Add attributes to dataloader to make it more consistent with Pytorch loader

deeplake/enterprise/dataloader.py

@@ -108,8 +108,10 @@ def __init__(
 
         # torch.utils.data.DataLoader attributes
         self.__initialized = True
+        self._IterableDataset_len_called = None
         self._iterator = None
 
+
     @property
     def batch_size(self):
         return self._batch_size or 1
@@ -130,14 +132,51 @@ def prefetch_factor(self):
     def pin_memory(self):
         return False
 
+    @property
+    def pin_memory_device(self):
+        return ""
+
     @property
     def timeout(self):
         return 0
 
+    @property
+    def worker_init_fn(self):
+        return None
+
+    @property
+    def multiprocessing_context(self):
+        return None
+
+    @property
+    def _dataset_kind(self):
+        return 1
+
     @property
     def sampler(self):
         return _InfiniteConstantSampler()
 
+    @property
+    def batch_sampler(self):
+        return None
+
+    @property
+    def generator(self):
+        return None
+
+    @property
+    def persistent_workers(self):
+        return self._persistent_workers or False
+
+    @property
+    def _auto_collation(self):
+        return False
+
+    @property
+    def _index_sampler(self):
+        return self.sampler
+
+
     @property
     def collate_fn(self):
         return get_collate_fn(self._collate, self._mode)