Rui Zhuang b6e8b9ccca
Add pipeline tuner component and dependencies. (#671)
* add pipeline tuner component and dependencies.

* clean code.

* do not need force rerun.

* replace the resources.

* update metrics retrieving.

* Update test/pipeline_tuning_example/requirements.txt

* Update test/pipeline_tuning_example/train/env.yaml

* Update test/pipeline_tuning_example/tuner/env.yaml

* Update test/pipeline_tuning_example/tuner/tuner_func.py

* Update test/pipeline_tuning_example/data_prep/env.yaml

* fix issues found by lint with flake8.

* add documentation

* add data.

* do not need AML resource for local run.

* AML -> AzureML

* clean code.

* Update website/docs/Examples/Tune-AzureML pipeline.md

* rename and add pip install.

* update figure name.

* align docs with code.

* remove extra line.
2022-08-10 20:20:21 -07:00

27 lines
556 B
YAML

$schema: https://componentsdk.azureedge.net/jsonschema/CommandComponent.json
name: data_prep
version: 0.0.1
display_name: Data preparation for training
type: CommandComponent
inputs:
data:
type: path
test_train_ratio:
type: float
outputs:
train_data:
type: path
test_data:
type: path
environment:
conda:
conda_dependencies_file: env.yaml
os: Linux
command: >-
python data_prep.py
--data {inputs.data}
--test_train_ratio {inputs.test_train_ratio}
--train_data {outputs.train_data}
--test_data {outputs.test_data}