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clean up
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commit
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1 changed files with 60 additions and 56 deletions
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@ -23,67 +23,71 @@ class ColumnName(Enum):
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context = "context"
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def get_expected_schema_for_scoring():
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return [
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{
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ColumnName.input_query.value: StringType(),
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ColumnName.expected_answer.value: StringType(),
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ColumnName.generated_answer.value: StringType(),
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},
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{
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ColumnName.input_query.value: StringType(),
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ColumnName.expected_answer.value: StringType(),
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ColumnName.generated_answer.value: StringType(),
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ColumnName.context.value: StringType(),
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},
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]
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def get_expected_schema_for_eval():
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return [
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{
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ColumnName.input_query.value: StringType(),
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ColumnName.expected_answer.value: StringType(),
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ColumnName.chat_completion_input.value: ChatCompletionInputType(),
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},
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{
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ColumnName.input_query.value: StringType(),
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ColumnName.expected_answer.value: StringType(),
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ColumnName.completion_input.value: CompletionInputType(),
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},
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]
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def validate_dataset_schema(
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dataset_schema: Dict[str, Any], expected_schemas: List[Dict[str, Any]]
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):
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if dataset_schema not in expected_schemas:
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raise ValueError(
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f"Dataset does not have a correct input schema in {expected_schemas}"
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)
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def validate_row_schema(
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input_row: Dict[str, Any], expected_schemas: List[Dict[str, Any]]
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):
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for schema in expected_schemas:
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if all(key in input_row for key in schema):
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return
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raise ValueError(
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f"Input row {input_row} does not match any of the expected schemas in {expected_schemas}"
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)
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class DataSchemaValidatorMixin:
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def validate_dataset_schema_for_scoring(self, dataset_schema: Dict[str, Any]):
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validate_dataset_schema(dataset_schema, get_expected_schema_for_scoring())
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self.validate_dataset_schema(
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dataset_schema, self.get_expected_schema_for_scoring()
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)
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def validate_dataset_schema_for_eval(self, dataset_schema: Dict[str, Any]):
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validate_dataset_schema(dataset_schema, get_expected_schema_for_eval())
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self.validate_dataset_schema(
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dataset_schema, self.get_expected_schema_for_eval()
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)
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def validate_row_schema_for_scoring(self, row_schema: Dict[str, Any]):
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validate_row_schema(row_schema, get_expected_schema_for_scoring())
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self.validate_row_schema(row_schema, self.get_expected_schema_for_scoring())
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def validate_row_schema_for_eval(self, row_schema: Dict[str, Any]):
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validate_row_schema(row_schema, get_expected_schema_for_eval())
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self.validate_row_schema(row_schema, self.get_expected_schema_for_eval())
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def get_expected_schema_for_scoring(self):
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return [
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{
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ColumnName.input_query.value: StringType(),
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ColumnName.expected_answer.value: StringType(),
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ColumnName.generated_answer.value: StringType(),
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},
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{
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ColumnName.input_query.value: StringType(),
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ColumnName.expected_answer.value: StringType(),
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ColumnName.generated_answer.value: StringType(),
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ColumnName.context.value: StringType(),
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},
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]
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def get_expected_schema_for_eval(self):
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return [
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{
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ColumnName.input_query.value: StringType(),
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ColumnName.expected_answer.value: StringType(),
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ColumnName.chat_completion_input.value: ChatCompletionInputType(),
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},
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{
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ColumnName.input_query.value: StringType(),
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ColumnName.expected_answer.value: StringType(),
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ColumnName.completion_input.value: CompletionInputType(),
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},
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]
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def validate_dataset_schema(
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self,
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dataset_schema: Dict[str, Any],
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expected_schemas: List[Dict[str, Any]],
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):
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if dataset_schema not in expected_schemas:
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raise ValueError(
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f"Dataset does not have a correct input schema in {expected_schemas}"
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)
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def validate_row_schema(
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self,
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input_row: Dict[str, Any],
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expected_schemas: List[Dict[str, Any]],
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):
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for schema in expected_schemas:
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if all(key in input_row for key in schema):
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return
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raise ValueError(
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f"Input row {input_row} does not match any of the expected schemas in {expected_schemas}"
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)
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