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4beb907 8b0ed14 57b839f 8b0ed14 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 | # Environment variables
# project id - replace with your GCP project id
PROJECT_ID=wagon-bootcamp-328205
# bucket name - replace with your GCP bucket name
BUCKET_NAME=wagon-data-737-sadriwala
# choose your region from https://cloud.google.com/storage/docs/locations#available_locations
REGION=europe-west1
set_project:
@gcloud config set project ${PROJECT_ID}
create_bucket:
@gsutil mb -l ${REGION} -p ${PROJECT_ID} gs://${BUCKET_NAME}
# path to the file to upload to GCP (the path to the file should be absolute or should match the directory where the make command is ran)
# replace with your local path to the `train_1k.csv` and make sure to put the path between quotes
LOCAL_PATH="/mnt/d/data-science/le-wagon/autotab/data"
# bucket directory in which to store the uploaded file (`data` is an arbitrary name that we choose to use)
BUCKET_FOLDER=data
# name for the uploaded file inside of the bucket (we choose not to rename the file that we upload)
#BUCKET_FILE_NAME=$(shell basename ${LOCAL_PATH})
BUCKET_FILE_NAME=.
##### Machine configuration - - - - - - - - - - - - - - - -
REGION=europe-west1
PYTHON_VERSION=3.7
FRAMEWORK=TensorFlow
RUNTIME_VERSION=2.6
##### Package params - - - - - - - - - - - - - - - - - - -
PACKAGE_NAME=autotab
FILENAME=TabCNN
##### Job - - - - - - - - - - - - - - - - - - - - - - - - -
JOB_NAME=autotab_$(shell date +'%Y%m%d_%H%M%S')
run_locally:
@python -m ${PACKAGE_NAME}.${FILENAME}
gcp_submit_training:
gcloud ai-platform jobs submit training ${JOB_NAME} \
--job-dir gs://${BUCKET_NAME}/${BUCKET_TRAINING_FOLDER} \
--package-path ${PACKAGE_NAME} \
--module-name ${PACKAGE_NAME}.${FILENAME} \
--python-version=${PYTHON_VERSION} \
--runtime-version=${RUNTIME_VERSION} \
--region ${REGION} \
--stream-logs
upload_data:
# @gsutil cp train_1k.csv gs://wagon-ml-my-bucket-name/data/train_1k.csv
# @gsutil -m cp -r ${LOCAL_PATH} gs://${BUCKET_NAME}/${BUCKET_FOLDER}/${BUCKET_FILE_NAME}
@gsutil -m cp -r ${LOCAL_PATH} gs://${BUCKET_NAME}
# ----------------------------------
# INSTALL & TEST
# ----------------------------------
first_npz:
@python autotab/TabDataReprGen.py
run_first_model:
@python autotab/TabCNN.py
install_requirements:
@pip install -r requirements.txt
check_code:
@flake8 scripts/* autotab/*.py
black:
@black scripts/* autotab/*.py
test:
@coverage run -m pytest tests/*.py
@coverage report -m --omit="${VIRTUAL_ENV}/lib/python*"
ftest:
@Write me
clean:
@rm -f */version.txt
@rm -f .coverage
@rm -fr */__pycache__ */*.pyc __pycache__
@rm -fr build dist
@rm -fr autotab-*.dist-info
@rm -fr autotab.egg-info
install:
@pip install . -U
all: clean install test black check_code
count_lines:
@find ./ -name '*.py' -exec wc -l {} \; | sort -n| awk \
'{printf "%4s %s\n", $$1, $$2}{s+=$$0}END{print s}'
@echo ''
@find ./scripts -name '*-*' -exec wc -l {} \; | sort -n| awk \
'{printf "%4s %s\n", $$1, $$2}{s+=$$0}END{print s}'
@echo ''
@find ./tests -name '*.py' -exec wc -l {} \; | sort -n| awk \
'{printf "%4s %s\n", $$1, $$2}{s+=$$0}END{print s}'
@echo ''
# ----------------------------------
# UPLOAD PACKAGE TO PYPI
# ----------------------------------
PYPI_USERNAME=<AUTHOR>
build:
@python setup.py sdist bdist_wheel
pypi_test:
@twine upload -r testpypi dist/* -u $(PYPI_USERNAME)
pypi:
@twine upload dist/* -u $(PYPI_USERNAME)
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