tfds decoder test

official/vision/beta/projects/yolo/tasks/image_classification.py

@@ -19,7 +19,8 @@ from official.core import base_task
 from official.core import input_reader
 from official.core import task_factory
 from official.modeling import tf_utils
-from official.vision.beta.projects.yolo.configs import darknet_classification as exp_cfg
+from official.vision.beta.configs import image_classification as exp_cfg
+from official.vision.beta.projects.yolo.dataloaders import classification_input as cli
 from official.vision.beta.dataloaders import classification_input
 from official.vision.beta.modeling import factory
 
@@ -52,7 +53,13 @@ class ImageClassificationTask(base_task.Task):
     num_classes = self.task_config.model.num_classes
     input_size = self.task_config.model.input_size
 
-    decoder = classification_input.Decoder()
+    if params.tfds_name != None: 
+      tf.print("i am here for training using tfds")
+      decoder = cli.Decoder()
+    else:
+      tf.print("i am here for regular input")
+      decoder = classification_input.Decoder()
+      
     parser = classification_input.Parser(
         output_size=input_size[:2],
         num_classes=num_classes,
@@ -201,3 +208,5 @@ class ImageClassificationTask(base_task.Task):
   def inference_step(self, inputs, model):
     """Performs the forward step."""
     return model(inputs, training=False)
+
+

official/vision/beta/tasks/image_classification.py

@@ -20,7 +20,6 @@ from official.core import input_reader
 from official.core import task_factory
 from official.modeling import tf_utils
 from official.vision.beta.configs import image_classification as exp_cfg
-from official.vision.beta.projects.yolo.dataloaders import classification_input as cli
 from official.vision.beta.dataloaders import classification_input
 from official.vision.beta.modeling import factory
 
@@ -53,12 +52,7 @@ class ImageClassificationTask(base_task.Task):
     num_classes = self.task_config.model.num_classes
     input_size = self.task_config.model.input_size
 
-    if params.tfds_name != None: 
-      tf.print("i am here for training using tfds")
-      decoder = cli.Decoder()
-    else:
-      tf.print("i am here for regular input")
-      decoder = classification_input.Decoder()
+    decoder = classification_input.Decoder()
 
     parser = classification_input.Parser(
         output_size=input_size[:2],