dssm train

recommend-model-produce/src/main/python/models/dssm/config_ps_hdfs.yaml

@@ -29,7 +29,7 @@ runner:
   epochs: 3
   print_interval: 1
   
-  test_data_dir: "data/test"
+  test_data_dir: "/dw/recommend/model/56_dssm_i2i_itempredData/20241206/part-00016.gz"
   infer_reader_path: "bq_reader_train_ps"  # importlib format
   infer_batch_size: 1
   infer_load_path: "/app/output_model_dssm"

recommend-model-produce/src/main/python/tools/static_ps_infer_v2.py

@@ -15,7 +15,7 @@
 from __future__ import print_function
 import os
 os.environ['FLAGS_enable_pir_api'] = '0'
-from utils.static_ps.reader_helper import get_infer_reader
+from utils.static_ps.reader_helper_hdfs import get_infer_reader
 from utils.static_ps.program_helper import get_model, get_strategy, set_dump_config
 from utils.static_ps.metric_helper import set_zero, get_global_auc
 from utils.static_ps.common_ps import YamlHelper, is_distributed_env
@@ -273,7 +273,9 @@ class Main(object):
         epoch_time = time.time() - epoch_start_time
         logger.info(
             "using time {} second, ips  {}/sec.".format(epoch_time, self.count_method))
-
+        while True:
+            time.sleep(300)
+            continue;
         if reader_type == "InmemoryDataset":
             self.reader.release_memory()
 
@@ -325,6 +327,7 @@ class Main(object):
             debug=debug,
             fetch_handler=fetch_handler)
         fetch_handler.finish()
+        
 
 
     def heter_train_loop(self, epoch):