# AryaXai-Backtrace
Backtrace module for Generating Explainability on Deep learning models using TensorFlow / Pytorch
# Backtrace Module
[](LICENSE)
## Overview
The Backtrace Module is a powerful and patent-pending algorithm developed by AryaXAI for enhancing the explainability of AI models, particularly in the context of complex techniques like deep learning.
## Features
- **Explainability:** Gain deep insights into your AI models by using the Backtrace algorithm, providing multiple explanations for their decisions.
- **Consistency:** Ensure consistent and accurate explanations across different scenarios and use cases.
- **Mission-Critical Support:** Tailored for mission-critical AI use cases where transparency is paramount.
## Installation
To integrate the Backtrace Module into your project, follow these simple steps:
```bash
pip install dl-backtrace
```
usage for Tensoflow based models
```python
from dl_backtrace.tf_backtrace import Backtrace as B
from dl_backtrace.tf_backtrace import contrast as UC
from dl_backtrace.tf_backtrace import prop as UP
from dl_backtrace.tf_backtrace import activation_master
```
usage for Pytorch based models
```python
from dl_backtrace.pytorch_backtrace import Backtrace as B
from dl_backtrace.pytorch_backtrace import contrast as UC
from dl_backtrace.pytorch_backtrace import prop as UP
from dl_backtrace.pytorch_backtrace import activation_master
```
## Example Notebooks
| Name | Link |
|-------------|-------------------------------|
| Tensorflow Backtrace Tabular Dataset | [Colab Link](https://colab.research.google.com/drive/1A4J-wgShD7M_pUmsqbnI8BD3hE43dT8o?usp=sharing) |
| Tensorflow Backtrace Textual Dataset | [Colab Link](https://colab.research.google.com/drive/1zT_K8mHdzyfQe_LG576qwiBqw8o6LRQH?usp=sharing) |
| Tensorflow Backtrace Image Dataset | [Colab Link](https://colab.research.google.com/drive/1KbLtcjYDrPQvG6oJj1wmHdiWxRrtKNrV?usp=sharing) |
| Pytorch Backtrace Tabular Dataset | [Colab Link](https://colab.research.google.com/drive/1Z4UJNFd83dwXBMM0cmiNYEjh6xhRtQA_?usp=sharing) |
| Pytorch Backtrace Image Dataset | [Colab Link](https://colab.research.google.com/drive/14XKwCsS9IZep2AlDDYfavnVRNz8_b-jM?usp=sharing) |
For more detailed examples and use cases, check out our documentation.
## Supported Layers and Future Work
- [x] Dense (Fully Connected) Layer
- [x] Convolutional Layer (Conv2D)
- [x] Reshape Layer
- [x] Flatten Layer
- [x] Global Average Pooling 2D Layer
- [x] Max Pooling 2D Layer
- [x] Average Pooling 2D Layer
- [x] Concatenate Layer
- [x] Add Layer
- [x] Long Short-Term Memory (LSTM) Layer
- [x] Batch Normalisation Layer
- [x] Dropout Layer
- [ ] Embedding Layer
- [ ] Other Custom Layers
## Getting Started
If you are new to Backtrace, head over to our Getting Started Guide to quickly set up and use the module in your projects.
## Contributing
We welcome contributions from the community. To contribute, please follow our Contribution Guidelines.
## License
This project is licensed under the MIT License - see the LICENSE file for details.
## Contact
For any inquiries or support, please contact AryaXAI Support.
Raw data
{
"_id": null,
"home_page": "https://xai.arya.ai/docs/introduction",
"name": "dl-backtrace",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.0",
"maintainer_email": "",
"keywords": "aryaxai deep learning backtrace,ML observability",
"author": "",
"author_email": "",
"download_url": "https://files.pythonhosted.org/packages/2c/70/777a42b4104b8875af88f49e9e0ca5c5306924de0c7639de77c5309da47d/dl_backtrace-0.0.14.tar.gz",
"platform": null,
"description": "# AryaXai-Backtrace\nBacktrace module for Generating Explainability on Deep learning models using TensorFlow / Pytorch\n\n# Backtrace Module\n[](LICENSE)\n\n## Overview\n\nThe Backtrace Module is a powerful and patent-pending algorithm developed by AryaXAI for enhancing the explainability of AI models, particularly in the context of complex techniques like deep learning.\n\n## Features\n\n- **Explainability:** Gain deep insights into your AI models by using the Backtrace algorithm, providing multiple explanations for their decisions.\n\n- **Consistency:** Ensure consistent and accurate explanations across different scenarios and use cases.\n\n- **Mission-Critical Support:** Tailored for mission-critical AI use cases where transparency is paramount.\n\n## Installation\n\nTo integrate the Backtrace Module into your project, follow these simple steps:\n\n```bash\npip install dl-backtrace\n```\n\nusage for Tensoflow based models\n\n```python\nfrom dl_backtrace.tf_backtrace import Backtrace as B\nfrom dl_backtrace.tf_backtrace import contrast as UC\nfrom dl_backtrace.tf_backtrace import prop as UP\nfrom dl_backtrace.tf_backtrace import activation_master\n```\n\nusage for Pytorch based models\n\n```python\nfrom dl_backtrace.pytorch_backtrace import Backtrace as B\nfrom dl_backtrace.pytorch_backtrace import contrast as UC\nfrom dl_backtrace.pytorch_backtrace import prop as UP\nfrom dl_backtrace.pytorch_backtrace import activation_master\n```\n\n## Example Notebooks\n\n| Name | Link |\n|-------------|-------------------------------|\n| Tensorflow Backtrace Tabular Dataset | [Colab Link](https://colab.research.google.com/drive/1A4J-wgShD7M_pUmsqbnI8BD3hE43dT8o?usp=sharing) |\n| Tensorflow Backtrace Textual Dataset | [Colab Link](https://colab.research.google.com/drive/1zT_K8mHdzyfQe_LG576qwiBqw8o6LRQH?usp=sharing) |\n| Tensorflow Backtrace Image Dataset | [Colab Link](https://colab.research.google.com/drive/1KbLtcjYDrPQvG6oJj1wmHdiWxRrtKNrV?usp=sharing) |\n| Pytorch Backtrace Tabular Dataset | [Colab Link](https://colab.research.google.com/drive/1Z4UJNFd83dwXBMM0cmiNYEjh6xhRtQA_?usp=sharing) |\n| Pytorch Backtrace Image Dataset | [Colab Link](https://colab.research.google.com/drive/14XKwCsS9IZep2AlDDYfavnVRNz8_b-jM?usp=sharing) |\n\n\nFor more detailed examples and use cases, check out our documentation.\n\n## Supported Layers and Future Work\n- [x] Dense (Fully Connected) Layer\n- [x] Convolutional Layer (Conv2D)\n- [x] Reshape Layer\n- [x] Flatten Layer\n- [x] Global Average Pooling 2D Layer\n- [x] Max Pooling 2D Layer\n- [x] Average Pooling 2D Layer\n- [x] Concatenate Layer\n- [x] Add Layer\n- [x] Long Short-Term Memory (LSTM) Layer\n- [x] Batch Normalisation Layer\n- [x] Dropout Layer\n- [ ] Embedding Layer\n- [ ] Other Custom Layers\n\n\n## Getting Started\nIf you are new to Backtrace, head over to our Getting Started Guide to quickly set up and use the module in your projects.\n\n## Contributing\nWe welcome contributions from the community. To contribute, please follow our Contribution Guidelines.\n\n## License\nThis project is licensed under the MIT License - see the LICENSE file for details.\n\n## Contact\nFor any inquiries or support, please contact AryaXAI Support.\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "A python SDK for Deep Learning Backtrace",
"version": "0.0.14",
"project_urls": {
"Homepage": "https://xai.arya.ai/docs/introduction"
},
"split_keywords": [
"aryaxai deep learning backtrace",
"ml observability"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "3f6232402e2f402666974143d4bf4a9b12e854efbf7fe2a9eef64c20a2b61b2e",
"md5": "7006080f0a58b05bb27d35d777dab050",
"sha256": "b54f76ba1e4526aaaf95dfdbcf4eccca8135d3756f584fb996b7228a9dd56a30"
},
"downloads": -1,
"filename": "dl_backtrace-0.0.14-py3-none-any.whl",
"has_sig": false,
"md5_digest": "7006080f0a58b05bb27d35d777dab050",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.0",
"size": 35228,
"upload_time": "2023-12-07T08:41:01",
"upload_time_iso_8601": "2023-12-07T08:41:01.917014Z",
"url": "https://files.pythonhosted.org/packages/3f/62/32402e2f402666974143d4bf4a9b12e854efbf7fe2a9eef64c20a2b61b2e/dl_backtrace-0.0.14-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "2c70777a42b4104b8875af88f49e9e0ca5c5306924de0c7639de77c5309da47d",
"md5": "b8333493bffa78468365cf35487998c7",
"sha256": "e2d0ba54ef3c142e241f5d0ed53e42bd22ebbf8b0e900c33f3619577c86fb68a"
},
"downloads": -1,
"filename": "dl_backtrace-0.0.14.tar.gz",
"has_sig": false,
"md5_digest": "b8333493bffa78468365cf35487998c7",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.0",
"size": 31053,
"upload_time": "2023-12-07T08:41:03",
"upload_time_iso_8601": "2023-12-07T08:41:03.234540Z",
"url": "https://files.pythonhosted.org/packages/2c/70/777a42b4104b8875af88f49e9e0ca5c5306924de0c7639de77c5309da47d/dl_backtrace-0.0.14.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-12-07 08:41:03",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "dl-backtrace"
}
JSON