diff --git a/examples/contrastive-image-text/clip_media_pipe.py b/examples/contrastive-image-text/clip_media_pipe.py
index 62c2a5651b..3ba1038fb8 100644
--- a/examples/contrastive-image-text/clip_media_pipe.py
+++ b/examples/contrastive-image-text/clip_media_pipe.py
@@ -24,28 +24,33 @@
 
 try:
     from habana_frameworks.mediapipe import fn
-    from habana_frameworks.mediapipe.backend.nodes import opnode_tensor_info
-    from habana_frameworks.mediapipe.backend.operator_specs import schema
     from habana_frameworks.mediapipe.media_types import dtype, ftype, imgtype, randomCropType, readerOutType
     from habana_frameworks.mediapipe.mediapipe import MediaPipe
-    from habana_frameworks.mediapipe.operators.media_nodes import MediaReaderNode
+    from habana_frameworks.mediapipe.operators.reader_nodes.reader_nodes import media_ext_reader_op_impl
     from habana_frameworks.mediapipe.operators.reader_nodes.read_image_from_dir import get_max_file
+    from habana_frameworks.mediapipe.operators.reader_nodes.reader_nodes import media_ext_reader_op_tensor_info
     from habana_frameworks.torch.hpu import get_device_name
 except ImportError:
     pass
 
+read_image_text_from_dataset_params = {
+    "label_dtype": dtype.UINT64,
+    "dataset": None,
+}
 
-class read_image_text_from_dataset(MediaReaderNode):
+class read_clip_data(media_ext_reader_op_impl):
     """
-    Class defining read image/text from directory node.
+    Class defining read image/text from clip dataset.
 
     """
 
-    def __init__(self, name, guid, device, inputs, params, cparams, node_attr):
-        super().__init__(name, guid, device, inputs, params, cparams, node_attr)
+    def __init__(self, params):
+        self.batch_size = 1
+        params = params['priv_params']
         self.meta_dtype = params["label_dtype"]
         self.dataset = params["dataset"]
         self.epoch = 0
+        self.batch_sampler_iter = None
 
         self.num_imgs_slice = len(ClipMediaPipe.batch_sampler.sampler)
         self.num_batches_slice = len(ClipMediaPipe.batch_sampler)
@@ -57,18 +62,16 @@ def __init__(self, name, guid, device, inputs, params, cparams, node_attr):
             self.max_file = get_max_file([img["path"] for img in self.dataset["image"]])
         logger.info(f"The largest file is {self.max_file}.")
 
+        self.iter_loc = 0
+
     def set_params(self, params):
         self.batch_size = params.batch_size
 
     def gen_output_info(self):
         out_info = []
-        o = opnode_tensor_info(dtype.NDT, np.array([self.batch_size], dtype=np.uint32), "")
-        out_info.append(o)
-        o = opnode_tensor_info(
-            self.meta_dtype, np.array([self.dataset.text_max_length, self.batch_size], dtype=np.uint32), ""
-        )
+        o = media_ext_reader_op_tensor_info(dtype.NDT, np.array([self.batch_size], dtype=np.uint32), "")
         out_info.append(o)
-        o = opnode_tensor_info(
+        o = media_ext_reader_op_tensor_info(
             self.meta_dtype, np.array([self.dataset.text_max_length, self.batch_size], dtype=np.uint32), ""
         )
         out_info.append(o)
@@ -111,28 +114,6 @@ def __next__(self):
 
         return img_list, input_id_list, attention_mask_list
 
-
-read_image_text_from_dataset_params = {
-    "label_dtype": dtype.UINT64,
-    "dataset": None,
-}
-schema.add_operator(
-    "ClipDataReader",
-    None,
-    0,
-    0,
-    [],
-    3,
-    read_image_text_from_dataset_params,
-    None,
-    read_image_text_from_dataset,
-    dtype.NDT,
-)
-op_class = fn.operator_add("ClipDataReader")
-op_class.__module__ = fn.__name__
-setattr(fn, "ClipDataReader", op_class)
-
-
 class ClipMediaPipe(MediaPipe):
     """
     Class defining clip media pipe:
@@ -160,8 +141,12 @@ def __init__(self, dataset=None, sampler=None, batch_size=512, drop_last=False,
         super(ClipMediaPipe, self).__init__(
             device=self.device, batch_size=batch_size, prefetch_depth=queue_depth, pipe_name=pipe_name
         )
-
-        self.input = fn.ClipDataReader(label_dtype=dtype.UINT32, dataset=self.dataset)
+        params = read_image_text_from_dataset_params.copy()
+        params['dataset'] = self.dataset
+        self.input = fn.MediaExtReaderOp(impl=read_clip_data,
+                                         num_outputs=3,
+                                         priv_params=params,
+                                        )
         def_output_image_size = [self.image_size, self.image_size]
         res_pp_filter = ftype.BICUBIC
         self.decode = fn.ImageDecoder(