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app.config.toml
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app.config.toml
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[DATA_NODE.dataset]
storage_type = "csv"
scope = "SCENARIO:SCOPE"
cacheable = "False:bool"
default_path = "data/data.csv"
headers = "True:bool"
[DATA_NODE.preprocessed]
storage_type = "pickle"
scope = "SCENARIO:SCOPE"
cacheable = "False:bool"
[DATA_NODE.prediction_model]
storage_type = "pickle"
scope = "SCENARIO:SCOPE"
cacheable = "False:bool"
[DATA_NODE.prediction]
storage_type = "pickle"
scope = "SCENARIO:SCOPE"
cacheable = "False:bool"
[DATA_NODE.long_running_output]
storage_type = "pickle"
scope = "SCENARIO:SCOPE"
cacheable = "False:bool"
[DATA_NODE.raise_exception_output]
storage_type = "pickle"
scope = "SCENARIO:SCOPE"
cacheable = "False:bool"
[DATA_NODE.fixed_value]
storage_type = "pickle"
scope = "SCENARIO:SCOPE"
cacheable = "False:bool"
default_data = ["1:int", "19:int", "20000:int"]
[TASK.long_running]
inputs = ["dataset:SECTION"]
function = "algo.debug.long_running:function"
outputs = ["long_running_output:SECTION"]
[TASK.raise_exception]
inputs = ["dataset:SECTION"]
function = "algo.debug.raise_exception:function"
outputs = ["raise_exception_output:SECTION"]
[TASK.preprocess]
inputs = ["dataset:SECTION"]
function = "algo.ml.preprocess:function"
outputs = ["preprocessed:SECTION"]
[TASK.train]
inputs = ["preprocessed:SECTION"]
function = "algo.ml.train:function"
outputs = ["prediction_model:SECTION"]
[TASK.predict]
inputs = ["fixed_value:SECTION", "prediction_model:SECTION"]
function = "algo.ml.predict:function"
outputs = ["prediction:SECTION"]
[PIPELINE.default]
tasks = []
[PIPELINE.train]
tasks = ["preprocess:SECTION", "train:SECTION"]
[PIPELINE.predict]
tasks = ["predict:SECTION"]
[PIPELINE.long_running]
tasks = ["long_running:SECTION"]
[PIPELINE.raise_exception]
tasks = ["raise_exception:SECTION"]