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Added boolean disables, generation of train (metrics.csv) and test metrics (test_metrics.csv) #397

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merged 13 commits into from
Nov 1, 2023
Merged

Added boolean disables, generation of train (metrics.csv) and test metrics (test_metrics.csv) #397

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7c32dfa
added boolean disables and added test_metrics.csv generation
govarsha Oct 30, 2023
1660455
updated metrics_filename, test_metrics_filename, forecast_filename in…
govarsha Oct 30, 2023
6824a57
changed report_file_name to report_filename
govarsha Oct 30, 2023
dccc779
added changes to schema.yaml
govarsha Oct 30, 2023
a9417fd
added comments
govarsha Oct 30, 2023
52eaf9c
Merge branch 'feature/forecasting' into feature/add-boolean-disables-…
ahosler Oct 31, 2023
9a8ab34
added train_metrics to base_model
govarsha Oct 31, 2023
db4b6f5
added forecast_col_name attribute to base_model
govarsha Oct 31, 2023
1c4949a
small fixes to be consistent with recent changes
govarsha Oct 31, 2023
8559ebf
fixing merge conflicts
govarsha Oct 31, 2023
baff6cd
resolving merge conflicts
govarsha Oct 31, 2023
d4d49bc
Merge branch 'feature/add-boolean-disables-and-save-train-test-metric…
govarsha Oct 31, 2023
4eef4e0
Merge branch 'feature/forecasting' into feature/add-boolean-disables-…
ahosler Nov 1, 2023
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10 changes: 6 additions & 4 deletions ads/opctl/operator/lowcode/forecast/model/arima.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,11 +11,17 @@

from .. import utils
from .base_model import ForecastOperatorBaseModel
from ..operator_config import ForecastOperatorConfig


class ArimaOperatorModel(ForecastOperatorBaseModel):
"""Class representing ARIMA operator model."""

def __init__(self, config: ForecastOperatorConfig):
super().__init__(config)
self.train_metrics = False
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If the all models require these extra attributes, maybe we can add them to the base model class?

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These values were defined for each model inside _generate_report method. I have abstracted them out as attributes because I needed them outside of that method.
The train_metrics value is True/False according to the model so I am not sure if we can define them in base_model. cc: @ahosler

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One thing you could do is add self.train_metrics = False to the base class, and then update it to True only in prophet and neuralprophet so that if we add model classes in the future train_metrics is disabled by default.

self.forecast_col_name = "yhat"

def _build_model(self) -> pd.DataFrame:
full_data_dict = self.full_data_dict

Expand Down Expand Up @@ -153,17 +159,13 @@ def _generate_report(self):
"it predicts future values based on past values."
)
other_sections = all_sections
forecast_col_name = "yhat"
train_metrics = False
ds_column_series = self.data[self.spec.datetime_column.name]
ds_forecast_col = self.outputs[0].index
ci_col_names = ["yhat_lower", "yhat_upper"]

return (
model_description,
other_sections,
forecast_col_name,
train_metrics,
ds_column_series,
ds_forecast_col,
ci_col_names,
Expand Down
8 changes: 3 additions & 5 deletions ads/opctl/operator/lowcode/forecast/model/automlx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,8 @@ def __init__(self, config: ForecastOperatorConfig):
super().__init__(config)
self.global_explanation = {}
self.local_explanation = {}
self.train_metrics = False
self.forecast_col_name = "yhat"

@runtime_dependency(
module="automl",
Expand Down Expand Up @@ -211,7 +213,7 @@ def _generate_report(self):

all_sections = [selected_models_text, selected_models_section]

if self.spec.explain:
if self.spec.generate_explanations:
# If the key is present, call the "explain_model" method
self.explain_model()

Expand Down Expand Up @@ -257,17 +259,13 @@ def _generate_report(self):
"high-quality features in your dataset, which are then provided for further processing."
)
other_sections = all_sections
forecast_col_name = "yhat"
train_metrics = False
ds_column_series = self.data[self.spec.datetime_column.name]
ds_forecast_col = self.outputs[0]["ds"]
ci_col_names = ["yhat_lower", "yhat_upper"]

return (
model_description,
other_sections,
forecast_col_name,
train_metrics,
ds_column_series,
ds_forecast_col,
ci_col_names,
Expand Down
10 changes: 6 additions & 4 deletions ads/opctl/operator/lowcode/forecast/model/autots.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@

from .. import utils
from .base_model import ForecastOperatorBaseModel
from ..operator_config import ForecastOperatorConfig
from ads.common.decorator.runtime_dependency import runtime_dependency


Expand All @@ -22,6 +23,11 @@
class AutoTSOperatorModel(ForecastOperatorBaseModel):
"""Class representing AutoTS operator model."""

def __init__(self, config: ForecastOperatorConfig):
super().__init__(config)
self.train_metrics = False
self.forecast_col_name = "yhat"

@runtime_dependency(
module="autots",
err_msg="Please run `pip3 install autots` to install the required dependencies for autots.",
Expand Down Expand Up @@ -250,8 +256,6 @@ def _generate_report(self) -> tuple:
)

other_sections = all_sections
forecast_col_name = "yhat"
train_metrics = False

ds_column_series = pd.to_datetime(self.data[self.spec.datetime_column.name])
ds_forecast_col = self.outputs[0].index
Expand All @@ -260,8 +264,6 @@ def _generate_report(self) -> tuple:
return (
model_description,
other_sections,
forecast_col_name,
train_metrics,
ds_column_series,
ds_forecast_col,
ci_col_names,
Expand Down
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