Add Instance Methods to PyTorch Frontend #3612 - sinc #21142 (#21144)

ivy/functional/frontends/torch/tensor.py

@@ -1752,6 +1752,18 @@ def quantile(self, q, dim=None, keepdim=False, *, interpolation="linear", out=No
             self, q, axis=dim, keepdims=keepdim, interpolation=interpolation, out=out
         )
 
+    @with_unsupported_dtypes(
+        {
+            "2.0.1 and below": (
+                "float16",
+                "bfloat16",
+            )
+        },
+        "torch",
+    )
+    def sinc(self):
+        return torch_frontend.sinc(self)
+
 
 class Size(tuple):
     def __new__(cls, iterable=()):

ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py

@@ -11929,3 +11929,38 @@ def test_torch_tensor_quantile(
         method_flags=method_flags,
         on_device=on_device,
     )
+
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="sinc",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_torch_instance_sinc(
+    *,
+    dtype_and_x,
+    frontend,
+    backend_fw,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+):
+    input_dtype, x = dtype_and_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,
+        backend_to_test=backend_fw,
+        on_device=on_device,
+    )