describe_postpaid_training_price(self)查询每种配置的每小时的价格，价格单位：元:rtype: tencentcloud.tione.v20211111.models.DescribeBillingSpecsResponsedescribe_system_reasoning_images(self)获取平台内置的推理镜像:return: 推理镜像信息:rtype: :class:`tikit.tencentcloud.tione.v20211111.models.DescribeInferTemplatesResponse`数据格式如：{"FrameworkTemplates": [{"Framework": "TENSORFLOW","FrameworkVersion": "2.4","Groups": ["TENSORFLOW","LIGHT"],"InferTemplates": [{"InferTemplateId": "tf2.4-py38-cpu","InferTemplateImage": "ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-tensorflow-cpu:py38-tensorflow2.4-cpu-20211206"},{"InferTemplateId": "tf2.4-py38-gpu","InferTemplateImage": "ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-tensorflow-gpu:py38-tensorflow2.4-cu110-20211206"}]}],"RequestId": "3654e19b-c2ba-4953-b131-d66495723008"}print的返回结果，输出如下：（镜像标识用来配置新模型的运行环境+------------+----------------+---------------------------------------------+----------------------------------+-------------------------------------------------------------------------------------------------------------+| 算法框架 | 算法框架版本号 | 支持的训练框架集合 | 镜像标识 | 镜像url |+------------+----------------+---------------------------------------------+----------------------------------+-------------------------------------------------------------------------------------------------------------+| TENSORFLOW | 2.4 | ['TENSORFLOW', 'LIGHT'] | tf2.4-py38-cpu | ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-tensorflow-cpu:py38-tf2.4-cpu-1.0.0 || TENSORFLOW | 2.4 | ['TENSORFLOW', 'LIGHT'] | tf2.4-py38-gpu | ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-tensorflow-cpu:py38-tf2.4-cu11.0-1.0.0 || TENSORFLOW | 1.15 | ['TENSORFLOW', 'LIGHT', 'TI_ACC'] | tf1.15-py37-cpu | ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-tensorflow-cpu:py37-tf1.15-cpu-1.0.0 || TENSORFLOW | 1.15 | ['TENSORFLOW', 'LIGHT', 'TI_ACC'] | tf1.15-py37-gpu | ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-tensorflow-cpu:py37-tf1.15-cu10.0-1.0.0 || PYTORCH | 1.9 | ['PYTORCH', 'LIGHT', 'TI_ACC', 'AUTOML_CV'] | torch1.9.0-py38-cpu | ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-pytorch-cpu:py38-torch1.9.0-cpu-1.0.0 || PYTORCH | 1.9 | ['PYTORCH', 'LIGHT', 'TI_ACC', 'AUTOML_CV'] | torch1.9.0-py38-cu111 | ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-pytorch-gpu:py38-torch1.9.0-cu111-1.0.0 || PMML | 0.9.12 | ['SPARK', 'PYSPARK'] | pypmml-py38 | ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-pmml:py38-pmml0.9.16-1.0.0 || OCR | 112 | ['AUTOML_OCR'] | ocr-serving | ccr.ccs.tencentyun.com/qcloud-ti-platform/ocr_serving_gpu:serving-v121-335584d || DETECTRON2 | 112 | ['DETECTRON2'] | detectron2-torch1.9.0-py38-cu111 | ccr.ccs.tencentyun.com/qcloud-ti-platform/ti-cloud-infer-pytorch-gpu:py38-torch1.9.0-detectron2-cu111-1.0.0 |+------------+----------------+---------------------------------------------+----------------------------------+-------------------------------------------------------------------------------------------------------------+def create_training_task(self,name,framework,cos_output,worker_resource,code_package_path,ps_resource=None,input_data_config=None,worker_start_cmd=None,ps_start_cmd=None,tags=None,tuning_parameters_dict={},resource_group_id="",remark=None,log_enable=False,log_logset_id=None,log_topic_id=None,vpc_id=None,sub_net_id=None):"""创建训练任务:param name: 任务名称:type name: str:param framework: 运行的框架环境:type framework: :class:`tikit.models.FrameworkInfo`:param cos_output: 输出的cos信息:type cos_output: str:param worker_resource: worker节点的配置:type worker_resource: :class:`tikit.models.ResourceConfigInfo`:param code_package_path: 代码的cos信息:type code_package_path: str:param ps_resource: ps节点的配置:type ps_resource: :class:`tikit.models.ResourceConfigInfo`:param input_data_config: 输入的数据信息:type input_data_config: list or :class:`tikit.models.TrainingDataConfig`:param worker_start_cmd: worker的启动命令:type worker_start_cmd: str:param ps_start_cmd: ps节点的启动命令:type ps_start_cmd: str:param tags: 标签:type tags: list of :class:`tikit.tencentcloud.tione.v20211111.models.Tag`:param tuning_parameters_dict: 调参字典:type tuning_parameters_dict: dict:param resource_group_id: 预付费的资源组id:type resource_group_id: str:param remark: 描述:type remark: str:param log_enable: 日志开关:type log_enable: bool:param log_logset_id: 日志集id:type log_logset_id: str:param log_topic_id: 日志的topic id:type log_topic_id: str:param vpc_id: vpc的id:type vpc_id: str:param sub_net_id: 子网id:type sub_net_id: str:return::rtype: :class:`tikit.tencentcloud.tione.v20211111.models.CreateTrainingTaskResponse`"""def describe_training_frameworks(self):"""查看训练框架:rtype: :class:`tikit.tencentcloud.tione.v20211111.models.DescribeTrainingFrameworksResponse`print返回的结果，输出如下：+------------+----------------------------------------+-------------------------+| 框架名称 | 版本 | 训练模式 |+------------+----------------------------------------+-------------------------+| TENSORFLOW | ti-acc1.0-tf1.15-py3.6-cuda10.0-gpu | PS_WORKER || TENSORFLOW | light3.1.3-tf2.4-py3.8-cuda11.1-gpu | MPI, HOROVOD || TENSORFLOW | tf1.15-py3.7-cpu | PS_WORKER, MPI, HOROVOD || TENSORFLOW | tf1.15-py3.7-cuda10.0-gpu | PS_WORKER, MPI, HOROVOD || TENSORFLOW | tf2.4-py3.8-cpu | PS_WORKER, MPI, HOROVOD || TENSORFLOW | tf2.4-py3.8-cuda11.1-gpu | PS_WORKER, MPI, HOROVOD || PYTORCH | ti-acc1.0-torch1.9-py3.8-cuda11.1-gpu | DDP || PYTORCH | light3.1.3-torch1.9-py3.8-cuda11.1-gpu | DDP, MPI, HOROVOD || PYTORCH | torch1.9-py3.8-cuda11.1-gpu | DDP, MPI, HOROVOD || SPARK | spark2.4.5-cpu | SPARK || PYSPARK | spark2.4.5-py3.6-cpu | SPARK |+------------+----------------------------------------+-------------------------+"""def describe_training_tasks(self, filters=None, tag_filters=None, offset=0, limit=50, order="DESC",order_field="UpdateTime"):"""获取训练任务列表:param filters: 过滤器，eg：[{ "Name": "TaskStatus", "Values": ["Running"] }]:type filters: list of Filter:param tag_filters: 标签过滤器，eg：[{ "TagKey": "TagKeyA", "TagValue": ["TagValueA"] }]:type tag_filters: list of TagFilter:param offset: 偏移量，默认为0:type offset: int:param limit: 返回数量，默认为50:type limit: int:param order: 输出列表的排列顺序。取值范围：ASC：升序排列 DESC：降序排列:type order: str:param order_field: 排序的依据字段， 取值范围 "CreateTime" "UpdateTime":type order_field: str:return::rtype: :class:`tikit.tencentcloud.tione.v20211111.models.DescribeTrainingTasksResponse`"""describe_training_task(self, task_id)获取单个训练任务信息:param task_id: 训练任务ID:type task_id: str:rtype: :class:`tencentcloud.tione.v20211111.models.DescribeTrainingTaskResponse`describe_training_task_pods(self, task_id)获取训练任务的pod列表:param task_id: 训练任务ID:type task_id: str:rtype: :class:`tencentcloud.tione.v20211111.models.DescribeTrainingTaskPodsResponse`def describe_train_logs(self, pod_name, start_time=None, end_time=None, limit=None, order=None,context=None, filters=None):"""查看训练任务的日志:param pod_name: 查询哪个Pod的日志，支持通配符。查看某个训练任务的全部pod的日志可以填： "<task_id>*"，如：train-51cd6bf7ec1000*:type pod_name: str:param start_time: 日志查询开始时间。RFC3339格式的时间字符串，比如2021-12-16T13:20:24+08:00，默认值为当前时间的前一个小时:type start_time: str:param end_time: 日志查询结束时间。RFC3339格式的时间字符串，比如2021-12-16T13:20:24+08:00，默认值为当前时间:type end_time: str:param limit: 日志查询条数，默认值100，最大值100:type limit: int:param order: 排序方向。(ASC | DESC) 默认值为DESC:type order: str:param context: 分页的游标:type context: str:param filters: 过滤Filters:type filters: list of tikit.tencentcloud.tione.v20211111.models.Filter:rtype: :class:`tikit.tencentcloud.tione.v20211111.models.DescribeLogsResponse`返回的对象如果非空，就会有 next() 方法，能不断地获取下一页的日志（如果有多页的话），如下：now_time = datetime.datetime.now(datetime.timezone.utc)now_time_str = now_time.isoformat()result = client.describe_train_logs("train-51cd6bf7ec1000-37c5p5nlr01s-launcher","2021-12-10T09:32:03.823509+00:00",now_time_str,limit=30)print(result)print(result.next())print(result.next())print(result.next())"""def push_training_metrics(self, timestamp, value_map, task_id=None, epoch=None, total_steps=None, step=None):"""上报训练自定义指标（单条）。单个子账号每秒可以调用20次，请在您的训练代码中注意控制上报频率，避免超限报错。或者使用push_training_metrics_list:param timestamp: 时间戳:type timestamp: int:param value_map: 指标映射。 指标名称 -> 指标值:type value_map: map: str -> float:param task_id: 任务ID。若为空，就当前取任务节点环境的 TI_TASK_ID 环境变量的值:type task_id: str:param epoch: epoch值:type epoch: int:param total_steps: 总步数:type total_steps: int:param step: 第几步:type step: int:return::rtype: :class:`tikit.tencentcloud.tione.v20211111.models.PushTrainingMetricsResponse`client.push_training_metrics(int(time.time()), {"field1": 11, "field2": 12}, "task-id-00001", 3, 1000, 66)"""push_training_metrics_list(self, metric_list)上报训练自定义指标（列表）:param metric_list: MetricData 数组。 若任务ID为空，就当前取任务节点环境的 TI_TASK_ID 环境变量的值:type metric_list: list of :class:`tencentcloud.tione.v20211111.models.MetricData`:return::rtype: :class:`tencentcloud.tione.v20211111.models.PushTrainingMetricsResponse`describe_training_metrics(self, task_id)查询训练自定义指标:param task_id: 任务ID:type task_id: str:rtype: :class:`tencentcloud.tione.v20211111.models.DescribeTrainingMetricsResponse`stop_training_task(self, task_id)停止某个训练任务:param task_id: 训练任务ID:type task_id: str:rtype: :class:`tencentcloud.tione.v20211111.models.StopTrainingTaskResponse`delete_training_task(self, task_id)删除某个训练任务:param task_id: 训练任务ID:type task_id: str:rtype: :class:`tencentcloud.tione.v20211111.models.DeleteTrainingTaskResponse`
中间配置：
tikit.models.FrameworkInfodef new_custom(training_mode, image_type, image_url, registry_region=None, registry_id=None):"""自定义训练框架的配置:param training_mode: 训练模式。 通过describe_training_frameworks()查看列表:type training_mode: str:param image_type: 腾讯云容器镜像服务的镜像类型，如"CCR":type image_type: str:param image_url: 腾讯云容器镜像服务的镜像地址:type image_url: str:param registry_region: 腾讯云容器镜像服务的镜像仓库的域:type registry_region: str:param registry_id: 腾讯云容器镜像服务的镜像仓库ID:type registry_id: str:return::rtype:"""def new_custom_image(image_type, image_url, registry_region=None, registry_id=None):"""自定义镜像的配置:param image_type: 腾讯云容器镜像服务的镜像类型，如"CCR":type image_type: str:param image_url: 腾讯云容器镜像服务的镜像地址:type image_url: str:param registry_region: 腾讯云容器镜像服务的镜像仓库的域:type registry_region: str:param registry_id: 腾讯云容器镜像服务的镜像仓库ID:type registry_id: str:return::rtype:"""def new_system_framework(framework_name, framework_environment, training_mode):"""系统内置的训练框架:param framework_name: 框架名称。 通过describe_training_frameworks()查看列表:type framework_name: str:param framework_environment: 框架环境。 通过describe_training_frameworks()查看列表:type framework_environment: str:param training_mode: 训练模式。 通过describe_training_frameworks()查看列表:type training_mode: str:return::rtype:"""----------------------------------------------------tikit.models.ResourceConfigInfodef new_postpaid(instance_type, instance_num):"""获取后付费模式下的资源配置:param instance_type: 实例类型。通过 describe_postpaid_training_price() 查看实例列表:type instance_type: str:param instance_num: 实例数量:type instance_num: int:return::rtype:"""|def new_prepaid(cpu, memory, gpu=0, gpu_type=None, instance_num=1):"""获取预付费模式下的资源配置:param cpu: CPU个数，单位是核:type cpu: float:param memory: 内存大小，单位是GB:type memory: float:param gpu_type: gpu类型:type gpu_type: str:param gpu: gpu个数:type gpu: float:param instance_num: 实例数量:type instance_num: int:return::rtype:"""----------------------------------------------------tikit.models.TrainingDataConfigdef new_mount_cos(cos_str, target_path):"""一个cos类型的训练数据:param cos_str: cos存储，格式： <bucket>/<cos path>/:type cos_str: str:param target_path: 目标挂载路径:type target_path: str:return::rtype:"""def new_dataset_mount(dataset_id, target_path):"""一个dataset类型的训练数据:param dataset_id: 数据集ID:type dataset_id: str:param target_path: 目标挂载路径:type target_path: str:return::rtype:"""def new_mount_cfs(cfs_id, source_path, target_path):"""新建一个cfs类型的训练数据集配置:param cfs_id: CFS的ID:type cfs_id: str:param source_path: CFS的路径:type source_path: str:param target_path: 目标挂载路径:type target_path: str:return::rtype:"""def new_mount_hdfs(hdfs_id, source_path, target_path):"""新建一个hdfs类型的训练数据集配置:param hdfs_id: EMR上HDFS的ID:type hdfs_id: str:param source_path: HDFS的路径:type source_path: str:param target_path: 目标挂载路径:type target_path: str:return::rtype:"""def new_mount_wedata_hdfs(wedata_id, source_path):"""新建一个wedata hdfs类型的训练数据集配置:param wedata_id: wedata数据源id:type wedata_id: int:param source_path: HDFS的路径:type source_path: str:return::rtype:"""def new_dataset(id_target_dict):""" Deprecated !新建一个dataset类型的训练数据集配置:param id_target_dict: 数据集信息。 dataset id -> 下载的目标路径:type id_target_dict: dict:return::rtype:"""def new_cos_data(cos_str_target_dict):"""Deprecated !新建一个cos类型的训练数据集配置:param cos_str_target_dict: 数据集信息。 <bucket>/<cos path>/ -> 下载的目标路径:type cos_str_target_dict: dict:return::rtype:"""
