110a17a4d96d21cecf449073c9b66e1c888d2573,test/test_foreach.py,TestForeach,test_bool_scalarlist,#TestForeach#Any#Any#,668

Before Change

                        return

                    if foreach_bin_op == torch._foreach_sub:
                        if self.device_type == "cpu":
                            // see TODO[Fix scalar list]
                            res = foreach_bin_op(tensors, scalars)
                            if dtype in torch.testing.integral_types():
                                self.assertEqual(res, [r.to(torch.float32) for r in [torch_bin_op(t, 1) for t in tensors]])

                                with self.assertRaisesRegex(RuntimeError, "result type Float can"t be cast to the "):
                                    foreach_bin_op_(tensors, scalars)
                            else:
                                self.assertEqual(res, [torch_bin_op(t, 1) for t in tensors])
                                foreach_bin_op_(tensors, scalars)
                                self.assertEqual(res, tensors)
                        else:
                            // see TODO[Fix scalar list]
                            res = foreach_bin_op(tensors, scalars)
                            if dtype in torch.testing.integral_types():
                                self.assertEqual(res, [r.to(dtype) for r in [torch_bin_op(t, 1) for t in tensors]])
                            else:
                                self.assertEqual(res, [torch_bin_op(t, 1) for t in tensors])

                            foreach_bin_op_(tensors, scalars)
                            self.assertEqual(res, tensors)
                    else:
                        if self.device_type == "cpu":
                            expected = [torch_bin_op(t, s) for t, s in zip(tensors, scalars)]
                            res = foreach_bin_op(tensors, scalars)

After Change

                            foreach_bin_op_(tensors, scalars)
                        return
                    else:
                        if foreach_bin_op == torch._foreach_sub:
                            with self.assertRaisesRegex(RuntimeError, "Subtraction, the `-` operator, with two bool tensors"):
                                foreach_bin_op_(tensors, scalars)

                            with self.assertRaisesRegex(RuntimeError, "Subtraction, the `-` operator, with two bool tensors"):
                                foreach_bin_op(tensors, scalars)
                        else:
                            expected = [torch_bin_op(t, s) for t, s in zip(tensors, scalars)]
                            res = foreach_bin_op(tensors, scalars)
                            self.assertEqual(res, expected)

                            if foreach_bin_op_ == torch._foreach_div_:
                                with self.assertRaisesRegex(RuntimeError, "result type Float can"t be cast to the desired"):
                                    foreach_bin_op_(tensors, scalars)
                            else:
                                foreach_bin_op_(tensors, scalars)
                                self.assertEqual(res, tensors)
                else:
                    // we dont support complex types on CUDA for now
                    if (dtype in torch.testing.get_all_complex_dtypes()) and self.device_type == "cuda":
                        with self.assertRaisesRegex(RuntimeError, "not implemented for"):

Instances