Refactor import error handling in models and update dependencies in documentation

Author: loribonna

.github/workflows/deploy_pages.yml

@@ -37,12 +37,11 @@ jobs:
       - uses: actions/setup-python@v3
         with:
           python-version: "3.10"
-      - name: Install dependencies
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+      - name: Build docs
         run: |
-          pip install -r docs/requirements.txt -r requirements.txt -r requirements-optional.txt
-      - name: Sphinx build
-        run: |
-          python ./utils/args.py && sphinx-build -j auto docs _build
+          cd docs && uv run make html
       - name: Setup Pages
         uses: actions/configure-pages@v5
       - name: Upload artifact

datasets/seq_eurosat_rgb.py

@@ -16,7 +16,7 @@
 try:
     from google_drive_downloader import GoogleDriveDownloader as gdd
 except ImportError:
-    raise ImportError("Please install the google_drive_downloader package by running: `pip install googledrivedownloader`")
+    raise ImportError("Please install the google_drive_downloader package by running: `pip install googledrivedownloader==0.4`")
 
 from datasets.utils import set_default_from_args
 from utils.conf import base_path

docs/pyproject.toml

@@ -3,7 +3,24 @@ name = "docs"
 version = "0.1.0"
 requires-python = ">=3.10"
 dependencies = [
+    "clip",
+    "ftfy>=6.3.1",
     "furo==2023.9.10",
+    "googledrivedownloader==0.4",
+    "kmeans-pytorch>=0.3",
+    "kornia>=0.8.1",
+    "numpy>=2.2.5",
+    "pandas>=2.2.3",
+    "qpsolvers>=4.7.0",
+    "regex>=2024.11.6",
+    "scikit-learn>=1.6.1",
     "sphinx==7.2.6",
     "sphinx-toolbox==3.5.0",
+    "timm==0.9.8",
+    "torch>=2.7.0",
+    "transformers>=4.51.3",
+    "xitorch>=0.5.1",
 ]
+
+[tool.uv.sources]
+clip = { git = "https://github.com/openai/CLIP.git" }

docs/utils/args.rst

@@ -9,19 +9,19 @@ Arguments
 	*Help*: Which dataset to perform experiments on.
 
 	- *Default*: ``None``
-	- *Choices*: ``seq-tinyimg, seq-mit67, seq-cars196, seq-cifar100-224-rs, seq-cifar100-224, seq-chestx, seq-celeba, seq-cifar10-224-rs, mnist-360, seq-cropdisease, seq-eurosat-rgb, seq-imagenet-r, seq-cifar100, seq-cifar10-224, perm-mnist, seq-cub200, seq-cifar10, rot-mnist, seq-resisc45, seq-mnist, seq-cub200-rs, seq-isic, seq-tinyimg-r``
+	- *Choices*: ``mnist-360, perm-mnist, rot-mnist, seq-cars196, seq-celeba, seq-chestx, seq-cifar10, seq-cifar100, seq-cifar100-224, seq-cifar100-224-rs, seq-cifar10-224, seq-cifar10-224-rs, seq-cropdisease, seq-cub200, seq-cub200-rs, seq-eurosat-rgb, seq-imagenet-r, seq-isic, seq-mit67, seq-mnist, seq-resisc45, seq-tinyimg, seq-tinyimg-r``
 
 **\-\-model** : str (with underscores replaced by dashes)
 	*Help*: Model name.
 
 	- *Default*: ``None``
-	- *Choices*: ``joint-gcl, second-stage-starprompt, lwf-mc, puridiver, xder-rpc-cscct, gdumb-lider, zscl, joint, cnll, ewc-on, xder, ranpac, hal, idefics, derpp-casper, er-ace-tricks, xder-rpc-star, sgd, si, moe-adapters, first-stage-starprompt, er-ace-aer-abs, icarl, lucir, fdr, icarl-lider, derpp, der, derpp-lider, gem, bic, llava, er-ace-casper, attriclip, second-order, starprompt, er-star, lws, coda-prompt, er-tricks, clip, pnn, er-ace, xder-ce, icarl-cscct, derpp-star, dualprompt, twf, mer, er-ace-lider, gdumb, derpp-cscct, dap, l2p, ccic, slca, agem-r, rpc, er-ace-cscct, icarl-casper, xder-rpc, gss, er-ace-star, spr, xder-rpc-casper, lwf, cgil, er, agem``
+	- *Choices*: ``agem, agem-r, attriclip, bic, ccic, cgil, clip, cnll, coda-prompt, dap, der, derpp, derpp-casper, derpp-cscct, derpp-lider, derpp-star, dualprompt, er, er-ace, er-ace-aer-abs, er-ace-casper, er-ace-cscct, er-ace-lider, er-ace-star, er-ace-tricks, er-star, er-tricks, ewc-on, fdr, first-stage-starprompt, gdumb, gdumb-lider, gem, gss, hal, icarl, icarl-casper, icarl-cscct, icarl-lider, idefics, joint, joint-gcl, l2p, llava, lucir, lwf, lwf-mc, lws, mer, moe-adapters, pnn, puridiver, ranpac, rpc, second-order, second-stage-starprompt, sgd, si, slca, spr, starprompt, twf, xder, xder-ce, xder-rpc, xder-rpc-casper, xder-rpc-cscct, xder-rpc-star, zscl``
 
 **\-\-backbone** : str (with underscores replaced by dashes)
 	*Help*: Backbone network name.
 
 	- *Default*: ``None``
-	- *Choices*: ``preact-resnet18, resnet18, resnet18-7x7-pt, reduced-resnet18, resnet34, resnet18-spr, resnet50, resnet50-pt, resnet32, mnistmlp, vit``
+	- *Choices*: ``mnistmlp, preact-resnet18, resnet18, resnet18-7x7-pt, reduced-resnet18, resnet34, resnet18-spr, resnet32, resnet50, resnet50-pt, vit``
 
 **\-\-load_best_args** : unknown
 	*Help*: (deprecated) Loads the best arguments for each method, dataset and memory buffer. NOTE: This option is deprecated and not up to date.

models/idefics.py

@@ -5,22 +5,6 @@
 import torch.nn as nn
 from torchvision import transforms
 
-try:
-    import bitsandbytes
-except ImportError:
-    raise ImportError("Please install the BitsAndBytes package by running: `pip install -i https://pypi.org/simple/ bitsandbytes`")
-
-try:
-    import accelerate
-except ImportError:
-    raise ImportError("Please install the accelerate package by running: `pip install accelerate`")
-
-try:
-    from transformers import BitsAndBytesConfig, IdeficsForVisionText2Text, AutoProcessor
-    from transformers.generation import GenerationConfig
-except ImportError as err:
-    raise ImportError("Please install the HuggingFace Transformers package by running: pip install transformers>=4.49.0")
-
 from datasets.utils.continual_dataset import ContinualDataset
 from models.utils.continual_model import ContinualModel
 from utils.args import ArgumentParser
@@ -31,6 +15,24 @@ class FinalModel(nn.Module):
     def __init__(self, dataset: ContinualDataset, args: Namespace, denorm_transform, device):
         super().__init__()
 
+        # moved here to avoid having to install them when building docs
+        try:
+            import bitsandbytes
+        except ImportError:
+            raise ImportError("Please install the BitsAndBytes package by running: `pip install -i https://pypi.org/simple/ bitsandbytes`")
+
+        try:
+            import accelerate
+        except ImportError:
+            raise ImportError("Please install the accelerate package by running: `pip install accelerate`")
+
+        try:
+            from transformers import BitsAndBytesConfig, IdeficsForVisionText2Text, AutoProcessor
+            from transformers.generation import GenerationConfig
+        except ImportError as err:
+            raise ImportError("Please install the HuggingFace Transformers package by running: pip install transformers>=4.49.0")
+
+
         self.denorm_transform = denorm_transform
         self.device = device
 

models/llava.py

@@ -4,22 +4,6 @@
 import torch.nn as nn
 from torchvision import transforms
 
-try:
-    import bitsandbytes
-except ImportError:
-    raise ImportError("Please install the BitsAndBytes package by running: `pip install -i https://pypi.org/simple/ bitsandbytes`")
-
-try:
-    import accelerate
-except ImportError:
-    raise ImportError("Please install the accelerate package by running: `pip install accelerate`")
-
-
-try:
-    import sentencepiece
-except ImportError:
-    raise ImportError("Please install the sentencepiece package by running: `pip install sentencepiece`")
-
 try:
     from transformers import AutoProcessor, LlavaForConditionalGeneration, BitsAndBytesConfig
 except ImportError:
@@ -36,6 +20,23 @@ class FinalModel(nn.Module):
     def __init__(self, dataset: ContinualDataset, args: Namespace, denorm_transform, device):
         super().__init__()
 
+        # moved here to avoid having to install them when building docs
+        try:
+            import bitsandbytes
+        except ImportError:
+            raise ImportError("Please install the BitsAndBytes package by running: `pip install -i https://pypi.org/simple/ bitsandbytes`")
+
+        try:
+            import accelerate
+        except ImportError:
+            raise ImportError("Please install the accelerate package by running: `pip install accelerate`")
+
+
+        try:
+            import sentencepiece
+        except ImportError:
+            raise ImportError("Please install the sentencepiece package by running: `pip install sentencepiece`")
+
         self.denorm_transform = denorm_transform
         self.device = device