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Bump pyarrow from 13.0.0 to 14.0.1 #501

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merged 1 commit into from
Nov 17, 2023

Bump pyarrow from 13.0.0 to 14.0.1

5f09f0d
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Merged

Bump pyarrow from 13.0.0 to 14.0.1 #501

Bump pyarrow from 13.0.0 to 14.0.1
5f09f0d
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Jenkins - ci.inria.fr / Tests / Functional tests / GPU / Train tests Linux failed Nov 16, 2023 in 0s

failed: 9, passed: 2

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test_train_ae.test_train_ae[image_ae]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_ae_image_ae_0')
test_name = 'image_ae'

    def test_train_ae(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = base_dir / "train" / "out"
        # tmp_out_dir.mkdir(parents=True)
    
        clean_folder(tmp_out_dir, recreate=True)
    
        labels_path = str(input_dir / "labels_list" / "2_fold")
        config_path = str(input_dir / "train_config.toml")
        if test_name == "image_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
                "--split",
                "1",
            ]
        elif test_name == "patch_multi_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
                "--multi_network",
            ]
        elif test_name == "roi_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
            ]
        elif test_name == "slice_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_ae.py:95: AssertionError

test_train_ae.test_train_ae[patch_multi_ae]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_ae_patch_multi_ae_0')
test_name = 'patch_multi_ae'

    def test_train_ae(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = base_dir / "train" / "out"
        # tmp_out_dir.mkdir(parents=True)
    
        clean_folder(tmp_out_dir, recreate=True)
    
        labels_path = str(input_dir / "labels_list" / "2_fold")
        config_path = str(input_dir / "train_config.toml")
        if test_name == "image_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
                "--split",
                "1",
            ]
        elif test_name == "patch_multi_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
                "--multi_network",
            ]
        elif test_name == "roi_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
            ]
        elif test_name == "slice_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_ae.py:95: AssertionError

test_train_ae.test_train_ae[roi_ae]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_ae_roi_ae_0')
test_name = 'roi_ae'

    def test_train_ae(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = base_dir / "train" / "out"
        # tmp_out_dir.mkdir(parents=True)
    
        clean_folder(tmp_out_dir, recreate=True)
    
        labels_path = str(input_dir / "labels_list" / "2_fold")
        config_path = str(input_dir / "train_config.toml")
        if test_name == "image_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
                "--split",
                "1",
            ]
        elif test_name == "patch_multi_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
                "--multi_network",
            ]
        elif test_name == "roi_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
            ]
        elif test_name == "slice_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_ae.py:95: AssertionError

test_train_ae.test_train_ae[slice_ae]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_ae_slice_ae_0')
test_name = 'slice_ae'

    def test_train_ae(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = base_dir / "train" / "out"
        # tmp_out_dir.mkdir(parents=True)
    
        clean_folder(tmp_out_dir, recreate=True)
    
        labels_path = str(input_dir / "labels_list" / "2_fold")
        config_path = str(input_dir / "train_config.toml")
        if test_name == "image_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
                "--split",
                "1",
            ]
        elif test_name == "patch_multi_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
                "--multi_network",
            ]
        elif test_name == "roi_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
            ]
        elif test_name == "slice_ae":
            split = [0, 0]
            test_input = [
                "train",
                "reconstruction",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                labels_path,
                str(tmp_out_dir),
                "-c",
                config_path,
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_ae.py:95: AssertionError

test_train_cnn.test_train_cnn[slice_cnn]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_cnn_slice_cnn_0')
test_name = 'slice_cnn'

    def test_train_cnn(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = tmp_path / "train" / "out"
        tmp_out_dir.mkdir(parents=True)
    
        labels_path = input_dir / "labels_list" / "2_fold"
        config_path = input_dir / "train_config.toml"
        split = "0"
    
        if test_name == "slice_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "image_cnn":
            split_ref = 1
            test_input = [
                "train",
                "regression",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "patch_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--split",
                split,
            ]
        elif test_name == "patch_multi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--multi_network",
            ]
        elif test_name == "roi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_cnn.py:108: AssertionError

test_train_cnn.test_train_cnn[image_cnn]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_cnn_image_cnn_0')
test_name = 'image_cnn'

    def test_train_cnn(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = tmp_path / "train" / "out"
        tmp_out_dir.mkdir(parents=True)
    
        labels_path = input_dir / "labels_list" / "2_fold"
        config_path = input_dir / "train_config.toml"
        split = "0"
    
        if test_name == "slice_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "image_cnn":
            split_ref = 1
            test_input = [
                "train",
                "regression",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "patch_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--split",
                split,
            ]
        elif test_name == "patch_multi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--multi_network",
            ]
        elif test_name == "roi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_cnn.py:108: AssertionError

test_train_cnn.test_train_cnn[patch_cnn]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_cnn_patch_cnn_0')
test_name = 'patch_cnn'

    def test_train_cnn(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = tmp_path / "train" / "out"
        tmp_out_dir.mkdir(parents=True)
    
        labels_path = input_dir / "labels_list" / "2_fold"
        config_path = input_dir / "train_config.toml"
        split = "0"
    
        if test_name == "slice_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "image_cnn":
            split_ref = 1
            test_input = [
                "train",
                "regression",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "patch_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--split",
                split,
            ]
        elif test_name == "patch_multi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--multi_network",
            ]
        elif test_name == "roi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_cnn.py:108: AssertionError

test_train_cnn.test_train_cnn[patch_multi_cnn]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_cnn_patch_multi_cnn0')
test_name = 'patch_multi_cnn'

    def test_train_cnn(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = tmp_path / "train" / "out"
        tmp_out_dir.mkdir(parents=True)
    
        labels_path = input_dir / "labels_list" / "2_fold"
        config_path = input_dir / "train_config.toml"
        split = "0"
    
        if test_name == "slice_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "image_cnn":
            split_ref = 1
            test_input = [
                "train",
                "regression",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "patch_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--split",
                split,
            ]
        elif test_name == "patch_multi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--multi_network",
            ]
        elif test_name == "roi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_cnn.py:108: AssertionError

test_train_cnn.test_train_cnn[roi_cnn]

assert False
Stack trace
cmdopt = {'input': '/mnt/data/clinicadl_data_ci/data_ci'}
tmp_path = PosixPath('/local2/ci/tmp/test_train_cnn_roi_cnn_0')
test_name = 'roi_cnn'

    def test_train_cnn(cmdopt, tmp_path, test_name):
        base_dir = Path(cmdopt["input"])
        input_dir = base_dir / "train" / "in"
        ref_dir = base_dir / "train" / "ref"
        tmp_out_dir = tmp_path / "train" / "out"
        tmp_out_dir.mkdir(parents=True)
    
        labels_path = input_dir / "labels_list" / "2_fold"
        config_path = input_dir / "train_config.toml"
        split = "0"
    
        if test_name == "slice_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_slice"),
                "t1-linear_crop-True_mode-slice.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "image_cnn":
            split_ref = 1
            test_input = [
                "train",
                "regression",
                str(input_dir / "caps_image"),
                "t1-linear_crop-True_mode-image.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        elif test_name == "patch_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--split",
                split,
            ]
        elif test_name == "patch_multi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_patch"),
                "t1-linear_crop-True_mode-patch.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
                "--multi_network",
            ]
        elif test_name == "roi_cnn":
            split_ref = 0
            test_input = [
                "train",
                "classification",
                str(input_dir / "caps_roi"),
                "t1-linear_crop-True_mode-roi.json",
                str(labels_path),
                str(tmp_out_dir),
                "-c",
                str(config_path),
            ]
        else:
            raise NotImplementedError(f"Test {test_name} is not implemented.")
    
        if tmp_out_dir.is_dir():
            shutil.rmtree(tmp_out_dir)
    
        flag_error = not os.system("clinicadl " + " ".join(test_input))
>       assert flag_error
E       assert False

test_train_cnn.py:108: AssertionError