Hi
\nI am new to use TPU in Kaggle, can anyone suggest some good resource for understanding prepossessing part in case of TPU.
\nThanks
", "messages": [ { "id": 1221121, "postDate": "2021-02-28T17:24:29.793Z", "content": "@pandekp there are a few really great notebooks and links that I have used to understand TPU's that I have put together below. There are many other great resources out there, but these are the ones I found most useful in developing my TPU knowledge. Hope this helps!
\nTPU Basics
\n\nGreat TPU Notebooks built w/ Tensorflow
\n\nData Augmentation w/ TPU's
\n", "rawMarkdown": "@pandekp there are a few really great notebooks and links that I have used to understand TPU's that I have put together below. There are many other great resources out there, but these are the ones I found most useful in developing my TPU knowledge. Hope this helps!\n\n**TPU Basics**\n\n- [Getting Started with TPU's](https://www.kaggle.com/jessemostipak/getting-started-tpus-cassava-leaf-disease)\n\n- [TPU Docs](https://www.kaggle.com/docs/tpu)\n\n- [TFRecords Basics](https://www.kaggle.com/ryanholbrook/tfrecords-basics)\n\n**Great TPU Notebooks built w/ Tensorflow**\n\n- [dimitreoliveira's notebook](https://www.kaggle.com/dimitreoliveira/flower-classification-with-tpus-eda-and-baseline)\n\n- [Xhlulu's flower competition notebook](https://www.kaggle.com/xhlulu/flowers-tpu-concise-efficientnet-b7)\n\n**Data Augmentation w/ TPU's**\n\n- [TF Data Augmentation Docs](tensorflow.org/tutorials/images/data_augmentation)\n\n- [TF Image Docs](https://www.tensorflow.org/api_docs/python/tf/image)\n\n\n", "votes": 3 }, { "id": 1221050, "postDate": "2021-02-28T16:10:56.197Z", "content": "Hi
\nI am new to use TPU in Kaggle, can anyone suggest some good resource for understanding prepossessing part in case of TPU.
\nThanks
", "rawMarkdown": "Hi\n\nI am new to use TPU in Kaggle, can anyone suggest some good resource for understanding prepossessing part in case of TPU. \n\nThanks", "votes": 1 }, { "id": 1251422, "postDate": "2021-03-24T18:52:53.913Z", "content": "Here is a good resource from TensorFlow Core under the Keras section > Working with Preprocessing Layers and Use TPUs. If you have a Google account, you could run the notebook in Google Colab by clicking the \"Run In Google Colab\" button. Once you're there, you could click the \"Copy to Drive\" button to save a copy on your Google Drive. I like to have a copy myself, so that I could make changes to it to try out different things and add my own notes.
\nThere are a lot of tutorials and guides on TensorFlow. Hope this help.
", "rawMarkdown": "Here is a good resource from [TensorFlow Core](https://www.tensorflow.org/guide/keras/preprocessing_layers) under the Keras section > Working with Preprocessing Layers and [Use TPUs](https://www.tensorflow.org/guide/tpu). If you have a Google account, you could run the notebook in Google Colab by clicking the \"Run In Google Colab\" button. Once you're there, you could click the \"Copy to Drive\" button to save a copy on your Google Drive. I like to have a copy myself, so that I could make changes to it to try out different things and add my own notes. \n\nThere are a lot of tutorials and guides on [TensorFlow](https://www.tensorflow.org/). Hope this help. ", "votes": 2 }, { "id": 1251442, "postDate": "2021-03-24T19:11:11.760Z", "content": "@saukha Thanks for the information. Actually your TF notebook on Petals to Metal was very helpful for me, it helped me in understanding the basic of TPU. I will check your resourses.
\nThanks
", "rawMarkdown": "@saukha Thanks for the information. Actually your TF notebook on Petals to Metal was very helpful for me, it helped me in understanding the basic of TPU. I will check your resourses.\n\nThanks ", "replies": [ { "id": 1251602, "postDate": "2021-03-25T00:01:48.270Z", "content": "I'm glad to hear that.
", "rawMarkdown": "I'm glad to hear that. " } ] }, { "id": 1221132, "postDate": "2021-02-28T17:30:29.283Z", "content": "@brendanartley thankyou for sharing this resource with the community….
", "rawMarkdown": "@brendanartley thankyou for sharing this resource with the community...." } ], "comments": [ { "id": 1221121, "author_name": "Bartley", "author_url": "", "post_date": "2021-02-28T17:24:29.793000", "content": "@pandekp there are a few really great notebooks and links that I have used to understand TPU's that I have put together below. There are many other great resources out there, but these are the ones I found most useful in developing my TPU knowledge. Hope this helps!
\nTPU Basics
\n\nGreat TPU Notebooks built w/ Tensorflow
\n\nData Augmentation w/ TPU's
\n", "votes": 3, "replies": [] }, { "id": 1251422, "author_name": "Sau Kha", "author_url": "", "post_date": "2021-03-24T18:52:53.913000", "content": "Here is a good resource from TensorFlow Core under the Keras section > Working with Preprocessing Layers and Use TPUs. If you have a Google account, you could run the notebook in Google Colab by clicking the \"Run In Google Colab\" button. Once you're there, you could click the \"Copy to Drive\" button to save a copy on your Google Drive. I like to have a copy myself, so that I could make changes to it to try out different things and add my own notes.
\nThere are a lot of tutorials and guides on TensorFlow. Hope this help.
", "votes": 2, "replies": [] }, { "id": 1251442, "author_name": "Perceptron", "author_url": "", "post_date": "2021-03-24T19:11:11.760000", "content": "@saukha Thanks for the information. Actually your TF notebook on Petals to Metal was very helpful for me, it helped me in understanding the basic of TPU. I will check your resourses.
\nThanks
", "votes": 0, "replies": [ { "id": 1251602, "author_name": "Sau Kha", "author_url": "", "post_date": "2021-03-25T00:01:48.270000", "content": "I'm glad to hear that.
", "votes": 0, "replies": [] } ] }, { "id": 1221132, "author_name": "Perceptron", "author_url": "", "post_date": "2021-02-28T17:30:29.283000", "content": "@brendanartley thankyou for sharing this resource with the community….
", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "1221121": "@pandekp there are a few really great notebooks and links that I have used to understand TPU's that I have put together below. There are many other great resources out there, but these are the ones I found most useful in developing my TPU knowledge. Hope this helps!\n\n**TPU Basics**\n\n- [Getting Started with TPU's](https://www.kaggle.com/jessemostipak/getting-started-tpus-cassava-leaf-disease)\n\n- [TPU Docs](https://www.kaggle.com/docs/tpu)\n\n- [TFRecords Basics](https://www.kaggle.com/ryanholbrook/tfrecords-basics)\n\n**Great TPU Notebooks built w/ Tensorflow**\n\n- [dimitreoliveira's notebook](https://www.kaggle.com/dimitreoliveira/flower-classification-with-tpus-eda-and-baseline)\n\n- [Xhlulu's flower competition notebook](https://www.kaggle.com/xhlulu/flowers-tpu-concise-efficientnet-b7)\n\n**Data Augmentation w/ TPU's**\n\n- [TF Data Augmentation Docs](tensorflow.org/tutorials/images/data_augmentation)\n\n- [TF Image Docs](https://www.tensorflow.org/api_docs/python/tf/image)\n\n\n", "1221050": "Hi\n\nI am new to use TPU in Kaggle, can anyone suggest some good resource for understanding prepossessing part in case of TPU. \n\nThanks", "1251422": "Here is a good resource from [TensorFlow Core](https://www.tensorflow.org/guide/keras/preprocessing_layers) under the Keras section > Working with Preprocessing Layers and [Use TPUs](https://www.tensorflow.org/guide/tpu). If you have a Google account, you could run the notebook in Google Colab by clicking the \"Run In Google Colab\" button. Once you're there, you could click the \"Copy to Drive\" button to save a copy on your Google Drive. I like to have a copy myself, so that I could make changes to it to try out different things and add my own notes. \n\nThere are a lot of tutorials and guides on [TensorFlow](https://www.tensorflow.org/). Hope this help. ", "1251442": "@saukha Thanks for the information. Actually your TF notebook on Petals to Metal was very helpful for me, it helped me in understanding the basic of TPU. I will check your resourses.\n\nThanks ", "1221132": "@brendanartley thankyou for sharing this resource with the community...." } }