feat: added the tensor operations for slicing, mutations, joinings and indexing

ivy/data_classes/array/experimental/manipulation.py

@@ -1080,3 +1080,29 @@ def fill_diagonal(
         ivy.fill_diag also applies to this method with minimal changes.
         """
         return ivy.fill_diagonal(self._data, v, wrap=wrap)
+
+
+def tensor_ops(tensor, operation_type, *args):
+    if operation_type == "index":
+        if len(args) != 1:
+            raise ValueError
+        index = args[0]
+        return tensor[index]
+    elif operation_type == "slice":
+        if len(args) != 2:
+            raise ValueError
+        start, end = args
+        return tensor[start:end]
+    elif operation_type == "join":
+        if len(args) != 1:
+            raise ValueError
+        other_tensor = args[0]
+        return ivy.cat((tensor, other_tensor), dim=0)
+    elif operation_type == "mutate":
+        if len(args) != 1:
+            raise ValueError
+        factor = args[0]
+        tensor.mul_(factor)
+        return tensor
+    else:
+        raise ValueError

ivy/data_classes/container/experimental/manipulation.py

@@ -2996,3 +2996,30 @@ def fill_diagonal(
             v,
             wrap=wrap,
         )
+
+
+@staticmethod
+def tensor_ops(tensor, operation_type, *args):
+    if operation_type == "index":
+        if len(args) != 1:
+            raise ValueError
+        index = args[0]
+        return tensor[index]
+    elif operation_type == "slice":
+        if len(args) != 2:
+            raise ValueError
+        start, end = args
+        return tensor[start:end]
+    elif operation_type == "join":
+        if len(args) != 1:
+            raise ValueError
+        other_tensor = args[0]
+        return ivy.cat((tensor, other_tensor), dim=0)
+    elif operation_type == "mutate":
+        if len(args) != 1:
+            raise ValueError
+        factor = args[0]
+        tensor.mul_(factor)
+        return tensor
+    else:
+        raise ValueError

ivy/functional/backends/jax/experimental/manipulation.py

@@ -416,3 +416,29 @@ def fill_diagonal(
     a = a.at[:end:step].set(jnp.array(v).astype(a.dtype))
     a = jnp.reshape(a, shape)
     return a
+
+
+def tensor_ops(tensor, operation_type, *args):
+    if operation_type == "index":
+        if len(args) != 1:
+            raise ValueError
+        index = args[0]
+        return tensor[index]
+    elif operation_type == "slice":
+        if len(args) != 2:
+            raise ValueError
+        start, end = args
+        return tensor[start:end]
+    elif operation_type == "join":
+        if len(args) != 1:
+            raise ValueError
+        other_tensor = args[0]
+        return ivy.cat((tensor, other_tensor), dim=0)
+    elif operation_type == "mutate":
+        if len(args) != 1:
+            raise ValueError
+        factor = args[0]
+        tensor.mul_(factor)
+        return tensor
+    else:
+        raise ValueError

ivy/functional/backends/numpy/experimental/manipulation.py

@@ -505,3 +505,29 @@ def fill_diagonal(
 ) -> np.ndarray:
     np.fill_diagonal(a, v, wrap=wrap)
     return a
+
+
+def tensor_ops(tensor, operation_type, *args):
+    if operation_type == "index":
+        if len(args) != 1:
+            raise ValueError
+        index = args[0]
+        return tensor[index]
+    elif operation_type == "slice":
+        if len(args) != 2:
+            raise ValueError
+        start, end = args
+        return tensor[start:end]
+    elif operation_type == "join":
+        if len(args) != 1:
+            raise ValueError
+        other_tensor = args[0]
+        return ivy.cat((tensor, other_tensor), dim=0)
+    elif operation_type == "mutate":
+        if len(args) != 1:
+            raise ValueError
+        factor = args[0]
+        tensor.mul_(factor)
+        return tensor
+    else:
+        raise ValueError

ivy/functional/backends/tensorflow/experimental/manipulation.py

@@ -367,3 +367,29 @@ def fill_diagonal(
     a = tf.tensor_scatter_nd_update(a, indices, ups)
     a = tf.reshape(a, shape)
     return a
+
+
+def tensor_ops(tensor, operation_type, *args):
+    if operation_type == "index":
+        if len(args) != 1:
+            raise ValueError
+        index = args[0]
+        return tensor[index]
+    elif operation_type == "slice":
+        if len(args) != 2:
+            raise ValueError
+        start, end = args
+        return tensor[start:end]
+    elif operation_type == "join":
+        if len(args) != 1:
+            raise ValueError
+        other_tensor = args[0]
+        return ivy.cat((tensor, other_tensor), dim=0)
+    elif operation_type == "mutate":
+        if len(args) != 1:
+            raise ValueError
+        factor = args[0]
+        tensor.mul_(factor)
+        return tensor
+    else:
+        raise ValueError

ivy/functional/backends/torch/experimental/manipulation.py

@@ -395,3 +395,29 @@ def fill_diagonal(
     a = torch.where(w, v, a)
     a = torch.reshape(a, shape)
     return a
+
+
+def tensor_ops(tensor, operation_type, *args):
+    if operation_type == "index":
+        if len(args) != 1:
+            raise ValueError
+        index = args[0]
+        return tensor[index]
+    elif operation_type == "slice":
+        if len(args) != 2:
+            raise ValueError
+        start, end = args
+        return tensor[start:end]
+    elif operation_type == "join":
+        if len(args) != 1:
+            raise ValueError
+        other_tensor = args[0]
+        return ivy.cat((tensor, other_tensor), dim=0)
+    elif operation_type == "mutate":
+        if len(args) != 1:
+            raise ValueError
+        factor = args[0]
+        tensor.mul_(factor)
+        return tensor
+    else:
+        raise ValueError