53 lines
2.2 KiB
YAML
53 lines
2.2 KiB
YAML
# name: Replace with any name for your model
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# description: Replace with any description for your model
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# version: Replace with any version of your model
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# gpus: Replace with the number of gpus to be used in
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# training your model
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# cpus: Replace with the number of cpus to be used in
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# training your model
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# learners: Replace with the number of learner nodes to be used
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# memory: Replace with the amount of memory to be
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# dedicated to training your model
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name: Pytorch gender_classification model
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description: Pytorch gender_classification model
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version: "1.0"
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gpus: 0
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cpus: 2
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learners: 1
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memory: 4Gb
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# Object stores that allow the system to retrieve training data.
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# id: The data_store id
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# type: The type of data_store
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# training_data: container: Replace with the name of the bucket at which
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# you stored the fashion MNIST dataset
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# training_results: container: Replace with the name of the bucket where
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# the resulting model should be saved to
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# connection: type: The type of connection
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# connection: auth_url: Replace with your Cloud Object Storage Endpoint url
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# for IBM Cloud
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# connection: user_name: Replace with the access_key_id found in the service
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# credentials tab on IBM Cloud
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# connection: password: Replace with the secret_access_key found in service
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# credentials tab on IBM Cloud
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data_stores:
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- id: test-datastore
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type: mount_cos
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training_data:
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container: gender-data
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training_results:
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container: gender-result
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connection:
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# Update the object storage credentials below
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auth_url: http://s3-api.us-geo.objectstorage.softlayer.net
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user_name: xxxxxx
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password: xxxxxxxxx
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# name: The name of the Deep Learning framework that will be used
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# version: The version of the framework to be used
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# command: The command to initiate training
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framework:
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name: pytorch
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version: "latest"
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command: tar -xzvf $DATA_DIR/UTKFace.tar.gz -C / --owner root --group root --no-same-owner 2>&1 > dummy.log; pip install torchsummary Pillow pandas; python -u gender_classification.py --data_dir /UTKFace/ --result_path $RESULT_DIR/model.pt --label_dir $RESULT_DIR
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