feat: add unflatten as torch frontend Tensor method and the test

tests pass.

ivy/functional/frontends/torch/tensor.py

@@ -823,6 +823,9 @@ def positive(self):
     def pow(self, exponent):
         return torch_frontend.pow(self, exponent)
 
+    def unflatten(self, dim, sizes):
+        return torch_frontend.unflatten(self, dim, sizes)
+
     @with_unsupported_dtypes({"2.2 and below": ("bfloat16",)}, "torch")
     def pow_(self, exponent):
         self.ivy_array = self.pow(exponent).ivy_array

ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py

@@ -21,6 +21,7 @@
 
 # local
 import ivy_tests.test_ivy.helpers as helpers
+from ivy_tests.test_ivy.helpers.hypothesis_helpers.general_helpers import sizes_
 from ivy_tests.test_ivy.test_frontends.test_torch.test_blas_and_lapack_ops import (
     _get_dtype_and_3dbatch_matrices,
     _get_dtype_input_and_matrices,
@@ -13800,6 +13801,54 @@ def test_torch_unbind(
     )
 
 
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="unflatten",
+    shape=st.shared(helpers.get_shape(min_num_dims=1), key="shape"),
+    dtype_and_values=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_num_dims=1,
+        shape_key="shape",
+    ),
+    axis=helpers.get_axis(
+        shape=st.shared(helpers.get_shape(min_num_dims=1), key="shape"),
+        force_int=True,
+    ),
+)
+def test_torch_unflatten(
+    *,
+    dtype_and_values,
+    on_device,
+    frontend,
+    backend_fw,
+    shape,
+    axis,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+):
+    dtype, x = dtype_and_values
+    sizes = sizes_(shape, axis)
+    helpers.test_frontend_method(
+        init_input_dtypes=dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=dtype,
+        method_all_as_kwargs_np={
+            "dim": axis,
+            "sizes": sizes,
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # unfold
 @handle_frontend_method(
     class_tree=CLASS_TREE,