Drops timm, fixes docs (#63)

* drops timm, fixes docs

* drops timm

* tries fixing docs

* patch up docs

* final try for docs

* fixes

* one more chance

.github/workflows/sphinx-docs-build.yml

@@ -13,19 +13,10 @@ jobs:
         with:
           # git is required to clone the docs theme
           # before custom requirement are resolved https://github.com/ammaraskar/sphinx-action/issues/16
-          pre-build-command: "sudo apt-get update -y && sudo apt-get install -y git && pip install . && pip install -r docs/requirements.txt"  
+          pre-build-command: "sudo apt-get update -y && sudo apt-get install -y git && pip install -r docs/requirements.txt" 
+          build-command: "sphinx-build -b html source build"
           docs-folder: "docs/"
-      - name: Test Documentation
-        env:
-          SPHINX_MOCK_REQUIREMENTS: 0
-        run: |
-          # First run the same pipeline as Read-The-Docs
-          sudo apt-get install python3-sphinx
-          sudo apt-get install -y texlive-latex-extra dvipng texlive-pictures
-          sudo apt-get install -y cmake
-          pip install .
-          pip install -r docs/requirements.txt
-          cd docs
-          make clean
-          make html
-        shell: bash
+      - uses: actions/upload-artifact@master
+        with:
+          name: Documentation
+          path: docs/build/

.github/workflows/sphinx-docs-deploy.yml

@@ -1,4 +1,4 @@
-name: Deploy mkdocs
+name: Deploy Sphinx Docs
 
 on:
   push:
@@ -9,10 +9,28 @@ jobs:
   sphinx-check:
     runs-on: ubuntu-20.04
     steps:
-    - uses: actions/checkout@v2
-    - uses: ammaraskar/sphinx-action@master
-      with:
-        # git is required to clone the docs theme
-        # before custom requirement are resolved https://github.com/ammaraskar/sphinx-action/issues/16
-        pre-build-command: "apt-get update -y && apt-get install -y git && pip install -r docs/requirements.txt"
-        docs-folder: "docs/"
+      - uses: actions/checkout@master
+      - uses: ammaraskar/sphinx-action@master
+        with:
+          # git is required to clone the docs theme
+          # before custom requirement are resolved https://github.com/ammaraskar/sphinx-action/issues/16
+          pre-build-command: "sudo apt-get update -y && sudo apt-get install -y git && pip install -r docs/requirements.txt"  
+          build-command: "sphinx-build -b html source build"
+          docs-folder: "docs/"
+      - name: Deploy Documentation
+        uses: ad-m/github-push-action@master
+        with:
+          branch: gh-pages
+          directory: master
+          force: true
+      #   run: |
+      #     # First run the same pipeline as Read-The-Docs
+      #     sudo apt-get install python3-sphinx
+      #     sudo apt-get install -y texlive-latex-extra dvipng texlive-pictures
+      #     sudo apt-get install -y cmake
+      #     pip install .
+      #     pip install -r docs/requirements.txt
+      #     cd docs
+      #     make html
+      #   shell: bash
+      # - name: 

.gitignore

@@ -1,6 +1,7 @@
 # Files
 *.DS_Store
 *.vscode
+*.idea
 *.vs
 .vscode
 # dotenv

docs/index.rst

@@ -4,14 +4,12 @@
    contain the root `toctree` directive.
 
 Quickvision API
-=======================================
+===============
 
 .. toctree::
    :maxdepth: 2
    :caption: Contents:
 
-   modules
-
 Indices and tables
 ==================
 

quickvision/models/classification/cnn/__init__.py

@@ -7,7 +7,6 @@
     sanity_fit,
 )
 from quickvision.models.classification.cnn.model_factory import (
-    create_timm_cnn,
     vision_cnn,
     create_vision_cnn,
 )

quickvision/models/classification/cnn/model_factory.py

@@ -2,29 +2,11 @@
 # We will remove the Linear Layer and create a new Linear Layer with num_classes
 # Port from pytorch_cnn_trainer https://github.com/oke-aditya/pytorch_cnn_trainer
 
-import timm
 import torchvision
 from quickvision.models import components
 import torch.nn as nn
 
-__all__ = ["create_timm_cnn", "vision_cnn", "create_vision_cnn"]
-
-
-def create_timm_cnn(model_name: str, num_classes: int,
-                    in_channels: int = 3, pretrained: bool = True,):
-
-    """
-    Creates a model from PyTorch Image Models repository.
-    To know which models are supported print(timm.list_models())
-    Args:
-        model_name (str) : Name of the model. E.g. efficientnet_b3
-        num_classes (int) : Number of classes for classification.
-        in_channels (int) : Defualt 3. Number of channels of images, 1 for grayscale, 3 for RGB
-        pretrained (bool) : If true uses modelwweights pretrained on ImageNet.
-    """
-    model = timm.create_model(model_name, pretrained=pretrained, num_classes=num_classes,
-                              in_chans=in_channels,)
-    return model
+__all__ = ["vision_cnn", "create_vision_cnn"]
 
 
 class vision_cnn(nn.Module):

requirements.txt

@@ -1,3 +1,2 @@
-timm
 pytorch_lightning
 scipy

tests/test_cnn.py

@@ -28,11 +28,6 @@
 
 
 class ModelFactoryTester(unittest.TestCase):
-    def test_create_timm_cnn(self):
-        for model_name in supported_timm_models:
-            model = cnn.create_timm_cnn(model_name, 10, pretrained=None)
-            self.assertTrue(isinstance(model, nn.Module))
-
     def test_vision_cnn(self):
         for model_name in supported_tv_models:
             model = cnn.vision_cnn(model_name, 10, pretrained=None)