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    Platform For AI:Model training

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    Platform For AI:Model training

    Last Updated:Aug 24, 2026

    This component trains EasyRec models.

    Prerequisites

    You must activate Object Storage Service (OSS) and grant the required permissions. For more information, see Activate OSS and Cloud product dependencies and authorizations: Designer.

    Component Configuration

    Configure the model training component in one of the following ways.

    Configure the component visually

    • Input ports

    Input port (from left to right)

    Recommended upstream component

    Corresponding PAI command parameter

    Required

    Negative sampling item feature table

    Note

    Negative sampling parameters are typically used in specific algorithms such as Deep Structured Semantic Models (DSSM).

    data_config.negative_sampler.input_path

    No

    EasyRec configuration file
    Note

    The full OSS path of the configuration file is required.

    config

    No

    Training table

    train_tables

    Yes

    Evaluation table

    eval_tables

    Yes

    fine_tune_checkpoint

    Note

    The model continues training based on this checkpoint.

    • Data type: Model stored in OSS

    • Supported components: Read OSS Data

    train_config.fine_tune_checkpoint in edit_config_json

    No

    Binning table

    boundary_table

    No

    • Component parameters

    Tab

    Parameter

    Required

    Description

    Corresponding PAI command parameter

    Default value

    Parameter Settings

    Model path

    No

    The model storage path.

    model_dir

    Pipeline data path

    EasyRec configuration file

    No

    If no configuration file is provided from the input port, refer to model_config, enter the configuration in the editor, and save it to a specified OSS path.

    config

    None

    Select target columns for training and evaluation

    No

    This parameter is available only when you select Is RTP FG mode.

    Specifies the target columns for training and evaluation.

    Combined into the selected_cols parameter

    None

    Weight columns for training and evaluation

    No

    This parameter is available only when you select Is RTP FG mode.

    Specifies the weight columns for training and evaluation.

    None

    Feature columns for training and evaluation

    No

    This parameter is available only when you select Is RTP FG mode.

    Specifies the feature columns for training and evaluation.

    None

    Specify algorithm version

    No

    After you select Advanced Options, you can customize the EasyRec execution version.

    1. First, refer to EasyRec version updates to generate an EasyRec TAR package.

    2. Upload the TAR package of the corresponding version to an OSS path. For more information, see Upload a file in the console.

    3. Select the uploaded TAR file for this parameter.

    script

    Empty

    Hyperparameter configuration edit_config_json

    No

    After you select Advanced Options, enter the hyperparameters to add to the EasyRec configuration file. The component merges these settings into the configuration file.

    edit_config_json

    None

    Execution tuning

    Number of PS

    No

    The number of parameter server (PS) nodes.

    The complete execution tuning parameters are combined into the cluster parameter

    2

    Number of PS CPUs

    No

    The number of CPUs requested by each PS. A value of 1 indicates one CPU core.

    10

    PS memory size (MB)

    No

    The memory requested by each PS. A value of 100 indicates 100 MB.

    40000

    Number of workers

    No

    The number of worker nodes.

    6

    Number of worker CPUs

    No

    The number of CPUs requested by each worker. A value of 1 indicates one CPU core.

    8

    Worker memory usage (MB)

    No

    The memory requested by each worker. A value of 100 indicates 100 MB.

    40000

    Number of worker GPUs

    No

    GPUs are generally not required for EasyRec training.

    0

    PAI command and description

    PAI -project algo_public -name easy_rec_ext 
    -Darn="acs:ram::xxxx:role/aliyunodpspaidefaultrole" 
    -Dbuckets="oss://rec_sln_demo/" 
    -Dcluster="{\"ps\": {\"count\": 2, \"cpu\": 1000, \"memory\": 40000}, \"worker\": {\"count\": 6, \"cpu\": 800, \"gpu\": 0, \"memory\": 40000}}" 
    -Dcmd="train" 
    -Dconfig="oss://rec_sln_demo/EasyRec/deploy/rec_sln_demo_dssm_recall_v1/rec_sln_demo_dssm_recall_v1.config" 
    -Deval_tables="odps://pai_hangzhou/tables/pai_temp_flow_26un8zq7v4goadi373_node_39w13qw9osm9rdbu0h_outputTable" 
    -Dlifecycle="28" 
    -Dmodel_dir="oss://rec_sln_demo/EasyRec/deploy/rec_sln_demo_dssm_recall_v1/20230425" 
    -DossHost="oss-cn-hangzhou-internal.aliyuncs.com" 
    -Dscript="oss://rec_sln_demo/easy_rec_ext_0.6.1_res.tar.gz" 
    -Dselected_cols="is_click,features" 
    -Dtables="odps://pai_hangzhou/tables/pai_temp_flow_26un8zq7v4goadi373_node_4ijqwcg7upzteu5036_outputTable,odps://pai_hangzhou/tables/pai_temp_flow_26un8zq7v4goadi373_node_39w13qw9osm9rdbu0h_outputTable,odps://pai_hangzhou/tables/pai_temp_flow_fty24i21e9dzvzj6a0_node_svxd0bqu2x7ep8furu_outputTable" 
    -Dtrain_tables="odps://pai_hangzhou/tables/pai_temp_flow_26un8zq7v4goadi373_node_4ijqwcg7upzteu5036_outputTable"
    -Dedit_config_json="{\"train_config.fine_tune_checkpoint\": \"oss://rec_sln_demo/EasyRec/deploy/rec_sln_demo_dssm_recall_v1/20230405/\", \"data_config.negative_sampler.input_path\": \"odps://pai_hangzhou/tables/pai_temp_flow_fty24i21e9dzvzj6a0_node_svxd0bqu2x7ep8furu_outputTable\"}" ;

    Parameter name

    Required

    Description

    cmd

    Yes

    Set cmd to train to run model training.

    config

    Yes

    The EasyRec configuration file for training. Provide the full OSS path.

    train_tables

    Yes

    The training table. The format is odps://{project}/tables/{table_name}. Separate multiple training tables with a comma (,).

    eval_tables

    Yes

    The evaluation table. The format is odps://{project}/tables/{table_name}. Separate multiple evaluation tables with a comma (,).

    arn

    Yes

    The resource group authorization. Log on to the PAI console. On the Activation and Authorization>All Cloud Product Dependencies page, in the Designer section, click View Authorization Information in the Operation column to obtain the arn.

    ossHost

    Yes

    The OSS endpoint for each region. For information about how to obtain an endpoint, see Endpoints and data centers.

    buckets

    Yes

    The buckets for the configuration file and model storage. Separate multiple buckets with commas (,), for example, oss://xxxx/,oss://xxxx/.

    model_dir

    Yes

    The model directory. Overrides the model_dir value in the configuration file when specified. Typically used for periodic scheduling.

    edit_config_json

    No

    Modifies configuration file fields in JSON format. For example: edit_config_json="{\"train_config.fine_tune_checkpoint\": \"oss://xxx/\"}".

    script

    No

    The EasyRec algorithm TAR file.

    selected_cols

    No

    The table columns used for training and evaluation. Specifying columns improves training speed.

    Usage example

    1. Prepare the following datasets:

      • train: pai_online_project.easyrec_demo_taobao_train_data

      • test: pai_online_project.easyrec_demo_taobao_test_data

      Note

      Ideally, you should use your own ODPS tables, but for testing purposes, the two provided tables are publicly accessible.

    2. Create a workflow as shown in the following figure.image..png

      Area

      Description

      ①

      Set the Table Name parameter of Read Data Table-1 to pai_online_project.easyrec_demo_taobao_train_data_training_table.

      ②

      Set the Table Name parameter of Read Data Table-2 to pai_online_project.easyrec_demo_taobao_test_data_test_table.

      ③

      • Upload the configuration file to OSS and select the file for the EasyRec configuration file parameter.

      • For the Model path parameter, select the model storage path.

    3. After the workflow finishes, you can view the output model file.

      You can view the output model file in the OSS path that you configured for the Model path parameter.

    4. View and analyze logs in Logview.

      When the EasyRec command runs, Designer provides a link to Logview. Right-click the model training component and click View Log in the shortcut menu. You can use Logview to quickly view the model training results or locate errors.

    image..png

    On the Worker running page, select a task instance and worker to view details.

    image..png

    Where:

    • worker 0 is a training worker. Workers 2 to 7 are also training workers. Click the icon in the StdErr column to view the training process.

    • worker 1 is an evaluation worker. Click the icon in the StdErr column to view the model's metrics on the evaluation set.

    For more usage examples, see the 8_rec_sln_demo_rec_sln_demo_sorting_v2_train node in the Recommendation Algorithm Customization - Sorting example and the 12_rec_sln_demo_dssm_recall_v1_train node in the Recommendation Algorithm Customization - Vector Recall example.