[[package]]
-name = "pytorchvideo"
-version = "0.1.5"
-description = "A video understanding deep learning library."
-optional = false
-python-versions = ">=3.7"
-files = []
-develop = false
-
-[package.dependencies]
-av = "*"
-fvcore = "*"
-iopath = "*"
-networkx = "*"
-parameterized = "*"
-
-[package.extras]
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-opencv-python = ["opencv-python"]
-test = ["coverage", "decord", "opencv-python", "pytest"]
-
-[package.source]
-type = "git"
-url = "https://github.com/facebookresearch/pytorchvideo"
-reference = "main"
-resolved_reference = "1fadaef40dd393ca09680f55582399f4679fc9b7"
-
 [[package]]
 name = "pytz"
 version = "2024.1"
@@ -3111,120 +2950,120 @@ files = [
 
 [[package]]
 name = "pyzmq"
-version = "26.1.0"
+version = "26.1.1"
 description = "Python bindings for 0MQ"
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 python-versions = ">=3.7"
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 [package.dependencies]
@@ -3486,29 +3325,29 @@ files = [
 
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+version = "0.6.1"
 description = "An extremely fast Python linter and code formatter, written in Rust."
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 python-versions = ">=3.7"
 files = [
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 ]
 
 [[package]]
@@ -3645,13 +3484,13 @@ torch = ["safetensors[numpy]", "torch (>=1.10)"]
 
 [[package]]
 name = "sentry-sdk"
-version = "2.12.0"
+version = "2.13.0"
 description = "Python client for Sentry (https://sentry.io)"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
@@ -3678,6 +3517,7 @@ httpx = ["httpx (>=0.16.0)"]
 huey = ["huey (>=2)"]
 huggingface-hub = ["huggingface-hub (>=0.22)"]
 langchain = ["langchain (>=0.0.210)"]
+litestar = ["litestar (>=2.0.0)"]
 loguru = ["loguru (>=0.5)"]
 openai = ["openai (>=1.0.0)", "tiktoken (>=0.3.0)"]
 opentelemetry = ["opentelemetry-distro (>=0.35b0)"]
@@ -3795,19 +3635,19 @@ test = ["pytest"]
 
 [[package]]
 name = "setuptools"
-version = "72.1.0"
+version = "73.0.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "setuptools-72.1.0.tar.gz", hash = "sha256:8d243eff56d095e5817f796ede6ae32941278f542e0f941867cc05ae52b162ec"},
+    {file = "setuptools-73.0.0-py3-none-any.whl", hash = "sha256:f2bfcce7ae1784d90b04c57c2802e8649e1976530bb25dc72c2b078d3ecf4864"},
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 ]
 
 [package.extras]
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-doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "mypy (==1.11.*)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (<0.4)", "pytest-ruff (>=0.2.1)", "pytest-ruff (>=0.3.2)", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.text (>=3.7)", "more-itertools (>=8.8)", "packaging (>=24)", "platformdirs (>=2.6.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
+test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "mypy (==1.11.*)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (<0.4)", "pytest-ruff (>=0.2.1)", "pytest-ruff (>=0.3.2)", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
 
 [[package]]
 name = "six"
@@ -3881,13 +3721,13 @@ dev = ["black (==23.3.0)", "coverage[toml] (>=5.1)", "flit (>=3.5.1)", "isort (=
 
 [[package]]
 name = "sympy"
-version = "1.13.1"
+version = "1.13.2"
 description = "Computer algebra system (CAS) in Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3896,20 +3736,6 @@ mpmath = ">=1.1.0,<1.4"
 [package.extras]
 dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
 
-[[package]]
-name = "tabulate"
-version = "0.9.0"
-description = "Pretty-print tabular data"
-optional = false
-python-versions = ">=3.7"
-files = [
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-]
-
-[package.extras]
-widechars = ["wcwidth"]
-
 [[package]]
 name = "tbb"
 version = "2021.13.1"
@@ -3923,20 +3749,6 @@ files = [
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 ]
 
-[[package]]
-name = "termcolor"
-version = "2.4.0"
-description = "ANSI color formatting for output in terminal"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[package.extras]
-tests = ["pytest", "pytest-cov"]
-
 [[package]]
 name = "timm"
 version = "1.0.8"
@@ -4107,13 +3919,13 @@ files = [
 
 [[package]]
 name = "tomlkit"
-version = "0.13.0"
+version = "0.13.2"
 description = "Style preserving TOML library"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "tomlkit-0.13.2-py3-none-any.whl", hash = "sha256:7a974427f6e119197f670fbbbeae7bef749a6c14e793db934baefc1b5f03efde"},
+    {file = "tomlkit-0.13.2.tar.gz", hash = "sha256:fff5fe59a87295b278abd31bec92c15d9bc4a06885ab12bcea52c71119392e79"},
 ]
 
 [[package]]
@@ -4477,19 +4289,19 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess
 
 [[package]]
 name = "wandb"
-version = "0.17.6"
+version = "0.17.7"
 description = "A CLI and library for interacting with the Weights & Biases API."
 optional = false
 python-versions = ">=3.7"
 files = [
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-    {file = "wandb-0.17.6-py3-none-win_amd64.whl", hash = "sha256:51954f993b372c20812616838302183f0e3abf137614f05d80c7c17c307bfff9"},
-    {file = "wandb-0.17.6.tar.gz", hash = "sha256:416739f293d59b95bcb189ecbaeb19b3a74ff2b80d501a90b93e6b6f9435c017"},
+    {file = "wandb-0.17.7-py3-none-any.whl", hash = "sha256:42f37d7d4f1934fc5a33233be1de0f0c8e3bbff04a4403b3ac6030e577cc84e1"},
+    {file = "wandb-0.17.7-py3-none-macosx_10_14_x86_64.whl", hash = "sha256:ed3fcf51b533249db306a9dd41893d671eb936f64b8837ffc504dba56609ff47"},
+    {file = "wandb-0.17.7-py3-none-macosx_11_0_arm64.whl", hash = "sha256:f21183b74ed05744b274c7d876d473ae14a985becfbabd005104ce7e78200cf8"},
+    {file = "wandb-0.17.7-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:011cca25b2ca57956d1ff2c84e31c903058cc8f552ecc1d0450ffad34c8a59bd"},
+    {file = "wandb-0.17.7-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:df335a67d3fff9299d915c127ad476cdf9e3f2b1d86e025f54ed63c7dab62d72"},
+    {file = "wandb-0.17.7-py3-none-win32.whl", hash = "sha256:de7e040fe553e149926437ea2d24a20c6b563092e5a17709c4b99dff8a38470c"},
+    {file = "wandb-0.17.7-py3-none-win_amd64.whl", hash = "sha256:c81be25cb1a5322aff95f66a89ca4abcb2a8e98ee09b8938f123a536b967a235"},
+    {file = "wandb-0.17.7.tar.gz", hash = "sha256:4623fb7618ff094ebab91101b8b5dcef5b3513d35e867a10f64021ca427bb38d"},
 ]
 
 [package.dependencies]
@@ -4544,21 +4356,6 @@ files = [
     {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
 ]
 
-[[package]]
-name = "yacs"
-version = "0.1.8"
-description = "Yet Another Configuration System"
-optional = false
-python-versions = "*"
-files = [
-    {file = "yacs-0.1.8-py2-none-any.whl", hash = "sha256:d43d1854c1ffc4634c5b349d1c1120f86f05c3a294c9d141134f282961ab5d94"},
-    {file = "yacs-0.1.8-py3-none-any.whl", hash = "sha256:99f893e30497a4b66842821bac316386f7bd5c4f47ad35c9073ef089aa33af32"},
-    {file = "yacs-0.1.8.tar.gz", hash = "sha256:efc4c732942b3103bea904ee89af98bcd27d01f0ac12d8d4d369f1e7a2914384"},
-]
-
-[package.dependencies]
-PyYAML = "*"
-
 [[package]]
 name = "yarl"
 version = "1.9.4"
@@ -4664,20 +4461,25 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.19.2"
+version = "3.20.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.19.2-py3-none-any.whl", hash = "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c"},
-    {file = "zipp-3.19.2.tar.gz", hash = "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19"},
+    {file = "zipp-3.20.0-py3-none-any.whl", hash = "sha256:58da6168be89f0be59beb194da1250516fdaa062ccebd30127ac65d30045e10d"},
+    {file = "zipp-3.20.0.tar.gz", hash = "sha256:0145e43d89664cfe1a2e533adc75adafed82fe2da404b4bbb6b026c0157bdb31"},
 ]
 
 [package.extras]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
+[extras]
+audio = ["torchaudio"]
+peft = ["peft"]
+vision = ["opencv-python", "timm", "torchvision"]
+
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9, <3.13"
-content-hash = "2fdac68071dd0fe9f0c7481a6d7b61a27ae8b26b5e9dd1022f2fd80df5d0dcb3"
+content-hash = "04aedc790392dba74b0a1b9a0e2d0c7cbda861e59fe6885d01fea9e4bf9ff41c"
diff --git a/projects/med_benchmarking/README.md b/projects/med_benchmarking/README.md
index a64ac34..b06277f 100644
--- a/projects/med_benchmarking/README.md
+++ b/projects/med_benchmarking/README.md
@@ -3,7 +3,7 @@ Prior to running any experiments under this project, please install the required
 ```bash
 pip install -r requirements.txt
 ```
-**NOTE**: It is assumed that the requirements for the `mmlearn` package have already been installed in a virtual environment. 
+**NOTE**: It is assumed that the requirements for the `mmlearn` package have already been installed in a virtual environment.
 If not, please refer to the README file in the `mmlearn` package for installation instructions.
 
 Also, please make sure to set the following environment variables:
diff --git a/pyproject.toml b/pyproject.toml
index e7c1eab..00a0bc1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "mmlearn"
-version = "0.1.0a0.dev1" # https://www.python.org/dev/peps/pep-0440/#version-schemes
+version = "0.1.0a0.dev2" # https://www.python.org/dev/peps/pep-0440/#version-schemes
 description = "A modular framework for research on multimodal representation learning."
 readme = "README.md"
 authors = ["Vector AI Engineering <ai_engineering@vectorinstitute.ai>"]
@@ -20,17 +20,19 @@ transformers = "^4.44.0"
 torch = {version = "^2.3.0", source = "torch-cu121"}
 lightning = "^2.3.0"
 jsonlines = "^4.0.0"
-pandas = "^2.2.2"
+pandas = {version="^2.2.2", extras=["numexpr", "bottleneck"]}
+
+torchvision = {version = "^0.18.0", source = "torch-cu121", optional = true}
+opencv-python = {version = "^4.10.0.84", optional = true}
+timm = {version = "^1.0.7", optional = true}
+torchaudio = {version = "^2.3.0", source = "torch-cu121", optional = true}
+peft = {version = "^0.12.0", optional = true}
 
 [tool.poetry.group.vision.dependencies]
 torchvision = {version = "^0.18.0", source = "torch-cu121"}
 opencv-python = "^4.10.0.84"
 timm = "^1.0.7"
 
-[tool.poetry.group.video.dependencies]
-pytorchvideo = {git = "https://github.com/facebookresearch/pytorchvideo", branch = "main"}
-decord = "^0.6.0"
-
 [tool.poetry.group.audio.dependencies]
 torchaudio = {version = "^2.3.0", source = "torch-cu121"}
 
@@ -52,7 +54,7 @@ ipython = "8.18.0"
 optional = true
 
 [tool.poetry.group.test.dependencies]
-ruff = "^0.5.6"
+ruff = "^0.6.1"
 mypy = "^1.11.1"
 pytest = "^8.3.2"
 pre-commit = "^3.8.0"
@@ -65,6 +67,11 @@ name = "torch-cu121"
 url = "https://download.pytorch.org/whl/cu121"
 priority = "supplemental"
 
+[tool.poetry.extras]
+peft = ["peft"]
+vision = ["torchvision", "opencv-python", "timm"]
+audio = ["torchaudio"]
+
 [tool.mypy]
 ignore_missing_imports = true
 install_types = true
@@ -125,9 +132,9 @@ ignore = [
     "COM812", # Missing trailing comma
 ]
 
-# Ignore import violations in all `__init__.py` files.
 [tool.ruff.lint.per-file-ignores]
-"__init__.py" = ["E402", "F401", "F403", "F811"]
+"__init__.py" = ["E402", "F401", "F403", "F811"] # Ignore import violations in all `__init__.py` files.
+"projects/*" = ["D", "F", "I"] # Ignore docstring, pyflakes, and isort violations in all `projects` files.
 
 [tool.ruff.lint.pep8-naming]
 ignore-names = ["X*", "setUp*"]