Added sqrt_ function to torch frontend

ivy/functional/frontends/torch/tensor.py

@@ -675,6 +675,11 @@ def clamp_(self, min=None, max=None, *, out=None):
     def sqrt(self):
         return torch_frontend.sqrt(self._ivy_array)
 
+    @with_unsupported_dtypes({"1.11.0 and below": ("float16", "bfloat16")}, "torch")
+    def sqrt_(self):
+        self._ivy_array = self.sqrt().ivy_array
+        return self
+
     def where(self, condition, other):
         # TODO: replace with torch_frontend.where when it's added
         return torch_frontend.tensor(ivy.where(condition, self._ivy_array, other))

ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py

@@ -5009,6 +5009,37 @@ def test_torch_instance_sqrt(
     )
 
 
+# sqrt_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="sqrt_",
+    dtype_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_torch_instance_sqrt_(
+    dtype_x,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x = dtype_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={"data": x[0]},
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # index_select
 @handle_frontend_method(
     class_tree=CLASS_TREE,