snowflake.ml.model.ModelVersion¶

class snowflake.ml.model.ModelVersion¶

Bases: object

Model Version Object representing a specific version of the model that could be run.

Methods

delete_metric(metric_name: str) → None¶

Delete a metric from metric storage.

Args:

metric_name:: The name of the metric to be deleted.

Raises:

KeyError: When the requested metric name does not exist.

get_metric(metric_name: str) → Any¶

Get the value of a specific metric.

Args:

metric_name:: The name of the metric.

Raises:

KeyError: When the requested metric name does not exist.

Returns:

The value of the metric.

run(X: Union[DataFrame, DataFrame], *, function_name: Optional[str] = None, strict_input_validation: bool = False) → Union[DataFrame, DataFrame]¶

Invoke a method in a model version object.

Args:

X:: The input data, which could be a pandas DataFrame or Snowpark DataFrame.
function_name:: The function name to run. It is the name used to call a function in SQL. Defaults to None. It can only be None if there is only 1 method.
strict_input_validation:: Enable stricter validation for the input data. This will result value range based type validation to make sure your input data won’t overflow when providing to the model.

Raises:

ValueError: When no method with the corresponding name is available.

ValueError: When there are multiple target methods available in the model but no function name specified.

Returns:

The prediction data. It would be the same type dataframe as your input.

set_metric(metric_name: str, value: Any) → None¶

Set the value of a specific metric.

Args:

metric_name:: The name of the metric.
value:: The value of the metric.

show_functions() → List[ModelFunctionInfo]¶

Show all functions information in a model version that is callable.

Returns:

A list of ModelFunctionInfo objects containing the following information:

name: The name of the function to be called (both in SQL and in Python SDK).
target_method: The original method name in the logged Python object.
signature: Python signature of the original method.

show_metrics() → Dict[str, Any]¶

Show all metrics logged with the model version.

Returns:: A dictionary showing the metrics.

Attributes

comment¶: The comment to the model version.

description¶: The description for the model version. This is an alias of comment.

fully_qualified_model_name¶: Return the fully qualified name of the model to which the model version belongs.

model_name¶: Return the name of the model to which the model version belongs, usable as a reference in SQL.

version_name¶: Return the name of the version to which the model version belongs, usable as a reference in SQL.