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rename config.json to parameters.json (#223)
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AML workspace configuration files are named"config.json" by default, so renaming the file containing training parameters to "parameters.json" to avoid confusion.
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jotaylo authored Mar 6, 2020
1 parent 806f042 commit efddca9
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4 changes: 2 additions & 2 deletions diabetes_regression/training/train_aml.py
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Expand Up @@ -110,8 +110,8 @@ def main():

print("Getting training parameters")

# Load the training parameters from the config file
with open("config.json") as f:
# Load the training parameters from the parameters file
with open("parameters.json") as f:
pars = json.load(f)
try:
train_args = pars["training"]
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2 changes: 1 addition & 1 deletion docs/getting_started.md
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Expand Up @@ -269,7 +269,7 @@ There are more variables used in the project. They're defined in two places: one

For using Azure Pipelines, all other variables are stored in the file `.pipelines/diabetes_regression-variables-template.yml`. Using the default values as a starting point, adjust the variables to suit your requirements.

In that folder, you'll also find the `config.json` file that we recommend using to provide parameters for training, evaluation, and scoring scripts. The sample parameter that `diabetes_regression` uses is the ridge regression [*alpha* hyperparameter](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html). We don't provide any serializers for this config file.
In that folder, you'll also find the `parameters.json` file that we recommend using to provide parameters for training, evaluation, and scoring scripts. The sample parameter that `diabetes_regression` uses is the ridge regression [*alpha* hyperparameter](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html). We don't provide any serializers for this config file.

#### Local configuration

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