automatic import of python-ktrainopeneuler20.03

3 files changed, 12 insertions, 5 deletions

diff --git a/.gitignore b/.gitignore
index 12fb72c..8b48d04 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,2 @@
 /ktrain-0.35.1.tar.gz
+/ktrain-0.36.0.tar.gz
diff --git a/python-ktrain.spec b/python-ktrain.spec
index 0286696..a7a04d0 100644
--- a/python-ktrain.spec
+++ b/python-ktrain.spec
@@ -1,11 +1,11 @@
 %global _empty_manifest_terminate_build 0
 Name:		python-ktrain
-Version:	0.35.1
+Version:	0.36.0
 Release:	1
 Summary:	ktrain is a wrapper for TensorFlow Keras that makes deep learning and AI more accessible and easier to apply
 License:	Apache License 2.0
 URL:		https://github.com/amaiya/ktrain
-Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/32/fd/8b2106a02b9237111baf21fb06662ed7acb24f1e5058bfd8d6fd37463cd6/ktrain-0.35.1.tar.gz
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/18/26/cf5705c8649557779a978eae92edda57c6ae064636772fe2b15fd22e95b7/ktrain-0.36.0.tar.gz
 BuildArch:	noarch
 
 
@@ -31,6 +31,7 @@ BuildArch:	noarch
      - **Speech Transcription**: Extract text from audio files <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/speech_transcription_example.ipynb)]</sup></sub>
      - **Universal Information Extraction**:  extract any kind of information from documents by simply phrasing it in the form of a question <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/master/examples/text/qa_information_extraction.ipynb)]</sup></sub>
      - **Keyphrase Extraction**:  extract keywords from documents <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/keyword_extraction_example.ipynb)]</sup></sub>
+     - **Sentiment Analysis**: easy-to-use wrapper to pretrained sentiment analysis <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/sentiment_analysis_example.ipynb)]</sup
      - **Generative AI with GPT**: Provide instructions to a lightweight ChatGPT-like model running on your own own machine to solve various tasks. Model was fine-tuned on the [Alpaca](https://github.com/tatsu-lab/stanford_alpaca) instruction dataset ([CC By NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/deed.en_GB)) <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/generative_ai_example.ipynb)]</sup>
   - `vision` data:
     - **image classification** (e.g., [ResNet](https://arxiv.org/abs/1512.03385), [Wide ResNet](https://arxiv.org/abs/1605.07146), [Inception](https://www.cs.unc.edu/~wliu/papers/GoogLeNet.pdf)) <sub><sup>[[example notebook](https://colab.research.google.com/drive/1WipQJUPL7zqyvLT10yekxf_HNMXDDtyR)]</sup></sub>
@@ -268,6 +269,7 @@ can be used out-of-the-box **without** having TensorFlow installed, as summarize
 | [Speech Transcription](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/speech_transcription_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Image Captioning](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/vision/image_captioning_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Object Detection](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/vision/object_detection_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
+| [Sentiment Analysis](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/sentiment_analysis_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Topic Modeling](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/master/tutorials/tutorial-05-learning_from_unlabeled_text_data.ipynb) (sklearn)  |  ❌  | ❌  | ✅  |
 | [Keyphrase Extraction](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/keyword_extraction_example.ipynb) (textblob/nltk/sklearn)   |  ❌  | ❌  | ✅  |
 As noted above, end-to-end question-answering and information extraction in **ktrain** can be used with either TensorFlow (using `framework='tf'`) or PyTorch (using `framework='pt'`).
@@ -329,6 +331,7 @@ BuildRequires:	python3-pip
      - **Speech Transcription**: Extract text from audio files <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/speech_transcription_example.ipynb)]</sup></sub>
      - **Universal Information Extraction**:  extract any kind of information from documents by simply phrasing it in the form of a question <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/master/examples/text/qa_information_extraction.ipynb)]</sup></sub>
      - **Keyphrase Extraction**:  extract keywords from documents <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/keyword_extraction_example.ipynb)]</sup></sub>
+     - **Sentiment Analysis**: easy-to-use wrapper to pretrained sentiment analysis <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/sentiment_analysis_example.ipynb)]</sup
      - **Generative AI with GPT**: Provide instructions to a lightweight ChatGPT-like model running on your own own machine to solve various tasks. Model was fine-tuned on the [Alpaca](https://github.com/tatsu-lab/stanford_alpaca) instruction dataset ([CC By NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/deed.en_GB)) <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/generative_ai_example.ipynb)]</sup>
   - `vision` data:
     - **image classification** (e.g., [ResNet](https://arxiv.org/abs/1512.03385), [Wide ResNet](https://arxiv.org/abs/1605.07146), [Inception](https://www.cs.unc.edu/~wliu/papers/GoogLeNet.pdf)) <sub><sup>[[example notebook](https://colab.research.google.com/drive/1WipQJUPL7zqyvLT10yekxf_HNMXDDtyR)]</sup></sub>
@@ -566,6 +569,7 @@ can be used out-of-the-box **without** having TensorFlow installed, as summarize
 | [Speech Transcription](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/speech_transcription_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Image Captioning](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/vision/image_captioning_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Object Detection](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/vision/object_detection_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
+| [Sentiment Analysis](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/sentiment_analysis_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Topic Modeling](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/master/tutorials/tutorial-05-learning_from_unlabeled_text_data.ipynb) (sklearn)  |  ❌  | ❌  | ✅  |
 | [Keyphrase Extraction](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/keyword_extraction_example.ipynb) (textblob/nltk/sklearn)   |  ❌  | ❌  | ✅  |
 As noted above, end-to-end question-answering and information extraction in **ktrain** can be used with either TensorFlow (using `framework='tf'`) or PyTorch (using `framework='pt'`).
@@ -624,6 +628,7 @@ Provides:	python3-ktrain-doc
      - **Speech Transcription**: Extract text from audio files <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/speech_transcription_example.ipynb)]</sup></sub>
      - **Universal Information Extraction**:  extract any kind of information from documents by simply phrasing it in the form of a question <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/master/examples/text/qa_information_extraction.ipynb)]</sup></sub>
      - **Keyphrase Extraction**:  extract keywords from documents <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/keyword_extraction_example.ipynb)]</sup></sub>
+     - **Sentiment Analysis**: easy-to-use wrapper to pretrained sentiment analysis <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/sentiment_analysis_example.ipynb)]</sup
      - **Generative AI with GPT**: Provide instructions to a lightweight ChatGPT-like model running on your own own machine to solve various tasks. Model was fine-tuned on the [Alpaca](https://github.com/tatsu-lab/stanford_alpaca) instruction dataset ([CC By NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/deed.en_GB)) <sub><sup>[[example notebook](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/generative_ai_example.ipynb)]</sup>
   - `vision` data:
     - **image classification** (e.g., [ResNet](https://arxiv.org/abs/1512.03385), [Wide ResNet](https://arxiv.org/abs/1605.07146), [Inception](https://www.cs.unc.edu/~wliu/papers/GoogLeNet.pdf)) <sub><sup>[[example notebook](https://colab.research.google.com/drive/1WipQJUPL7zqyvLT10yekxf_HNMXDDtyR)]</sup></sub>
@@ -861,6 +866,7 @@ can be used out-of-the-box **without** having TensorFlow installed, as summarize
 | [Speech Transcription](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/speech_transcription_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Image Captioning](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/vision/image_captioning_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Object Detection](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/vision/object_detection_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
+| [Sentiment Analysis](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/sentiment_analysis_example.ipynb) (pretrained)     |  ❌  | ✅  |❌   |
 | [Topic Modeling](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/master/tutorials/tutorial-05-learning_from_unlabeled_text_data.ipynb) (sklearn)  |  ❌  | ❌  | ✅  |
 | [Keyphrase Extraction](https://nbviewer.jupyter.org/github/amaiya/ktrain/blob/develop/examples/text/keyword_extraction_example.ipynb) (textblob/nltk/sklearn)   |  ❌  | ❌  | ✅  |
 As noted above, end-to-end question-answering and information extraction in **ktrain** can be used with either TensorFlow (using `framework='tf'`) or PyTorch (using `framework='pt'`).
@@ -895,7 +901,7 @@ The following software/libraries should be installed:
 - [fastprogress](https://github.com/fastai/fastprogress)
 
 %prep
-%autosetup -n ktrain-0.35.1
+%autosetup -n ktrain-0.36.0
 
 %build
 %py3_build
@@ -935,5 +941,5 @@ mv %{buildroot}/doclist.lst .
 %{_docdir}/*
 
 %changelog
-* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.35.1-1
+* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 0.36.0-1
 - Package Spec generated
diff --git a/sources b/sources
index 5abc6e3..a4504f2 100644
--- a/sources
+++ b/sources
@@ -1 +1 @@
-f6f26341b2c81e00bcec0e8135fa3e91  ktrain-0.35.1.tar.gz
+cf506947abea544b87af27035e7a2593  ktrain-0.36.0.tar.gz