feat: Add negative_ method to torch frontend (#23766)

ivy/functional/frontends/torch/tensor.py

@@ -956,6 +956,11 @@ def neg_(self):
     def negative(self):
         return torch_frontend.negative(self)
 
+    @with_unsupported_dtypes({"2.0.1 and below": ("bool", "bfloat16")}, "torch")
+    def negative_(self):
+        self.ivy_array = torch_frontend.negative(self).ivy_array
+        return self
+
     def int(self, memory_format=None):
         self.ivy_array = ivy.astype(self.ivy_array, ivy.int32, copy=False)
         return self

ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py

@@ -10296,6 +10296,44 @@ def test_torch_new_(
     )
 
 
+# negative_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="negative_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_value=-1e04,
+        max_value=1e04,
+        allow_inf=False,
+    ),
+)
+def test_torch_tensor_negative_(
+    dtype_and_x,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        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,
+    )
+
+
 # new_empty (not actually intuitive for testing)
 @handle_frontend_method(
     class_tree=CLASS_TREE,