Use libdeeplake batch requests for getting bytes. (#2783)

* Switch to batch request for indra tensor bytes.

* Bump libdeeplake version.

* Fixed tests.

deeplake/core/dataset/deeplake_query_tensor.py

@@ -78,20 +78,21 @@ def numpy(
 
     def text(self, fetch_chunks: bool = False):
         """Return text data. Only applicable for tensors with 'text' base htype."""
+        bs = self.indra_tensor.bytes()
         if self.ndim == 1:
-            return self.indra_tensor.bytes().decode()
-        return list(
-            self.indra_tensor[i].bytes().decode() for i in range(len(self.indra_tensor))
-        )
+            return bs.decode()
+        if isinstance(bs, bytes):
+            return [bs.decode()]
+        return list(b.decode() for b in bs)
 
     def dict(self, fetch_chunks: bool = False):
         """Return json data. Only applicable for tensors with 'json' base htype."""
+        bs = self.indra_tensor.bytes()
         if self.ndim == 1:
-            return json.loads(self.indra_tensor.bytes().decode())
-        return list(
-            json.loads(self.indra_tensor[i].bytes().decode())
-            for i in range(len(self.indra_tensor))
-        )
+            return json.loads(bs.decode())
+        if isinstance(bs, bytes):
+            return [json.loads(bs.decode())]
+        return list(json.loads(b.decode()) for b in self.indra_tensor.bytes())
 
     @property
     def dtype(self):

setup.py

@@ -70,7 +70,7 @@ def libdeeplake_available():
 extras_require["all"] = [req_map[r] for r in all_extras]
 
 if libdeeplake_available():
-    libdeeplake = "libdeeplake==0.0.101"
+    libdeeplake = "libdeeplake==0.0.104"
     extras_require["enterprise"] = [libdeeplake, "pyjwt"]
     extras_require["all"].append(libdeeplake)
     install_requires.append(libdeeplake)