Updates with Poplar SDK 3.2 release

Author: adamjsanders277

.git-blame-ignore-revs

@@ -0,0 +1,8 @@
+# Reformat with black & clang-format
+02f34546c54ed62ded7f43c33cb203aa1dc5c88a
+
+# Refactor public_examples taxonomy
+8db3486cd7d559517dc2e275bc3477bebd31f262
+
+# Add more pre-commit hooks, add black to docs & jupyter
+62ffeefaf3266b01a3ad012545d0a82383398a47

.gitignore

@@ -7,35 +7,46 @@
 *.bin
 
 **/weights
-**/images
+
 **/checkpoints
 
 **/model
 **/data
 **/logs
+**/*ubyte*
+**/exe_cache
+**/tf_report_*
+**/images
 
 **/cifar-10-batches-bin
 
 *.pyc
 __pycache__
 .cache
+.ipu_cache
+
 *.csv
 *.json
+!codeowners.json
 *.log
 *.so
 *.lock
-report.txt
 archive.a
 vars.capnp
+debug.cbor
+profile.pop*
+report.txt
 
 *.onnx
 *.popef
+*.pvti
 
 .DS_Store
 
 .idea
 .project
 .pydevproject
+.hypothesis
 
 # Remove VIM temp files
 *.swp
@@ -56,3 +67,6 @@ nohup.*
 
 utils/triton_server/backends
 !vision/cnns/pytorch/tests/tritonserver/models/*/*/*.json
+
+# cppimport files
+.rendered.*

.pre-commit-config.yaml

@@ -2,22 +2,64 @@
 #        pre-commit autoupdate
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v3.3.0
+    rev: v4.4.0
     hooks:
+      - id: check-json
+      - id: check-yaml
+      - id: check-merge-conflict
+      - id: debug-statements
+      - id: check-added-large-files
       - id: no-commit-to-branch
         args: [--branch, master, --branch, main]
-  - repo: https://github.com/pre-commit/mirrors-autopep8
-    rev: v1.6.0  # v1.7.0 is not compatible with python3.6
+      - id: end-of-file-fixer
+      - id: mixed-line-ending
+        args: ["--fix=lf"]
+      - id: trailing-whitespace
+  - repo: https://github.com/psf/black
+    rev: 22.12.0
     hooks:
-      - id: autopep8
-        args: [--in-place, --list-fixes, --ignore, 'E251,E303,E402,E501,E701,E226,E24,W50,W690']
+      - id: black
+        args: [--line-length, "120"]
+      - id: black-jupyter
+        files: '.*\.ipynb'
+  - repo: https://github.com/asottile/blacken-docs
+    rev: 1.13.0
+    hooks:
+      - id: blacken-docs
+        additional_dependencies:
+          - black==22.12.0
+  - repo: https://github.com/ssciwr/clang-format-hook
+    rev: v15.0.6
+    hooks:
+      - id: clang-format
+        args: [-i]
+        # Exclude protobuff files
+        exclude: '^(.*pb\.h)|(.*pb\.cc)$'
   - repo: local
     hooks:
-    - id: copyright-header-check
-      name: Copyright header check
-      description: Ensures that files have the proper copyright line at the top
-      entry: python3 -m examples_utils test_copyright --amend --exclude_json utils/examples_tests/copyright_header_test_exclude.json
-      pass_filenames: false
-      language: python
-      additional_dependencies:
-        - 'git+https://github.com/graphcore/examples-utils.git@latest_stable'
+      - id: copyright-header-check
+        name: Copyright header check
+        description: Ensures that files have the proper copyright line at the top
+        entry: python3 -m examples_utils test_copyright --amend --exclude_json utils/examples_tests/copyright_header_test_exclude.json
+        pass_filenames: false
+        language: python
+        additional_dependencies:
+          - "git+https://github.com/graphcore/examples-utils@f8673d362fdc7dc77e1fee5f77cbcd81dd9e4a2e"
+      - id: trademark-linter
+        name: Trademark linter
+        description: Ensures that files have the proper trademark line.
+        entry: python3 -m utils.linters.trademark.trademark
+        language: python
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.1.0
+    hooks:
+      - id: codespell
+        args: [-I, utils/linters/codespell_ignore.txt]
+        exclude: |
+          (?x)^(
+            nlp/gpt2/pytorch/tokenizer/gpt2-merges-50256.txt |
+            nlp/gpt2/pytorch/tokenizer/gpt2-vocab-50256.json |
+            speech/fastpitch/pytorch/filelists/ljs_audio_text_train_filelist.txt |
+            speech/fastpitch/pytorch/filelists/ljs_mel_dur_pitch_text_train_filelist.txt |
+            gnn/nbfnet/pytorch_geometric/static/fb15k-237_entitymapping.txt
+          )$

LICENSE

@@ -19,4 +19,3 @@ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
-

README.md

@@ -10,13 +10,26 @@ To see what's new and easily filter applications by domain and framework, please
 
 For more detailed benchmark information, please visit our [Performance Results page](https://www.graphcore.ai/performance-results).
 
-> The code presented here requires using Poplar SDK 3.1.x, and has been tested using Ubuntu 20.04 and Python 3.8
+> The code presented here requires using Poplar SDK 3.2.x, and has been tested using Ubuntu 20.04 and Python 3.8
 
 Please install and enable the Poplar SDK following the instructions in the [Getting Started](https://docs.graphcore.ai/en/latest/getting-started.html#pod-system-getting-started-guides) guide for your IPU system.
 
+## Developer Resources
+- [Documentation](https://docs.graphcore.ai/en/latest/): Explore our software documentation, user guides, and technical notes
+- [Tutorials](https://github.com/graphcore/tutorials/tree/master/tutorials): Hands-on code tutorials, simple application and feature examples
+- [How-to Videos](https://www.graphcore.ai/resources/how-to-videos): Watch practical how-to videos and demos by Graphcore engineers
+- [Research Papers](https://www.graphcore.ai/resources/research-papers): Read publications from Graphcore's Research team and IPU innovators
+
+## Support
+
+If you encounter a problem or want to suggest an improvement to our example application please raise a Github issue, contact us at
+[support@graphcore.ai](mailto:support@graphcore.ai?subject=Applications%20Feedback), or get in touch through the #help channel of our slack community!
+
+[![Join our Slack Community](https://img.shields.io/badge/Slack-Join%20Graphcore's%20Community-blue?style=flat-square&logo=slack)](https://www.graphcore.ai/join-community)
+
 If you require POD128/256 setup and configuration for our applications, please contact [our engineering support](https://www.graphcore.ai/support).
 <br>
-<br>
+
 
 ## Repository contents
 1. [Computer Vision](#cv)
@@ -40,15 +53,13 @@ If you require POD128/256 setup and configuration for our applications, please c
 | Model | Domain | Type |Links |
 | ------- | ------- |------- | ------- |
 | ResNet  | Image Classification | Training & Inference | [TensorFlow 2](vision/cnns/tensorflow2/), [PyTorch](vision/cnns/pytorch/), [PyTorch Lightning](https://github.com/graphcore/pytorch-lightning-examples/tree/release/applications)|
-| ResNeXt  | Image Classification | Training & Inference | [PopART (Inference)](vision/resnext_inference/popart), [PyTorch (Inference)](vision/cnns/pytorch/inference)
 | EfficientNet | Image Classification | Training & Inference | [PyTorch](vision/cnns/pytorch/), [PyTorch Lightning](https://github.com/graphcore/pytorch-lightning-examples/tree/release/applications)|
 | MobileNetv3 | Image Classification | Training & Inference | [PyTorch](vision/cnns/pytorch/) |
-| ViT(Vision Transformer) | Image Classification | Training| [PyTorch](vision/vit/pytorch/), [Hugging Face Optimum](https://huggingface.co/Graphcore/vit-base-ipu) |
-| DINO | Image Classification | Training| [PyTorch](vision/dino/pytorch) |
+| ViT(Vision Transformer) | Image Classification | Training | [PyTorch](vision/vit/pytorch/), [Hugging Face Optimum](https://huggingface.co/Graphcore/vit-base-ipu) |
+| DINO | Image Classification | Training | [PyTorch](vision/dino/pytorch) |
 | Swin | Image Classification | Training | [PyTorch](vision/swin/pytorch)  |
 | MAE (Masked AutoEncoder) | Image Classification | Training | [PyTorch](vision/mae/pytorch)  |
 | Yolov4-P5 | Object Detection | Inference | [PyTorch](vision/yolo_v4/pytorch) |
-| Faster RCNN | Object Detection | Training & Inference | [PopART](vision/faster_rcnn/popart) |
 | EfficientDet | Object Detection | Inference | [TensorFlow 2](vision/efficientdet/tensorflow2) |
 | UNet (Medical) | Image segmentation | Training & Inference | [TensorFlow 2](vision/unet_medical/tensorflow2)  |
 | Neural Image Fields | Neural Radiance Fields | Training | [TensorFlow 2](vision/neural_image_fields/tensorflow2)  |
@@ -58,17 +69,18 @@ If you require POD128/256 setup and configuration for our applications, please c
 
 | Model | Domain | Type |Links |
 | ------- | ------- |------- | ------- |
-| BERT | NLP | Training & Inference | [PyTorch](nlp/bert/pytorch) , [PopART](nlp/bert/popart), [TensorFlow 2](nlp/bert/tensorflow2/), [PopXL](nlp/bert/popxl), [PaddlePaddle](https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/bert/static_ipu), [Hugging Face Optimum](https://huggingface.co/Graphcore/bert-large-ipu)|
-| Packed BERT | NLP | Training |[PyTorch](nlp/bert/pytorch), [PopART](nlp/bert/popart) |
+| BERT | NLP | Training & Inference | [PyTorch](nlp/bert/pytorch) , [TensorFlow 2](nlp/bert/tensorflow2/), [PopXL](nlp/bert/popxl), [PaddlePaddle](https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/bert/static_ipu), [Hugging Face Optimum](https://huggingface.co/Graphcore/bert-large-ipu)|
+| Packed BERT | NLP | Training |[PyTorch](nlp/bert/pytorch) |
 | GPT2 | NLP | Training |[PyTorch](nlp/gpt2/pytorch) , [Hugging Face Optimum](https://huggingface.co/Graphcore/gpt2-medium-ipu) |
 | GPTJ | NLP | Training |[PopXL](nlp/gpt_j/popxl)|
 | GPT3-2.7B | NLP | Training |[PopXL](nlp/gpt3_2.7B/popxl) |
+| GPT3-175B | NLP | Training |[PopXL](nlp/gpt3_175B/popxl) |
 | RoBERTa | NLP | Training | [Hugging Face Optimum](https://huggingface.co/Graphcore/roberta-large-ipu)|
 | DeBERTa | NLP | Training | [Hugging Face Optimum](https://huggingface.co/Graphcore/deberta-base-ipu)|
 | HuBERT | NLP | Training | [Hugging Face Optimum](https://huggingface.co/Graphcore/hubert-base-ipu)|
 | BART | NLP | Training | [Hugging Face Optimum](https://huggingface.co/Graphcore/bart-base-ipu)|
 | T5 | NLP | Training | [Hugging Face Optimum](https://huggingface.co/Graphcore/t5-small-ipu)|
-
+| Bloom | NLP | Inference |[PopXL](nlp/bloom/popxl) |
 
 <br>
 
@@ -77,11 +89,8 @@ If you require POD128/256 setup and configuration for our applications, please c
 
 | Model | Domain | Type |Links |
 | ------- | ------- |------- | ------- |
-| DeepVoice3 | TTS (TextToSpeech) | Training & Inference |[PopART](speech/deepvoice3/popart) |
-| FastSpeech2 | TTS(TextToSpeech) | Training & Inference | [TensorFlow 2](speech/fastspeech2/tensorflow2) |
 | Fastpitch | TTS (TextToSpeech) | Training | [PyTorch](speech/fastpitch/pytorch) |
-| Conformer | STT(SpeechToText) | Training & Inference | [PopART](speech/conformer/popart), [PyTorch](speech/conformer/pytorch)|
-| Transfomer Transducer | STT(SpeechToText) | Training & Inference | [PopART](speech/transformer_transducer/popart) |
+| Conformer | STT(SpeechToText) | Training & Inference | [PyTorch](speech/conformer/pytorch)|
 | Wav2Vec2 | STT(SpeechToText) | Training | [Hugging Face Optimum](https://huggingface.co/Graphcore/wav2vec2-base-ipu)|
 
 <br>
@@ -94,78 +103,51 @@ If you require POD128/256 setup and configuration for our applications, please c
 | CLIP | multimodal | Training |[PyTorch](multimodal/CLIP/pytorch)|
 | LXMERT | multimodal | Training | [Hugging Face Optimum](https://huggingface.co/Graphcore/lxmert-base-ipu)|
 | Frozen in time | multimodal | Training & Inference |[PyTorch](multimodal/frozen_in_time/pytorch)|
-| ruDalle (Preview) | multimodal | Inference |[PopXL](preview/multimodal/rudalle)|
 
 <br>
 
 ### <img width="25" src="https://user-images.githubusercontent.com/81682248/177357459-84ed7863-6477-4d8f-b63e-3db6c2ad405c.png"></a> Graph Neural Network <a name="gnn"></a>
 
 | Model | Domain | Type |Links |
 | ------- | ------- |------- | ------- |
-| MPNN (Message Passing Neural Networks) | GNN | Training & Inference | [TensorFlow 2](gnn/message_passing/tensorflow2) |
+| MPNN (Message Passing Neural Networks) | GNN | Training & Inference | [PyTorch Geometric](gnn/message_passing/pytorch_geometric) , [TensorFlow 2](gnn/message_passing/tensorflow2) |
 | Spektral GNN library with QM9 | GNN | Training | [TensorFlow 2](gnn/spektral/tensorflow2)  |
-| Cluster GCN | GNN | Training & Inference | [TensorFlow 2](gnn/cluster_gcn/tensorflow2) |
+| Cluster GCN | GNN | Training & Inference | [PyTorch Geometric](gnn/cluster_gcn/pytorch_geometric) , [TensorFlow 2](gnn/cluster_gcn/tensorflow2) |
 | TGN (Temporal Graph Networks) | GNN | Training | [PyTorch](gnn/tgn/pytorch) |
+| NBFNet | GNN | Training & Inference | [PyTorch Geometric](gnn/nbfnet/pytorch_geometric) |
+| SchNet | GNN | Training & Inference | [PyTorch Geometric](gnn/schnet/pytorch_geometric) |
+| GPS++ - OGB-LSC PCQM4Mv2 competition submission | GNN | Training & Inference | [TensorFlow 2](gnn/ogb_lsc_pcqm4mv2/tensorflow2) |
 
 <br>
 
 ### <img width="25" src="https://user-images.githubusercontent.com/81682248/177359725-f8b1c268-ddbb-41c5-a037-16168564cacc.png"></a> AI for Simulation <a name="simulation"></a>
 
 | Model | Domain | Type |Links |
 | ------- | ------- |------- | ------- |
-| DeepDriveMD | Biology (Protein folding) | Training | [TensorFlow 2](ai_for_simulation/deep_drive_md/tensorflow2)  |
 | Approximate Bayesian Computation (ABC) COVID-19 | Medical | Inference | [TensorFlow 2](ai_for_simulation/abc_covid_19/tensorflow2)  |
 
 
 <br>
 
-### <img width="25" src="https://user-images.githubusercontent.com/81682248/177373761-77d40785-5390-400b-ad9f-305f4fd54a05.png"></a> Sparsity <a name="sparsity"></a>
-
-| Model | Domain | Type |Links |
-| ------- | ------- |------- | ------- |
-| Block-Sparse library  | Sparsity | Training & Inference | [PopART](sparsity/block_sparse/popart)
-
-<br>
-
-### Miscellaneous <a name="miscellaneous"></a>
-| Model | Domain | Type |Links |
-| ------- | ------- |------- | ------- |
-| Monte Carlo Ray Tracing  | Graphics | Inference | [Poplar](miscellaneous/monte_carlo_ray_tracing/poplar) |
-
-<br>
-
-## Developer Resources
-- [Documentation](https://docs.graphcore.ai/en/latest/): Explore our software documentation, user guides, and technical notes
-- [Tutorials](https://github.com/graphcore/tutorials/tree/master/tutorials): Hands-on code tutorials, simple application and feature examples
-- [How-to Videos](https://www.graphcore.ai/resources/how-to-videos): Watch practical how-to videos and demos by Graphcore engineers
-- [Research Papers](https://www.graphcore.ai/resources/research-papers): Read publications from Graphcore's Research team and IPU innovators
-
-<br>
 
 ## Benchmarking tools
 To easily run the examples with tested and optimised configurations and to reproduce the performance shown on our [performance results page](https://www.graphcore.ai/performance-results), you can use the examples-utils benchmarking module, which comes with every example when you install its requirements. To use this simple, shared interface for almost any of the examples provided here, locate and look through the example's `benchmarks.yml` file and run:
 
-```python
+```bash
 python3 -m examples_utils benchmark --spec <path to benchmarks.yml file> --benchmark <name of benchmark>
 ```
 
 For more information on using the examples-utils benchmarking module, please refer to [the README](https://github.com/graphcore/examples-utils/blob/master/examples_utils/benchmarks/README.md).
 
 <br>
 
-## PopVision™ Tools
+## PopVision® Tools
 Visualise your code's inner workings with a user-friendly, graphical interface to optimise your machine learning models.
 
 [Download](https://www.graphcore.ai/developer/popvision-tools) PopVision to analyse IPU performance and utilisation.
 
 <br>
 
-## Support
-If you encounter a problem or want to suggest an improvement to our examples please raise a Github issue or contact us at
- [support@graphcore.ai](mailto:support@graphcore.ai?subject=General%20Feedback).
-
-<br>
-
 ## Utilities
 The [utils/](utils) folder contains utilities libraries and scripts that are used across the other code examples. This includes:
 
@@ -181,15 +163,31 @@ Unless otherwise specified by a LICENSE file in a subdirectory, the LICENSE refe
 
 ## Changelog
 
+<details>
+<summary>March 2023</summary>
+<br>
+
+*  Added this model below to reference models
+    *  GNN: NBFNet (PyTorch Geometric), SchNet (PyTorch Geometric), Cluster-GCN (PyTorch Geometric), GIN (PyTorch Geometric), GPS++ - OGB-LSC PCQM4Mv2 competition submission (TensorFlow 2)
+    *  NLP : GPT3_175B (PopXL), Bloom (PopXL)
+*  Removed all PopART applications, as well as the following:
+    * Miscellaneous: Monte-Carlo ray tracing
+    * AI for simulation: DeepDriveMD
+    * (Preview) Multimodel: ruDalle
+    * Speech: FastSpeech2
+    * Vision: ResNeXt inference
+* Moved the contents of the [Graphcore/tutorials](https://github.com/graphcore/tutorials) repository into this repository (PopART tutorials have also been removed)
+</details>
+
 <details>
 <summary>Dec 2022</summary>
 <br>
 
 *  Added this model below to reference models
     *  GNN: TGN (PyTorch)
 *  Deprecating all PopART applications. Support will be removed in the next release.
-*  Deprecated all TensorFlow 1 applications.
-*  Deprecated Ubuntu 18.04 support.
+*  Removed all TensorFlow 1 applications.
+*  Ubuntu 18.04 no longer supported.
 </details>
 
 <details>
@@ -250,14 +248,15 @@ Unless otherwise specified by a LICENSE file in a subdirectory, the LICENSE refe
 *  Added those models below to reference models
     *  Vision : miniDALL-E(PyTorch), Faster RCNN(PopART), UNet(TensorFlow 2), ResNet50(TensorFlow 2)
     *  NLP : BERT(TensorFlow 2)
-    *  Speech : FastSpeech2(TensorFlow 2), Transfomer Transducer(PopART), Conformer-Small(PyTorch)
+    *  Speech : FastSpeech2(TensorFlow 2), Transformer Transducer(PopART), Conformer-Small(PyTorch)
     *  GNN : TGN(TensorFlow 1), MPNN(TensorFlow 2)
 </details>
 
 <br>
 
 ## Connect with us
 <p align="center">
+  <a href="https://www.graphcore.ai/join-community"><img src="https://img.shields.io/badge/Slack-4A154B.svg?style=for-the-badge&logo=Slack&logoColor=white"/></a>
   <a href="https://twitter.com/graphcoreai"><img src="https://img.shields.io/badge/Twitter-1DA1F2.svg?style=for-the-badge&logo=Twitter&logoColor=white"/></a>
   <a href="https://www.linkedin.com/company/graphcore"><img src="https://img.shields.io/badge/LinkedIn-0A66C2.svg?style=for-the-badge&logo=LinkedIn&logoColor=white"/></a>
   <a href="http://www.facebook.com/pages/Graphcore/890447934394683"><img src="https://img.shields.io/badge/Facebook-1877F2.svg?style=for-the-badge&logo=Facebook&logoColor=white"/></a>