avoid calling hyperparaneters twince

Author: Chuyang Deng

src/sagemaker/estimator.py

@@ -1113,8 +1113,9 @@ def _get_train_args(cls, estimator, inputs, experiment_config):
 
         config = _Job._load_config(inputs, estimator)
 
-        if estimator.hyperparameters() is not None:
-            hyperparameters = {str(k): str(v) for (k, v) in estimator.hyperparameters().items()}
+        current_hyperparameters = estimator.hyperparameters()
+        if current_hyperparameters is not None:
+            hyperparameters = {str(k): str(v) for (k, v) in current_hyperparameters.items()}
 
         train_args = config.copy()
         train_args["input_mode"] = estimator.input_mode

src/sagemaker/tensorflow/estimator.py

@@ -135,13 +135,9 @@ def __init__(
                 kwargs["enable_sagemaker_metrics"] = True
 
         super(TensorFlow, self).__init__(image_uri=image_uri, **kwargs)
-        self.disable_model_dir = False
         self.model_dir = model_dir
         self.distribution = distribution or {}
 
-        if self.model_dir is False:
-            self.disable_model_dir = True
-
         self._validate_args(py_version=py_version)
 
     def _validate_args(self, py_version):
@@ -319,7 +315,7 @@ def hyperparameters(self):
                 "custom_mpi_options", ""
             )
 
-        if not self.disable_model_dir:
+        if self.model_dir is not False:
             self.model_dir = self.model_dir or self._default_s3_path("model", mpi=mpi_enabled)
             additional_hyperparameters["model_dir"] = self.model_dir