{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"## TPU Based Model for Cassava Leaf Disease Classification\nI created the following notebook demonstrating how you can train on TPUs and run inference.\n\nThis was done for a competition submission in the [Cassava Leaf Disease Classification competition](https://www.kaggle.com/c/cassava-leaf-disease-classification)<br> Since this is a code competition with a hidden test set, internet and TPUs cannot be enabled on the submission notebook. Therefore TPUs are only available for training models.\n\nI started with the notebook [Jesse](https://www.kaggle.com/jessemostipak) wrote [Getting Started: TPUs + Cassava Leaf Disease](https://www.kaggle.com/jessemostipak/getting-started-tpus-cassava-leaf-disease) this is the basis for the model I trained.\n\nAt the end of this notebook in my copy I added `model.save('<yourModelName>.h5')`. <br>\nI then created a new [dataset](https://www.kaggle.com/peretzcohen/cassavaleafdiseasetpumodel) using the output of the notebook, the output is the model that was trained on TPUs.\n\nFor the next part I referenced the strategy and code of [Devon](https://www.kaggle.com/devonstanfield) in the notebook [cassava-infer](https://www.kaggle.com/devonstanfield/cassava-infer). <br> The strategy was to utilize my previously generated model and create a submission file for the competition.\n\nIn the new notebook, in order to submit to the competition, ensure that the Accelerator and Internet are disabled as seen in the screenshot below.\n\nHappy coding!\n\n\n![TPU-based-notebook.png](attachment:2e51c1c7-ba19-484d-b42d-63e2444c3aee.png)","metadata":{},"attachments":{"2e51c1c7-ba19-484d-b42d-63e2444c3aee.png":{"image/png":"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"}}},{"cell_type":"code","source":"import os\nimport tensorflow as tf\nimport tensorflow_hub as hub\nimport numpy as np\nimport pandas as pd","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model = tf.keras.models.load_model('../input/cassavaleafdiseasetpumodel/leafKnowledge.h5')\n    \n","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"AUTO = tf.data.experimental.AUTOTUNE\nBATCH_SIZE = 32\nIMAGE_SIZE = [512, 512]\n","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def _parse_function(proto):\n    # feature_description needs to be defined since datasets use graph-execution\n    # - its used to build their shape and type signature\n    feature_description = {\n        'image': tf.io.FixedLenFeature([], tf.string, default_value=''),\n        'image_name': tf.io.FixedLenFeature([], tf.string, default_value=''),\n        'target': tf.io.FixedLenFeature([], tf.int64, default_value=-1)\n    }\n\n    parsed_features = tf.io.parse_single_example(proto, feature_description)\n    image = tf.image.decode_jpeg(parsed_features['image'], channels=3)\n    image = tf.cast(image, tf.float32) # :: [0.0, 255.0]\n    image = tf.reshape(image, [*IMAGE_SIZE, 3])\n    target = tf.one_hot(parsed_features['target'], depth=5)\n    image_id = parsed_features['image_name']\n    return image, target, image_id\n\ndef _preprocess_fn(image, label, image_id):\n    image = image / 255.0\n    image = tf.image.resize(image, (224, 224))\n    label = tf.concat([label, [0]], axis=0)\n    return image, label, image_id","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def load_dataset(tfrecords_fnames):\n    raw_ds = tf.data.TFRecordDataset(tfrecords_fnames, num_parallel_reads=AUTO)\n    parsed_ds = raw_ds.map(_parse_function, num_parallel_calls=AUTO)\n    parsed_ds = parsed_ds.map(_preprocess_fn, num_parallel_calls=AUTO)\n    return parsed_ds\ndef build_valid_ds(valid_fnames):\n    ds = load_dataset(valid_fnames)\n    ds = ds.batch(BATCH_SIZE).prefetch(AUTO)\n    return ds\nTEST_PATH = '../input/cassava-leaf-disease-classification/test_tfrecords/'\nvalid_fnames = [TEST_PATH + fname for fname in os.listdir(TEST_PATH)]\ntest_ds = build_valid_ds(valid_fnames)\npreds = model.predict(test_ds)\nlabels = tf.argmax(preds, axis=-1)\nlabels = labels.numpy()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_ds = build_valid_ds(valid_fnames)\nnames = []\nfor item in test_ds:\n    names.append(item[2].numpy())\nnames = np.concatenate(names)\nnames = [name.decode() for name in names]\nsubmission_df = pd.DataFrame({'image_id':names, 'label':labels})\nsubmission_df.to_csv(\"submission.csv\", index=False)\n!head submission.csv","metadata":{"trusted":true},"execution_count":null,"outputs":[]}]}