# -*- coding: utf-8 -*- # This file is auto-generated, don't edit it. Thanks. from typing import Dict from Tea.core import TeaCore from alibabacloud_tea_openapi.client import Client as OpenApiClient from alibabacloud_tea_openapi import models as open_api_models from alibabacloud_tea_util.client import Client as UtilClient from alibabacloud_endpoint_util.client import Client as EndpointUtilClient # from alibabacloud_pai_dlc20201203 import models as pai_dlc_20201203_models from alibabacloud_tea_util import models as util_models from alibabacloud_openapi_util.client import Client as OpenApiUtilClient from pai.libs.alibabacloud_pai_dlc20201203 import models as pai_dlc_20201203_models class Client(OpenApiClient): """ *\ """ def __init__( self, config: open_api_models.Config, ): super().__init__(config) self._signature_algorithm = 'v2' self._endpoint_rule = 'regional' self._endpoint_map = { 'ap-northeast-1': 'pai-dlc.aliyuncs.com', 'ap-northeast-2-pop': 'pai-dlc.aliyuncs.com', 'ap-south-1': 'pai-dlc.aliyuncs.com', 'ap-southeast-2': 'pai-dlc.aliyuncs.com', 'ap-southeast-3': 'pai-dlc.aliyuncs.com', 'ap-southeast-5': 'pai-dlc.aliyuncs.com', 'cn-beijing-finance-1': 'pai-dlc.aliyuncs.com', 'cn-beijing-finance-pop': 'pai-dlc.aliyuncs.com', 'cn-beijing-gov-1': 'pai-dlc.aliyuncs.com', 'cn-beijing-nu16-b01': 'pai-dlc.aliyuncs.com', 'cn-chengdu': 'pai-dlc.aliyuncs.com', 'cn-edge-1': 'pai-dlc.aliyuncs.com', 'cn-fujian': 'pai-dlc.aliyuncs.com', 'cn-haidian-cm12-c01': 'pai-dlc.aliyuncs.com', 'cn-hangzhou-bj-b01': 'pai-dlc.aliyuncs.com', 'cn-hangzhou-finance': 'pai-dlc.aliyuncs.com', 'cn-hangzhou-internal-prod-1': 'pai-dlc.aliyuncs.com', 'cn-hangzhou-internal-test-1': 'pai-dlc.aliyuncs.com', 'cn-hangzhou-internal-test-2': 'pai-dlc.aliyuncs.com', 'cn-hangzhou-internal-test-3': 'pai-dlc.aliyuncs.com', 'cn-hangzhou-test-306': 'pai-dlc.aliyuncs.com', 'cn-hongkong-finance-pop': 'pai-dlc.aliyuncs.com', 'cn-huhehaote': 'pai-dlc.aliyuncs.com', 'cn-huhehaote-nebula-1': 'pai-dlc.aliyuncs.com', 'cn-north-2-gov-1': 'pai-dlc.aliyuncs.com', 'cn-qingdao': 'pai-dlc.aliyuncs.com', 'cn-qingdao-nebula': 'pai-dlc.aliyuncs.com', 'cn-shanghai-et15-b01': 'pai-dlc.aliyuncs.com', 'cn-shanghai-et2-b01': 'pai-dlc.aliyuncs.com', 'cn-shanghai-inner': 'pai-dlc.aliyuncs.com', 'cn-shanghai-internal-test-1': 'pai-dlc.aliyuncs.com', 'cn-shenzhen-finance-1': 'pai-dlc.aliyuncs.com', 'cn-shenzhen-inner': 'pai-dlc.aliyuncs.com', 'cn-shenzhen-st4-d01': 'pai-dlc.aliyuncs.com', 'cn-shenzhen-su18-b01': 'pai-dlc.aliyuncs.com', 'cn-wuhan': 'pai-dlc.aliyuncs.com', 'cn-wulanchabu': 'pai-dlc.aliyuncs.com', 'cn-yushanfang': 'pai-dlc.aliyuncs.com', 'cn-zhangbei': 'pai-dlc.aliyuncs.com', 'cn-zhangbei-na61-b01': 'pai-dlc.aliyuncs.com', 'cn-zhangjiakou': 'pai-dlc.aliyuncs.com', 'cn-zhangjiakou-na62-a01': 'pai-dlc.aliyuncs.com', 'cn-zhengzhou-nebula-1': 'pai-dlc.aliyuncs.com', 'eu-west-1': 'pai-dlc.aliyuncs.com', 'eu-west-1-oxs': 'pai-dlc.aliyuncs.com', 'me-east-1': 'pai-dlc.aliyuncs.com', 'rus-west-1-pop': 'pai-dlc.aliyuncs.com', 'us-east-1': 'pai-dlc.aliyuncs.com', 'us-west-1': 'pai-dlc.aliyuncs.com' } self.check_config(config) self._endpoint = self.get_endpoint('pai-dlc', self._region_id, self._endpoint_rule, self._network, self._suffix, self._endpoint_map, self._endpoint) def get_endpoint( self, product_id: str, region_id: str, endpoint_rule: str, network: str, suffix: str, endpoint_map: Dict[str, str], endpoint: str, ) -> str: if not UtilClient.empty(endpoint): return endpoint if not UtilClient.is_unset(endpoint_map) and not UtilClient.empty(endpoint_map.get(region_id)): return endpoint_map.get(region_id) return EndpointUtilClient.get_endpoint_rules(product_id, region_id, endpoint_rule, network, suffix) def create_job( self, request: pai_dlc_20201203_models.CreateJobRequest, ) -> pai_dlc_20201203_models.CreateJobResponse: runtime = util_models.RuntimeOptions() headers = {} return self.create_job_with_options(request, headers, runtime) async def create_job_async( self, request: pai_dlc_20201203_models.CreateJobRequest, ) -> pai_dlc_20201203_models.CreateJobResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.create_job_with_options_async(request, headers, runtime) def create_job_with_options( self, request: pai_dlc_20201203_models.CreateJobRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.CreateJobResponse: UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.code_source): body['CodeSource'] = request.code_source if not UtilClient.is_unset(request.data_sources): body['DataSources'] = request.data_sources if not UtilClient.is_unset(request.debugger_config_content): body['DebuggerConfigContent'] = request.debugger_config_content if not UtilClient.is_unset(request.display_name): body['DisplayName'] = request.display_name if not UtilClient.is_unset(request.elastic_spec): body['ElasticSpec'] = request.elastic_spec if not UtilClient.is_unset(request.envs): body['Envs'] = request.envs if not UtilClient.is_unset(request.job_max_running_time_minutes): body['JobMaxRunningTimeMinutes'] = request.job_max_running_time_minutes if not UtilClient.is_unset(request.job_specs): body['JobSpecs'] = request.job_specs if not UtilClient.is_unset(request.job_type): body['JobType'] = request.job_type if not UtilClient.is_unset(request.options): body['Options'] = request.options if not UtilClient.is_unset(request.priority): body['Priority'] = request.priority if not UtilClient.is_unset(request.resource_id): body['ResourceId'] = request.resource_id if not UtilClient.is_unset(request.settings): body['Settings'] = request.settings if not UtilClient.is_unset(request.thirdparty_lib_dir): body['ThirdpartyLibDir'] = request.thirdparty_lib_dir if not UtilClient.is_unset(request.thirdparty_libs): body['ThirdpartyLibs'] = request.thirdparty_libs if not UtilClient.is_unset(request.user_command): body['UserCommand'] = request.user_command if not UtilClient.is_unset(request.user_vpc): body['UserVpc'] = request.user_vpc if not UtilClient.is_unset(request.workspace_id): body['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='CreateJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs', method='POST', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.CreateJobResponse(), self.call_api(params, req, runtime) ) async def create_job_with_options_async( self, request: pai_dlc_20201203_models.CreateJobRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.CreateJobResponse: UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.code_source): body['CodeSource'] = request.code_source if not UtilClient.is_unset(request.data_sources): body['DataSources'] = request.data_sources if not UtilClient.is_unset(request.debugger_config_content): body['DebuggerConfigContent'] = request.debugger_config_content if not UtilClient.is_unset(request.display_name): body['DisplayName'] = request.display_name if not UtilClient.is_unset(request.elastic_spec): body['ElasticSpec'] = request.elastic_spec if not UtilClient.is_unset(request.envs): body['Envs'] = request.envs if not UtilClient.is_unset(request.job_max_running_time_minutes): body['JobMaxRunningTimeMinutes'] = request.job_max_running_time_minutes if not UtilClient.is_unset(request.job_specs): body['JobSpecs'] = request.job_specs if not UtilClient.is_unset(request.job_type): body['JobType'] = request.job_type if not UtilClient.is_unset(request.options): body['Options'] = request.options if not UtilClient.is_unset(request.priority): body['Priority'] = request.priority if not UtilClient.is_unset(request.resource_id): body['ResourceId'] = request.resource_id if not UtilClient.is_unset(request.settings): body['Settings'] = request.settings if not UtilClient.is_unset(request.thirdparty_lib_dir): body['ThirdpartyLibDir'] = request.thirdparty_lib_dir if not UtilClient.is_unset(request.thirdparty_libs): body['ThirdpartyLibs'] = request.thirdparty_libs if not UtilClient.is_unset(request.user_command): body['UserCommand'] = request.user_command if not UtilClient.is_unset(request.user_vpc): body['UserVpc'] = request.user_vpc if not UtilClient.is_unset(request.workspace_id): body['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='CreateJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs', method='POST', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.CreateJobResponse(), await self.call_api_async(params, req, runtime) ) def create_tensorboard( self, request: pai_dlc_20201203_models.CreateTensorboardRequest, ) -> pai_dlc_20201203_models.CreateTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return self.create_tensorboard_with_options(request, headers, runtime) async def create_tensorboard_async( self, request: pai_dlc_20201203_models.CreateTensorboardRequest, ) -> pai_dlc_20201203_models.CreateTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.create_tensorboard_with_options_async(request, headers, runtime) def create_tensorboard_with_options( self, request: pai_dlc_20201203_models.CreateTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.CreateTensorboardResponse: UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.data_source_id): body['DataSourceId'] = request.data_source_id if not UtilClient.is_unset(request.data_source_type): body['DataSourceType'] = request.data_source_type if not UtilClient.is_unset(request.data_sources): body['DataSources'] = request.data_sources if not UtilClient.is_unset(request.display_name): body['DisplayName'] = request.display_name if not UtilClient.is_unset(request.job_id): body['JobId'] = request.job_id if not UtilClient.is_unset(request.max_running_time_minutes): body['MaxRunningTimeMinutes'] = request.max_running_time_minutes if not UtilClient.is_unset(request.options): body['Options'] = request.options if not UtilClient.is_unset(request.source_id): body['SourceId'] = request.source_id if not UtilClient.is_unset(request.source_type): body['SourceType'] = request.source_type if not UtilClient.is_unset(request.summary_path): body['SummaryPath'] = request.summary_path if not UtilClient.is_unset(request.summary_relative_path): body['SummaryRelativePath'] = request.summary_relative_path if not UtilClient.is_unset(request.uri): body['Uri'] = request.uri if not UtilClient.is_unset(request.workspace_id): body['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='CreateTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards', method='POST', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.CreateTensorboardResponse(), self.call_api(params, req, runtime) ) async def create_tensorboard_with_options_async( self, request: pai_dlc_20201203_models.CreateTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.CreateTensorboardResponse: UtilClient.validate_model(request) body = {} if not UtilClient.is_unset(request.data_source_id): body['DataSourceId'] = request.data_source_id if not UtilClient.is_unset(request.data_source_type): body['DataSourceType'] = request.data_source_type if not UtilClient.is_unset(request.data_sources): body['DataSources'] = request.data_sources if not UtilClient.is_unset(request.display_name): body['DisplayName'] = request.display_name if not UtilClient.is_unset(request.job_id): body['JobId'] = request.job_id if not UtilClient.is_unset(request.max_running_time_minutes): body['MaxRunningTimeMinutes'] = request.max_running_time_minutes if not UtilClient.is_unset(request.options): body['Options'] = request.options if not UtilClient.is_unset(request.source_id): body['SourceId'] = request.source_id if not UtilClient.is_unset(request.source_type): body['SourceType'] = request.source_type if not UtilClient.is_unset(request.summary_path): body['SummaryPath'] = request.summary_path if not UtilClient.is_unset(request.summary_relative_path): body['SummaryRelativePath'] = request.summary_relative_path if not UtilClient.is_unset(request.uri): body['Uri'] = request.uri if not UtilClient.is_unset(request.workspace_id): body['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='CreateTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards', method='POST', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.CreateTensorboardResponse(), await self.call_api_async(params, req, runtime) ) def delete_job( self, job_id: str, ) -> pai_dlc_20201203_models.DeleteJobResponse: runtime = util_models.RuntimeOptions() headers = {} return self.delete_job_with_options(job_id, headers, runtime) async def delete_job_async( self, job_id: str, ) -> pai_dlc_20201203_models.DeleteJobResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.delete_job_with_options_async(job_id, headers, runtime) def delete_job_with_options( self, job_id: str, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.DeleteJobResponse: job_id = OpenApiUtilClient.get_encode_param(job_id) req = open_api_models.OpenApiRequest( headers=headers ) params = open_api_models.Params( action='DeleteJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}', method='DELETE', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.DeleteJobResponse(), self.call_api(params, req, runtime) ) async def delete_job_with_options_async( self, job_id: str, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.DeleteJobResponse: job_id = OpenApiUtilClient.get_encode_param(job_id) req = open_api_models.OpenApiRequest( headers=headers ) params = open_api_models.Params( action='DeleteJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}', method='DELETE', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.DeleteJobResponse(), await self.call_api_async(params, req, runtime) ) def delete_tensorboard( self, tensorboard_id: str, request: pai_dlc_20201203_models.DeleteTensorboardRequest, ) -> pai_dlc_20201203_models.DeleteTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return self.delete_tensorboard_with_options(tensorboard_id, request, headers, runtime) async def delete_tensorboard_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.DeleteTensorboardRequest, ) -> pai_dlc_20201203_models.DeleteTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.delete_tensorboard_with_options_async(tensorboard_id, request, headers, runtime) def delete_tensorboard_with_options( self, tensorboard_id: str, request: pai_dlc_20201203_models.DeleteTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.DeleteTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='DeleteTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}', method='DELETE', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.DeleteTensorboardResponse(), self.call_api(params, req, runtime) ) async def delete_tensorboard_with_options_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.DeleteTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.DeleteTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='DeleteTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}', method='DELETE', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.DeleteTensorboardResponse(), await self.call_api_async(params, req, runtime) ) def get_job( self, job_id: str, ) -> pai_dlc_20201203_models.GetJobResponse: runtime = util_models.RuntimeOptions() headers = {} return self.get_job_with_options(job_id, headers, runtime) async def get_job_async( self, job_id: str, ) -> pai_dlc_20201203_models.GetJobResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.get_job_with_options_async(job_id, headers, runtime) def get_job_with_options( self, job_id: str, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetJobResponse: job_id = OpenApiUtilClient.get_encode_param(job_id) req = open_api_models.OpenApiRequest( headers=headers ) params = open_api_models.Params( action='GetJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetJobResponse(), self.call_api(params, req, runtime) ) async def get_job_with_options_async( self, job_id: str, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetJobResponse: job_id = OpenApiUtilClient.get_encode_param(job_id) req = open_api_models.OpenApiRequest( headers=headers ) params = open_api_models.Params( action='GetJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetJobResponse(), await self.call_api_async(params, req, runtime) ) def get_job_events( self, job_id: str, request: pai_dlc_20201203_models.GetJobEventsRequest, ) -> pai_dlc_20201203_models.GetJobEventsResponse: runtime = util_models.RuntimeOptions() headers = {} return self.get_job_events_with_options(job_id, request, headers, runtime) async def get_job_events_async( self, job_id: str, request: pai_dlc_20201203_models.GetJobEventsRequest, ) -> pai_dlc_20201203_models.GetJobEventsResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.get_job_events_with_options_async(job_id, request, headers, runtime) def get_job_events_with_options( self, job_id: str, request: pai_dlc_20201203_models.GetJobEventsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetJobEventsResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) query = {} if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.max_events_num): query['MaxEventsNum'] = request.max_events_num if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetJobEvents', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/events', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetJobEventsResponse(), self.call_api(params, req, runtime) ) async def get_job_events_with_options_async( self, job_id: str, request: pai_dlc_20201203_models.GetJobEventsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetJobEventsResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) query = {} if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.max_events_num): query['MaxEventsNum'] = request.max_events_num if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetJobEvents', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/events', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetJobEventsResponse(), await self.call_api_async(params, req, runtime) ) def get_job_metrics( self, job_id: str, request: pai_dlc_20201203_models.GetJobMetricsRequest, ) -> pai_dlc_20201203_models.GetJobMetricsResponse: runtime = util_models.RuntimeOptions() headers = {} return self.get_job_metrics_with_options(job_id, request, headers, runtime) async def get_job_metrics_async( self, job_id: str, request: pai_dlc_20201203_models.GetJobMetricsRequest, ) -> pai_dlc_20201203_models.GetJobMetricsResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.get_job_metrics_with_options_async(job_id, request, headers, runtime) def get_job_metrics_with_options( self, job_id: str, request: pai_dlc_20201203_models.GetJobMetricsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetJobMetricsResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) query = {} if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.metric_type): query['MetricType'] = request.metric_type if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time if not UtilClient.is_unset(request.time_step): query['TimeStep'] = request.time_step if not UtilClient.is_unset(request.token): query['Token'] = request.token req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetJobMetrics', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/metrics', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetJobMetricsResponse(), self.call_api(params, req, runtime) ) async def get_job_metrics_with_options_async( self, job_id: str, request: pai_dlc_20201203_models.GetJobMetricsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetJobMetricsResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) query = {} if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.metric_type): query['MetricType'] = request.metric_type if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time if not UtilClient.is_unset(request.time_step): query['TimeStep'] = request.time_step if not UtilClient.is_unset(request.token): query['Token'] = request.token req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetJobMetrics', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/metrics', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetJobMetricsResponse(), await self.call_api_async(params, req, runtime) ) def get_pod_events( self, job_id: str, pod_id: str, request: pai_dlc_20201203_models.GetPodEventsRequest, ) -> pai_dlc_20201203_models.GetPodEventsResponse: runtime = util_models.RuntimeOptions() headers = {} return self.get_pod_events_with_options(job_id, pod_id, request, headers, runtime) async def get_pod_events_async( self, job_id: str, pod_id: str, request: pai_dlc_20201203_models.GetPodEventsRequest, ) -> pai_dlc_20201203_models.GetPodEventsResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.get_pod_events_with_options_async(job_id, pod_id, request, headers, runtime) def get_pod_events_with_options( self, job_id: str, pod_id: str, request: pai_dlc_20201203_models.GetPodEventsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetPodEventsResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) pod_id = OpenApiUtilClient.get_encode_param(pod_id) query = {} if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.max_events_num): query['MaxEventsNum'] = request.max_events_num if not UtilClient.is_unset(request.pod_uid): query['PodUid'] = request.pod_uid if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetPodEvents', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/pods/{pod_id}/events', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetPodEventsResponse(), self.call_api(params, req, runtime) ) async def get_pod_events_with_options_async( self, job_id: str, pod_id: str, request: pai_dlc_20201203_models.GetPodEventsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetPodEventsResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) pod_id = OpenApiUtilClient.get_encode_param(pod_id) query = {} if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.max_events_num): query['MaxEventsNum'] = request.max_events_num if not UtilClient.is_unset(request.pod_uid): query['PodUid'] = request.pod_uid if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetPodEvents', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/pods/{pod_id}/events', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetPodEventsResponse(), await self.call_api_async(params, req, runtime) ) def get_pod_logs( self, job_id: str, pod_id: str, request: pai_dlc_20201203_models.GetPodLogsRequest, ) -> pai_dlc_20201203_models.GetPodLogsResponse: runtime = util_models.RuntimeOptions() headers = {} return self.get_pod_logs_with_options(job_id, pod_id, request, headers, runtime) async def get_pod_logs_async( self, job_id: str, pod_id: str, request: pai_dlc_20201203_models.GetPodLogsRequest, ) -> pai_dlc_20201203_models.GetPodLogsResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.get_pod_logs_with_options_async(job_id, pod_id, request, headers, runtime) def get_pod_logs_with_options( self, job_id: str, pod_id: str, request: pai_dlc_20201203_models.GetPodLogsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetPodLogsResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) pod_id = OpenApiUtilClient.get_encode_param(pod_id) query = {} if not UtilClient.is_unset(request.download_to_file): query['DownloadToFile'] = request.download_to_file if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.max_lines): query['MaxLines'] = request.max_lines if not UtilClient.is_unset(request.pod_uid): query['PodUid'] = request.pod_uid if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetPodLogs', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/pods/{pod_id}/logs', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetPodLogsResponse(), self.call_api(params, req, runtime) ) async def get_pod_logs_with_options_async( self, job_id: str, pod_id: str, request: pai_dlc_20201203_models.GetPodLogsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetPodLogsResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) pod_id = OpenApiUtilClient.get_encode_param(pod_id) query = {} if not UtilClient.is_unset(request.download_to_file): query['DownloadToFile'] = request.download_to_file if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.max_lines): query['MaxLines'] = request.max_lines if not UtilClient.is_unset(request.pod_uid): query['PodUid'] = request.pod_uid if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetPodLogs', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/pods/{pod_id}/logs', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetPodLogsResponse(), await self.call_api_async(params, req, runtime) ) def get_tensorboard( self, tensorboard_id: str, request: pai_dlc_20201203_models.GetTensorboardRequest, ) -> pai_dlc_20201203_models.GetTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return self.get_tensorboard_with_options(tensorboard_id, request, headers, runtime) async def get_tensorboard_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.GetTensorboardRequest, ) -> pai_dlc_20201203_models.GetTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.get_tensorboard_with_options_async(tensorboard_id, request, headers, runtime) def get_tensorboard_with_options( self, tensorboard_id: str, request: pai_dlc_20201203_models.GetTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.jod_id): query['JodId'] = request.jod_id if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetTensorboardResponse(), self.call_api(params, req, runtime) ) async def get_tensorboard_with_options_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.GetTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.GetTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.jod_id): query['JodId'] = request.jod_id if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='GetTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.GetTensorboardResponse(), await self.call_api_async(params, req, runtime) ) def list_ecs_specs( self, request: pai_dlc_20201203_models.ListEcsSpecsRequest, ) -> pai_dlc_20201203_models.ListEcsSpecsResponse: runtime = util_models.RuntimeOptions() headers = {} return self.list_ecs_specs_with_options(request, headers, runtime) async def list_ecs_specs_async( self, request: pai_dlc_20201203_models.ListEcsSpecsRequest, ) -> pai_dlc_20201203_models.ListEcsSpecsResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.list_ecs_specs_with_options_async(request, headers, runtime) def list_ecs_specs_with_options( self, request: pai_dlc_20201203_models.ListEcsSpecsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.ListEcsSpecsResponse: UtilClient.validate_model(request) query = {} if not UtilClient.is_unset(request.accelerator_type): query['AcceleratorType'] = request.accelerator_type if not UtilClient.is_unset(request.order): query['Order'] = request.order if not UtilClient.is_unset(request.page_number): query['PageNumber'] = request.page_number if not UtilClient.is_unset(request.page_size): query['PageSize'] = request.page_size if not UtilClient.is_unset(request.sort_by): query['SortBy'] = request.sort_by req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='ListEcsSpecs', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/ecsspecs', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.ListEcsSpecsResponse(), self.call_api(params, req, runtime) ) async def list_ecs_specs_with_options_async( self, request: pai_dlc_20201203_models.ListEcsSpecsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.ListEcsSpecsResponse: UtilClient.validate_model(request) query = {} if not UtilClient.is_unset(request.accelerator_type): query['AcceleratorType'] = request.accelerator_type if not UtilClient.is_unset(request.order): query['Order'] = request.order if not UtilClient.is_unset(request.page_number): query['PageNumber'] = request.page_number if not UtilClient.is_unset(request.page_size): query['PageSize'] = request.page_size if not UtilClient.is_unset(request.sort_by): query['SortBy'] = request.sort_by req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='ListEcsSpecs', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/ecsspecs', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.ListEcsSpecsResponse(), await self.call_api_async(params, req, runtime) ) def list_jobs( self, request: pai_dlc_20201203_models.ListJobsRequest, ) -> pai_dlc_20201203_models.ListJobsResponse: runtime = util_models.RuntimeOptions() headers = {} return self.list_jobs_with_options(request, headers, runtime) async def list_jobs_async( self, request: pai_dlc_20201203_models.ListJobsRequest, ) -> pai_dlc_20201203_models.ListJobsResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.list_jobs_with_options_async(request, headers, runtime) def list_jobs_with_options( self, tmp_req: pai_dlc_20201203_models.ListJobsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.ListJobsResponse: UtilClient.validate_model(tmp_req) request = pai_dlc_20201203_models.ListJobsShrinkRequest() OpenApiUtilClient.convert(tmp_req, request) if not UtilClient.is_unset(tmp_req.tags): request.tags_shrink = OpenApiUtilClient.array_to_string_with_specified_style(tmp_req.tags, 'Tags', 'json') query = {} if not UtilClient.is_unset(request.business_user_id): query['BusinessUserId'] = request.business_user_id if not UtilClient.is_unset(request.caller): query['Caller'] = request.caller if not UtilClient.is_unset(request.display_name): query['DisplayName'] = request.display_name if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.from_all_workspaces): query['FromAllWorkspaces'] = request.from_all_workspaces if not UtilClient.is_unset(request.job_type): query['JobType'] = request.job_type if not UtilClient.is_unset(request.order): query['Order'] = request.order if not UtilClient.is_unset(request.page_number): query['PageNumber'] = request.page_number if not UtilClient.is_unset(request.page_size): query['PageSize'] = request.page_size if not UtilClient.is_unset(request.pipeline_id): query['PipelineId'] = request.pipeline_id if not UtilClient.is_unset(request.resource_id): query['ResourceId'] = request.resource_id if not UtilClient.is_unset(request.show_own): query['ShowOwn'] = request.show_own if not UtilClient.is_unset(request.sort_by): query['SortBy'] = request.sort_by if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time if not UtilClient.is_unset(request.status): query['Status'] = request.status if not UtilClient.is_unset(request.tags_shrink): query['Tags'] = request.tags_shrink if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='ListJobs', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.ListJobsResponse(), self.call_api(params, req, runtime) ) async def list_jobs_with_options_async( self, tmp_req: pai_dlc_20201203_models.ListJobsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.ListJobsResponse: UtilClient.validate_model(tmp_req) request = pai_dlc_20201203_models.ListJobsShrinkRequest() OpenApiUtilClient.convert(tmp_req, request) if not UtilClient.is_unset(tmp_req.tags): request.tags_shrink = OpenApiUtilClient.array_to_string_with_specified_style(tmp_req.tags, 'Tags', 'json') query = {} if not UtilClient.is_unset(request.business_user_id): query['BusinessUserId'] = request.business_user_id if not UtilClient.is_unset(request.caller): query['Caller'] = request.caller if not UtilClient.is_unset(request.display_name): query['DisplayName'] = request.display_name if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.from_all_workspaces): query['FromAllWorkspaces'] = request.from_all_workspaces if not UtilClient.is_unset(request.job_type): query['JobType'] = request.job_type if not UtilClient.is_unset(request.order): query['Order'] = request.order if not UtilClient.is_unset(request.page_number): query['PageNumber'] = request.page_number if not UtilClient.is_unset(request.page_size): query['PageSize'] = request.page_size if not UtilClient.is_unset(request.pipeline_id): query['PipelineId'] = request.pipeline_id if not UtilClient.is_unset(request.resource_id): query['ResourceId'] = request.resource_id if not UtilClient.is_unset(request.show_own): query['ShowOwn'] = request.show_own if not UtilClient.is_unset(request.sort_by): query['SortBy'] = request.sort_by if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time if not UtilClient.is_unset(request.status): query['Status'] = request.status if not UtilClient.is_unset(request.tags_shrink): query['Tags'] = request.tags_shrink if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='ListJobs', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.ListJobsResponse(), await self.call_api_async(params, req, runtime) ) def list_tensorboards( self, request: pai_dlc_20201203_models.ListTensorboardsRequest, ) -> pai_dlc_20201203_models.ListTensorboardsResponse: runtime = util_models.RuntimeOptions() headers = {} return self.list_tensorboards_with_options(request, headers, runtime) async def list_tensorboards_async( self, request: pai_dlc_20201203_models.ListTensorboardsRequest, ) -> pai_dlc_20201203_models.ListTensorboardsResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.list_tensorboards_with_options_async(request, headers, runtime) def list_tensorboards_with_options( self, request: pai_dlc_20201203_models.ListTensorboardsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.ListTensorboardsResponse: UtilClient.validate_model(request) query = {} if not UtilClient.is_unset(request.display_name): query['DisplayName'] = request.display_name if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.job_id): query['JobId'] = request.job_id if not UtilClient.is_unset(request.order): query['Order'] = request.order if not UtilClient.is_unset(request.page_number): query['PageNumber'] = request.page_number if not UtilClient.is_unset(request.page_size): query['PageSize'] = request.page_size if not UtilClient.is_unset(request.sort_by): query['SortBy'] = request.sort_by if not UtilClient.is_unset(request.source_id): query['SourceId'] = request.source_id if not UtilClient.is_unset(request.source_type): query['SourceType'] = request.source_type if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time if not UtilClient.is_unset(request.status): query['Status'] = request.status if not UtilClient.is_unset(request.tensorboard_id): query['TensorboardId'] = request.tensorboard_id if not UtilClient.is_unset(request.verbose): query['Verbose'] = request.verbose if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='ListTensorboards', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.ListTensorboardsResponse(), self.call_api(params, req, runtime) ) async def list_tensorboards_with_options_async( self, request: pai_dlc_20201203_models.ListTensorboardsRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.ListTensorboardsResponse: UtilClient.validate_model(request) query = {} if not UtilClient.is_unset(request.display_name): query['DisplayName'] = request.display_name if not UtilClient.is_unset(request.end_time): query['EndTime'] = request.end_time if not UtilClient.is_unset(request.job_id): query['JobId'] = request.job_id if not UtilClient.is_unset(request.order): query['Order'] = request.order if not UtilClient.is_unset(request.page_number): query['PageNumber'] = request.page_number if not UtilClient.is_unset(request.page_size): query['PageSize'] = request.page_size if not UtilClient.is_unset(request.sort_by): query['SortBy'] = request.sort_by if not UtilClient.is_unset(request.source_id): query['SourceId'] = request.source_id if not UtilClient.is_unset(request.source_type): query['SourceType'] = request.source_type if not UtilClient.is_unset(request.start_time): query['StartTime'] = request.start_time if not UtilClient.is_unset(request.status): query['Status'] = request.status if not UtilClient.is_unset(request.tensorboard_id): query['TensorboardId'] = request.tensorboard_id if not UtilClient.is_unset(request.verbose): query['Verbose'] = request.verbose if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='ListTensorboards', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards', method='GET', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.ListTensorboardsResponse(), await self.call_api_async(params, req, runtime) ) def start_tensorboard( self, tensorboard_id: str, request: pai_dlc_20201203_models.StartTensorboardRequest, ) -> pai_dlc_20201203_models.StartTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return self.start_tensorboard_with_options(tensorboard_id, request, headers, runtime) async def start_tensorboard_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.StartTensorboardRequest, ) -> pai_dlc_20201203_models.StartTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.start_tensorboard_with_options_async(tensorboard_id, request, headers, runtime) def start_tensorboard_with_options( self, tensorboard_id: str, request: pai_dlc_20201203_models.StartTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.StartTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='StartTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}/start', method='PUT', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.StartTensorboardResponse(), self.call_api(params, req, runtime) ) async def start_tensorboard_with_options_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.StartTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.StartTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='StartTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}/start', method='PUT', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.StartTensorboardResponse(), await self.call_api_async(params, req, runtime) ) def stop_job( self, job_id: str, ) -> pai_dlc_20201203_models.StopJobResponse: runtime = util_models.RuntimeOptions() headers = {} return self.stop_job_with_options(job_id, headers, runtime) async def stop_job_async( self, job_id: str, ) -> pai_dlc_20201203_models.StopJobResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.stop_job_with_options_async(job_id, headers, runtime) def stop_job_with_options( self, job_id: str, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.StopJobResponse: job_id = OpenApiUtilClient.get_encode_param(job_id) req = open_api_models.OpenApiRequest( headers=headers ) params = open_api_models.Params( action='StopJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/stop', method='POST', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.StopJobResponse(), self.call_api(params, req, runtime) ) async def stop_job_with_options_async( self, job_id: str, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.StopJobResponse: job_id = OpenApiUtilClient.get_encode_param(job_id) req = open_api_models.OpenApiRequest( headers=headers ) params = open_api_models.Params( action='StopJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}/stop', method='POST', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.StopJobResponse(), await self.call_api_async(params, req, runtime) ) def stop_tensorboard( self, tensorboard_id: str, request: pai_dlc_20201203_models.StopTensorboardRequest, ) -> pai_dlc_20201203_models.StopTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return self.stop_tensorboard_with_options(tensorboard_id, request, headers, runtime) async def stop_tensorboard_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.StopTensorboardRequest, ) -> pai_dlc_20201203_models.StopTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.stop_tensorboard_with_options_async(tensorboard_id, request, headers, runtime) def stop_tensorboard_with_options( self, tensorboard_id: str, request: pai_dlc_20201203_models.StopTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.StopTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='StopTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}/stop', method='PUT', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.StopTensorboardResponse(), self.call_api(params, req, runtime) ) async def stop_tensorboard_with_options_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.StopTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.StopTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='StopTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}/stop', method='PUT', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.StopTensorboardResponse(), await self.call_api_async(params, req, runtime) ) def update_job( self, job_id: str, request: pai_dlc_20201203_models.UpdateJobRequest, ) -> pai_dlc_20201203_models.UpdateJobResponse: runtime = util_models.RuntimeOptions() headers = {} return self.update_job_with_options(job_id, request, headers, runtime) async def update_job_async( self, job_id: str, request: pai_dlc_20201203_models.UpdateJobRequest, ) -> pai_dlc_20201203_models.UpdateJobResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.update_job_with_options_async(job_id, request, headers, runtime) def update_job_with_options( self, job_id: str, request: pai_dlc_20201203_models.UpdateJobRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.UpdateJobResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) body = {} if not UtilClient.is_unset(request.priority): body['Priority'] = request.priority req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='UpdateJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}', method='PUT', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.UpdateJobResponse(), self.call_api(params, req, runtime) ) async def update_job_with_options_async( self, job_id: str, request: pai_dlc_20201203_models.UpdateJobRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.UpdateJobResponse: UtilClient.validate_model(request) job_id = OpenApiUtilClient.get_encode_param(job_id) body = {} if not UtilClient.is_unset(request.priority): body['Priority'] = request.priority req = open_api_models.OpenApiRequest( headers=headers, body=OpenApiUtilClient.parse_to_map(body) ) params = open_api_models.Params( action='UpdateJob', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/jobs/{job_id}', method='PUT', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.UpdateJobResponse(), await self.call_api_async(params, req, runtime) ) def update_tensorboard( self, tensorboard_id: str, request: pai_dlc_20201203_models.UpdateTensorboardRequest, ) -> pai_dlc_20201203_models.UpdateTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return self.update_tensorboard_with_options(tensorboard_id, request, headers, runtime) async def update_tensorboard_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.UpdateTensorboardRequest, ) -> pai_dlc_20201203_models.UpdateTensorboardResponse: runtime = util_models.RuntimeOptions() headers = {} return await self.update_tensorboard_with_options_async(tensorboard_id, request, headers, runtime) def update_tensorboard_with_options( self, tensorboard_id: str, request: pai_dlc_20201203_models.UpdateTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.UpdateTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.max_running_time_minutes): query['MaxRunningTimeMinutes'] = request.max_running_time_minutes if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='UpdateTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}', method='PUT', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.UpdateTensorboardResponse(), self.call_api(params, req, runtime) ) async def update_tensorboard_with_options_async( self, tensorboard_id: str, request: pai_dlc_20201203_models.UpdateTensorboardRequest, headers: Dict[str, str], runtime: util_models.RuntimeOptions, ) -> pai_dlc_20201203_models.UpdateTensorboardResponse: UtilClient.validate_model(request) tensorboard_id = OpenApiUtilClient.get_encode_param(tensorboard_id) query = {} if not UtilClient.is_unset(request.max_running_time_minutes): query['MaxRunningTimeMinutes'] = request.max_running_time_minutes if not UtilClient.is_unset(request.workspace_id): query['WorkspaceId'] = request.workspace_id req = open_api_models.OpenApiRequest( headers=headers, query=OpenApiUtilClient.query(query) ) params = open_api_models.Params( action='UpdateTensorboard', version='2020-12-03', protocol='HTTPS', pathname=f'/api/v1/tensorboards/{tensorboard_id}', method='PUT', auth_type='AK', style='ROA', req_body_type='json', body_type='json' ) return TeaCore.from_map( pai_dlc_20201203_models.UpdateTensorboardResponse(), await self.call_api_async(params, req, runtime) )