gigl.src.validation_check.libs.template_config_checks#

Attributes#

logger

Functions#

`check_if_data_preprocessor_config_cls_valid`(gbml_config_pb)	Check if dataPreprocessorArgs are all string.
`check_if_graph_metadata_valid`(gbml_config_pb)	Check if GraphMetadata specification is valid.
`check_if_inferencer_cls_valid`(gbml_config_pb)	Check if inferencerArgs are all string.
`check_if_kfp_pipeline_job_name_valid`(job_name)	Check if kfp pipeline job name valid. It is used to start spark cluster and must match pattern.
`check_if_post_processor_cls_valid`(gbml_config_pb)	Check if postProcessorArgs are all string.
`check_if_preprocessed_metadata_valid`(gbml_config_pb)	Check if preprocessedMetadata is valid.
`check_if_runtime_args_all_str`(args_name, runtime_args)	Check if all values of the given runtime arguements are string.
`check_if_split_generator_config_valid`(gbml_config_pb)	Check if splitGeneratorConfig is valid.
`check_if_subgraph_sampler_config_valid`(gbml_config_pb)	Check if subgraphSamplerConfig is valid.
`check_if_task_metadata_valid`(gbml_config_pb)	Check if taskMetadata specification is valid.
`check_if_trainer_cls_valid`(gbml_config_pb)	Check if trainerArgs are all string.
`check_pipeline_has_valid_start_and_stop_flags`(...)	Check if start_at and stop_after are valid with current static (gigl) or dynamic (glt) backend

Module Contents#

gigl.src.validation_check.libs.template_config_checks.check_if_data_preprocessor_config_cls_valid(gbml_config_pb)[source]#

Check if dataPreprocessorArgs are all string. Check if dataPreprocessorConfigClsPath is valid and importable.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_graph_metadata_valid(gbml_config_pb)[source]#

Check if GraphMetadata specification is valid.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_inferencer_cls_valid(gbml_config_pb)[source]#

Check if inferencerArgs are all string. Check if inferencerClsPath is valid and importable.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_kfp_pipeline_job_name_valid(job_name)[source]#

Check if kfp pipeline job name valid. It is used to start spark cluster and must match pattern. The kfp pipeline job name is also used to generate AppliedTaskIdentifier for each component.

Parameters:: job_name (str)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_post_processor_cls_valid(gbml_config_pb)[source]#

Check if postProcessorArgs are all string. Check if postProcessorClsPath is valid and importable.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_preprocessed_metadata_valid(gbml_config_pb)[source]#

Check if preprocessedMetadata is valid.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_runtime_args_all_str(args_name, runtime_args)[source]#

Check if all values of the given runtime arguements are string.

Parameters:

args_name (str)
runtime_args (Dict[str, Any])

Return type:

None

gigl.src.validation_check.libs.template_config_checks.check_if_split_generator_config_valid(gbml_config_pb)[source]#

Check if splitGeneratorConfig is valid.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_subgraph_sampler_config_valid(gbml_config_pb)[source]#

Check if subgraphSamplerConfig is valid.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_task_metadata_valid(gbml_config_pb)[source]#

Check if taskMetadata specification is valid.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_if_trainer_cls_valid(gbml_config_pb)[source]#

Check if trainerArgs are all string. Check if trainerClsPath is valid and importable.

Parameters:: gbml_config_pb (snapchat.research.gbml.gbml_config_pb2.GbmlConfig)
Return type:: None

gigl.src.validation_check.libs.template_config_checks.check_pipeline_has_valid_start_and_stop_flags(start_at, stop_after, task_config_uri)[source]#

Check if start_at and stop_after are valid with current static (gigl) or dynamic (glt) backend

Parameters:

start_at (str)
stop_after (Optional[str])
task_config_uri (str)

Return type:

None

gigl.src.validation_check.libs.template_config_checks.logger[source]#