Add cuda pinned place branch in slice op GetExpectedKernelType (#26027)

* add cuda pinned place branch

* add unittest

* add skip when not gpu

paddle/fluid/operators/slice_op.cc

@@ -155,6 +155,10 @@ class SliceOp : public framework::OperatorWithKernel {
           in_tensor.IsInitialized(), true,
           platform::errors::InvalidArgument(
               "The tensor Input (Input) of Slice op is not initialized."));
+      // NOTE: cuda pinned tensor need to copy its data to target place
+      if (platform::is_cuda_pinned_place(in_tensor.place())) {
+        return framework::OpKernelType(in_tensor.type(), ctx.device_context());
+      }
       return framework::OpKernelType(in_tensor.type(), in_tensor.place());
     }
     return framework::OpKernelType(

python/paddle/fluid/tests/unittests/test_slice_op.py

@@ -663,5 +663,21 @@ class TestImperativeVarBaseGetItem(unittest.TestCase):
         self.assertRaises(Exception, test_float_in_index)
 
 
+@unittest.skipIf(not core.is_compiled_with_cuda(),
+                 "core is not compiled with CUDA")
+class TestImperativeCUDAPinnedInput(unittest.TestCase):
+    def test_input_cuda_pinned_var(self):
+        with fluid.dygraph.guard():
+            data = np.random.random((2, 80, 16128)).astype('float32')
+            var = core.VarBase(
+                value=data,
+                name='',
+                persistable=False,
+                place=fluid.CUDAPinnedPlace(),
+                zero_copy=False)
+            sliced = var[:, 10:, :var.shape[1]]
+            self.assertEqual(sliced.shape, [2, 70, 80])
+
+
 if __name__ == '__main__':
     unittest.main()