no bool parameter parser in wide_and_deep

mindspore/nn/layer/embedding.py

@@ -129,9 +129,9 @@ class EmbeddingLookup(Cell):
         embedding_size (int): The size of each embedding vector.
         param_init (str): The initialize way of embedding table. Default: 'normal'.
         target (str): Specify the target where the op is executed. The value should in
-        ['DEVICE', 'CPU']. Default: 'CPU'.
+            ['DEVICE', 'CPU']. Default: 'CPU'.
         slice_mode (str): The slicing way in semi auto parallel/auto parallel. The value should get through
-        nn.EmbeddingLookUpSplitMode. Default: 'batch_slice'.
+            nn.EmbeddingLookUpSplitMode. Default: nn.EmbeddingLookUpSplitMode.BATCH_SLICE.
         manual_shapes (tuple): The accompaniment array in field slice mode.
 
     Inputs:

model_zoo/official/recommend/wide_and_deep/src/config.py

@@ -25,7 +25,7 @@ def argparse_init():
     parser.add_argument("--data_path", type=str, default="./test_raw_data/",
                         help="This should be set to the same directory given to the data_download's data_dir argument")
     parser.add_argument("--epochs", type=int, default=15, help="Total train epochs")
-    parser.add_argument("--full_batch", type=bool, default=False, help="Enable loading the full batch ")
+    parser.add_argument("--full_batch", type=int, default=0, help="Enable loading the full batch ")
     parser.add_argument("--batch_size", type=int, default=16000, help="Training batch size.")
     parser.add_argument("--eval_batch_size", type=int, default=16000, help="Eval batch size.")
     parser.add_argument("--field_size", type=int, default=39, help="The number of features.")
@@ -88,7 +88,7 @@ class WideDeepConfig():
         self.device_target = args.device_target
         self.data_path = args.data_path
         self.epochs = args.epochs
-        self.full_batch = args.full_batch
+        self.full_batch = bool(args.full_batch)
         self.batch_size = args.batch_size
         self.eval_batch_size = args.eval_batch_size
         self.field_size = args.field_size

model_zoo/official/recommend/wide_and_deep_multitable/src/config.py

@@ -31,7 +31,7 @@ def argparse_init():
     parser.add_argument("--adam_lr", type=float, default=0.003)  # The Adam lr
     parser.add_argument("--ftrl_lr", type=float, default=0.1)  # The ftrl lr.
     parser.add_argument("--l2_coef", type=float, default=0.0)  # The l2 coefficient.
-    parser.add_argument("--is_tf_dataset", type=bool, default=True)  # The l2 coefficient.
+    parser.add_argument("--is_tf_dataset", type=int, default=1)  # Is tf_dataset.
     parser.add_argument("--dropout_flag", type=int, default=1) # The dropout rate
 
     parser.add_argument("--output_path", type=str, default="./output/")  # The location of the output file.
@@ -87,7 +87,7 @@ class WideDeepConfig():
         self.l2_coef = args.l2_coef
         self.ftrl_lr = args.ftrl_lr
         self.adam_lr = args.adam_lr
-        self.is_tf_dataset = args.is_tf_dataset
+        self.is_tf_dataset = bool(args.is_tf_dataset)
 
         self.output_path = args.output_path
         self.eval_file_name = args.eval_file_name