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travis test links fix readme Public Release v1.0
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| { | ||
| "projects": { | ||
| "default": "alzheimersai-2121" | ||
| } | ||
| } |
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| venv/ | ||
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| *.pyc | ||
| __pycache__/ | ||
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| instance/ | ||
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| .pytest_cache/ | ||
| .coverage | ||
| htmlcov/ | ||
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| dist/ | ||
| build/ | ||
| *.egg-info/ | ||
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| .vscode/ | ||
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| page_design/ | ||
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| .firebase/ | ||
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| firebase-debug.log | ||
| node_modules/ | ||
| functions/node_modules/ | ||
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| package-lock.json | ||
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| *.pth | ||
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| static/assets/usr/* | ||
| !.keep | ||
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| server/src/templates/usr_data/* | ||
| !.keep | ||
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| export.pkl |
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| matrix: | ||
| include: | ||
| - language: generic | ||
| python: "3.7" | ||
| node_js: "12.12.0" | ||
| services: docker | ||
| env: | ||
| - GCP_PROJECT_ID=alzheimersai-2121 | ||
| - IMAGE=gcr.io/alzheimersai-2121/alzheimersai | ||
| - CLOUD_RUN_SERVICE=alzheimersai | ||
| - CLOUD_RUN_REGION=us-central1 | ||
| - CLOUDSDK_CORE_DISABLE_PROMPTS=1 # prevent gcloud from prompting | ||
| before_install: | ||
| - nvm install node | ||
| - npm i -g firebase-tools | ||
| - pip install gdown --user | ||
| - python travis_builder.py | ||
| - openssl aes-256-cbc -K $encrypted_98d237b7dbf4_key -iv $encrypted_98d237b7dbf4_iv -in google-key.json.enc -out google-key.json -d | ||
| - curl https://sdk.cloud.google.com | bash > /dev/null | ||
| - source "$HOME/google-cloud-sdk/path.bash.inc" | ||
| - gcloud auth activate-service-account --key-file=google-key.json | ||
| - gcloud auth configure-docker # enable "docker push" to gcr | ||
| - gcloud config set project "${GCP_PROJECT_ID}" | ||
| - gcloud config set builds/use_kaniko True | ||
| - gcloud components install beta # until Cloud Run is generally available (GA) | ||
| install: true | ||
| script: | ||
| - | | ||
| set -ex; | ||
| docker build -t "${IMAGE}:${TRAVIS_COMMIT}" ./server && \ | ||
| docker push "${IMAGE}:${TRAVIS_COMMIT}" && \ | ||
| gcloud beta run deploy "${CLOUD_RUN_SERVICE}" --memory=1Gi \ | ||
| --image="${IMAGE}:${TRAVIS_COMMIT}" \ | ||
| --platform=managed \ | ||
| --region="${CLOUD_RUN_REGION}" \ | ||
| --allow-unauthenticated; | ||
| set +x | ||
| deploy: | ||
| provider: firebase | ||
| token: | ||
| secure: "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" |
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6
AI/NeuralZ-training/.ipynb_checkpoints/Untitled-checkpoint.ipynb
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| { | ||
| "cells": [], | ||
| "metadata": {}, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 4 | ||
| } |
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AI/NeuralZ-training/.ipynb_checkpoints/Untitled1-checkpoint.ipynb
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from fastai.vision import *\n", | ||
| "import numpy as np\n", | ||
| "import pandas as pd" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "path = Path('../data/train')\n", | ||
| "path.ls()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "np.random.seed(42)\n", | ||
| "data = ImageDataBunch.from_folder(path, train=\".\", valid_pct=0.2,\n", | ||
| " ds_tfms=get_transforms(), size=128, num_workers=4).normalize(imagenet_stats)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "data.classes" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "data.classes, data.c, len(data.train_ds), len(data.valid_ds)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "learn = cnn_learner(data, models.resnet101, metrics=error_rate)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "learn.fit_one_cycle(4)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "learn.save('stage-1')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.7.6" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 4 | ||
| } |
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6
AI/NeuralZ-training/.ipynb_checkpoints/Untitled2-checkpoint.ipynb
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,6 @@ | ||
| { | ||
| "cells": [], | ||
| "metadata": {}, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 4 | ||
| } |
6 changes: 6 additions & 0 deletions
6
AI/NeuralZ-training/.ipynb_checkpoints/Untitled3-checkpoint.ipynb
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,6 @@ | ||
| { | ||
| "cells": [], | ||
| "metadata": {}, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 4 | ||
| } |
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AI/NeuralZ-training/.ipynb_checkpoints/Untitled4-checkpoint.ipynb
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 46, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from fastai.vision import *\n", | ||
| "import pandas as pd\n", | ||
| "import numpy as np\n", | ||
| "import torch" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 47, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "path = Path('../data/train')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 48, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "[WindowsPath('../data/train/MildDemented'),\n", | ||
| " WindowsPath('../data/train/models'),\n", | ||
| " WindowsPath('../data/train/ModerateDemented'),\n", | ||
| " WindowsPath('../data/train/NonDemented'),\n", | ||
| " WindowsPath('../data/train/VeryMildDemented')]" | ||
| ] | ||
| }, | ||
| "execution_count": 48, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "path.ls()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "np.random.seed(42)\n", | ||
| "data = ImageDataBunch.from_folder(path, train=\".\", valid_pct=0.2,\n", | ||
| " size=128, num_workers=4).normalize(imagenet_stats)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "data.classes" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "data.classes, data.c, len(data.train_ds), len(data.valid_ds)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "learn = cnn_learner(data, models.resnet101, metrics=error_rate)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "learn.fit_one_cycle(4)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "learn.save('stage-1') # Save the first stage of the model\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3.7.7 64-bit ('python36': conda)", | ||
| "language": "python", | ||
| "name": "python37764bitpython36condadac793e125124000a42e65e438db1e77" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.7.7" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 4 | ||
| } |
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