Merge branch 'master' into 1.11.0

.github/workflows/ci.yaml

@@ -16,7 +16,7 @@ jobs:
       matrix:
         os: [ubuntu-18.04]
         python-version: [3.7]
-        pytorch-version: [1.3.1, 1.4.0, 1.5.1, 1.6.0, 1.7.1, 1.8.1, 1.9.1, 1.10.2, 1.11.0]
+        pytorch-version: [1.4.0, 1.5.1, 1.6.0, 1.7.1, 1.8.1, 1.9.1, 1.10.2, 1.11.0]
         chainer-version: [6.0.0]
         # NOTE(kamo): Conda is tested by Circle-CI
         use-conda: [false]

.github/workflows/docker.yml

@@ -0,0 +1,48 @@
+name: docker-builder
+
+on:
+  pull_request:
+    types: [closed]
+    branches:
+      - master
+    paths:
+      - 'tools/**'
+      - setup.py
+
+jobs:
+  docker:
+    runs-on: ubuntu-latest
+    if: github.event.pull_request.merged == true
+    steps:
+      - uses: actions/checkout@v2
+
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v1
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v1
+
+      - name: Login to DockerHub
+        uses: docker/login-action@v1 
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+      - name: Build and push CPU container
+        run: |
+          cd docker
+          docker build --build-arg FROM_TAG=runtime-latest \
+            -f prebuilt/devel.dockerfile \
+            --target devel \
+            -t espnet/espnet:cpu-latest .
+          docker push espnet/espnet:cpu-latest   
+
+      - name: Build and push GPU container
+        run: |
+          cd docker
+          docker build --build-arg FROM_TAG=cuda-latest \
+            --build-arg CUDA_VER=11.1 \
+            -f prebuilt/devel.dockerfile \
+            --target devel \
+            -t espnet/espnet:gpu-latest .
+          docker push espnet/espnet:gpu-latest

.gitignore

@@ -42,6 +42,8 @@ egs*/*/*/tensorboard
 egs*/*/*/wav*
 egs*/*/*/nltk*
 egs*/*/*/.cache*
+egs*/*/*/pretrained_models*
+egs*/fisher_callhome_spanish/*/local/mapping*
 
 # tools related
 tools/chainer

.gitmodules

@@ -1,3 +0,0 @@
-[submodule "doc/notebook"]
-	path = doc/notebook
-	url = https://github.com/espnet/notebook

CONTRIBUTING.md

@@ -53,9 +53,9 @@ ESPnet2's recipes correspond to `egs2`. ESPnet2 applies a new paradigm without d
 For ESPnet2, we do not recommend preparing the recipe's stages for each corpus but using the common pipelines we provided in `asr.sh`, `tts.sh`, and
 `enh.sh`. For details of creating ESPnet2 recipes, please refer to [egs2-readme](https://github.com/espnet/espnet/blob/master/egs2/TEMPLATE/README.md).
 
-The common pipeline of ESPnet2 recipes will take care of the `RESULTS.md` generation, model packing, and uploading. ESPnet2 models are maintained at Zenodo and Hugging Face.
+The common pipeline of ESPnet2 recipes will take care of the `RESULTS.md` generation, model packing, and uploading. ESPnet2 models are maintained at Hugging Face and Zenodo (Deprecated).
 You can also refer to the document in https://github.com/espnet/espnet_model_zoo
-To upload your model, you need first:
+To upload your model, you need first (This is currently deprecated , uploading to Huggingface Hub is prefered) :
 1. Sign up to Zenodo: https://zenodo.org/
 2. Create access token: https://zenodo.org/account/settings/applications/tokens/new/
 3. Set your environment: % export ACCESS_TOKEN="<your token>"
@@ -64,6 +64,21 @@ To port models from zenodo using Hugging Face hub,
 1. Create a Hugging Face account - https://huggingface.co/
 2. Request to be added to espnet organisation - https://huggingface.co/espnet
 3. Go to `egs2/RECIPE/*/scripts/utils` and run `./upload_models_to_hub.sh "ZENODO_MODEL_NAME"`
+
+To upload models using Huggingface-cli follow the following steps:
+You can also refer to https://huggingface.co/docs/transformers/model_sharing
+1. Create a Hugging Face account - https://huggingface.co/
+2. Request to be added to espnet organisation - https://huggingface.co/espnet 
+3. Run huggingface-cli login (You can get the token request at this step under setting > Access Tokens > espnet token  
+4. `huggingface-cli repo create your-model-name --organization espnet`
+5. `git clone https://huggingface.co/username/your-model-name` (clone this outside ESPNet to avoid issues as this a git repo)
+6. `cd your-model-name`
+7. `git lfs install`
+8. copy contents from exp diretory of your recipe into this directory (Check other models of similar task under ESPNet to confirm your directory structure) 
+9. `git add . `
+10. `git commit -m "Add model files"`
+11. `git push`
+12. Check if the inference demo on HF is running successfully to verify the upload      
 
 #### 1.3.3 Additional requirements for new recipe
 
@@ -76,6 +91,18 @@ to its differences.
 - If a recipe for a new corpus is proposed, you should add its name and information to:
 https://github.com/espnet/espnet/blob/master/egs/README.md if it's a ESPnet1 recipe,
 or https://github.com/espnet/espnet/blob/master/egs2/README.md + `db.sh` if it's a ESPnet2 recipe.
+
+#### 1.3.4 Checklist before you submit the recipe-based PR
+
+- [ ] be careful about the name for the recipe. It is recommended to follow naming conventions of the other recipes
+- [ ] common/shared files are linked with **soft link** (see Section 1.3.3)
+- [ ] modified or new python scripts should be passed through **latest** black formating (by using python package black). The command to be executed could be `black espnet espnet2 test utils setup.py egs*/*/*/local egs2/TEMPLATE/asr1/pyscripts`
+- [ ] cluster settings should be set as **default** (e.g., cmd.sh conf/slurm.conf conf/queue.conf conf/pbs.conf)
+- [ ] update `egs/README.md` or `egs2/README.md` with corresponding recipes
+- [ ] add corresponding entry in `egs2/TEMPLATE/db.sh` for a new corpus
+- [ ] try to **simplify** the model configurations. We recommend to have only the best configuration for the start of a recipe. Please also follow the default rule defined in Section 1.3.3
+- [ ] large meta-information for a corpus should be maintained elsewhere other than in the recipe itself
+- [ ] recommend to also include results and pre-trained model with the recipe
 
 ## 2 Pull Request
 If your proposed feature or bugfix is ready, please open a Pull Request (PR) at https://github.com/espnet/espnet
@@ -124,6 +151,11 @@ we recommend using small model parameters and avoiding dynamic imports, file acc
 more running time, you can annotate your test with `@pytest.mark.execution_timeout(sec)`.
 - For test initialization (parameters, modules, etc), you can use pytest fixtures. Refer to  [pytest fixtures](https://docs.pytest.org/en/latest/fixture.html#using-fixtures-from-classes-modules-or-projects) for more information.
 
+In addition, please follow the [PEP 8 convention](https://peps.python.org/pep-0008/) for the coding style and [Google's convention for docstrings](https://google.github.io/styleguide/pyguide.html#383-functions-and-methods).
+Below are some specific points that should be taken care of in particular:
+- [import ordering](https://peps.python.org/pep-0008/#imports)
+- Avoid writing python2-style code. For example, `super().__init__()` is preferred over `super(CLASS_NAME, self).__init()__`.
+
 
 ### 4.2 Bash scripts