From 0c98432d6b51d5ab44a2f8a4fb203f863d89189f Mon Sep 17 00:00:00 2001 From: YunLiu <55491388+KumoLiu@users.noreply.github.com> Date: Fri, 25 Apr 2025 21:55:37 +0800 Subject: [PATCH 1/7] part of #8421 remove deprecated functionality Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com> --- docs/source/metrics.rst | 1 - monai/bundle/scripts.py | 24 +-------------------- monai/bundle/workflows.py | 26 ---------------------- monai/metrics/__init__.py | 2 +- monai/metrics/generalized_dice.py | 15 +++---------- monai/metrics/hausdorff_distance.py | 30 +------------------------- monai/metrics/utils.py | 6 ++---- monai/networks/nets/swin_unetr.py | 12 ----------- monai/transforms/croppad/array.py | 6 +++--- monai/transforms/croppad/dictionary.py | 6 +++--- monai/transforms/utils.py | 8 +++---- 11 files changed, 18 insertions(+), 118 deletions(-) diff --git a/docs/source/metrics.rst b/docs/source/metrics.rst index 45e0827cf9..88fbea7ff0 100644 --- a/docs/source/metrics.rst +++ b/docs/source/metrics.rst @@ -98,7 +98,6 @@ Metrics `Hausdorff distance` -------------------- .. autofunction:: compute_hausdorff_distance -.. autofunction:: compute_percent_hausdorff_distance .. autoclass:: HausdorffDistanceMetric :members: diff --git a/monai/bundle/scripts.py b/monai/bundle/scripts.py index dbfc449edb..6b3643bb24 100644 --- a/monai/bundle/scripts.py +++ b/monai/bundle/scripts.py @@ -629,9 +629,6 @@ def download( _check_monai_version(bundle_dir_, name_) -@deprecated_arg("net_name", since="1.2", removed="1.5", msg_suffix="please use ``model`` instead.") -@deprecated_arg("net_kwargs", since="1.2", removed="1.5", msg_suffix="please use ``model`` instead.") -@deprecated_arg("return_state_dict", since="1.2", removed="1.5") def load( name: str, model: torch.nn.Module | None = None, @@ -650,10 +647,6 @@ def load( workflow_name: str | BundleWorkflow | None = None, args_file: str | None = None, copy_model_args: dict | None = None, - return_state_dict: bool = True, - net_override: dict | None = None, - net_name: str | None = None, - **net_kwargs: Any, ) -> object | tuple[torch.nn.Module, dict, dict] | Any: """ Load model weights or TorchScript module of a bundle. @@ -699,11 +692,6 @@ def load( workflow_name: specified bundle workflow name, should be a string or class, default to "ConfigWorkflow". args_file: a JSON or YAML file to provide default values for all the args in "download" function. copy_model_args: other arguments for the `monai.networks.copy_model_state` function. - return_state_dict: whether to return state dict, if True, return state_dict, else a corresponding network - from `_workflow.network_def` will be instantiated and load the achieved weights. - net_override: id-value pairs to override the parameters in the network of the bundle, default to `None`. - net_name: if not `None`, a corresponding network will be instantiated and load the achieved weights. - This argument only works when loading weights. net_kwargs: other arguments that are used to instantiate the network class defined by `net_name`. Returns: @@ -719,9 +707,6 @@ def load( when `model` and `net_name` are all `None`. """ - if return_state_dict and (model is not None or net_name is not None): - warnings.warn("Incompatible values: model and net_name are all specified, return state dict instead.") - bundle_dir_ = _process_bundle_dir(bundle_dir) net_override = {} if net_override is None else net_override copy_model_args = {} if copy_model_args is None else copy_model_args @@ -757,11 +742,8 @@ def load( warnings.warn(f"the state dictionary from {full_path} should be a dictionary but got {type(model_dict)}.") model_dict = get_state_dict(model_dict) - if return_state_dict: - return model_dict - _workflow = None - if model is None and net_name is None: + if model is None: bundle_config_file = bundle_dir_ / name / "configs" / f"{workflow_type}.json" if bundle_config_file.is_file(): _net_override = {f"network_def#{key}": value for key, value in net_override.items()} @@ -781,10 +763,6 @@ def load( return model_dict else: model = _workflow.network_def - elif net_name is not None: - net_kwargs["_target_"] = net_name - configer = ConfigComponent(config=net_kwargs) - model = configer.instantiate() # type: ignore model.to(device) # type: ignore diff --git a/monai/bundle/workflows.py b/monai/bundle/workflows.py index 75cf7b0b09..39cebbf84c 100644 --- a/monai/bundle/workflows.py +++ b/monai/bundle/workflows.py @@ -45,10 +45,6 @@ class BundleWorkflow(ABC): or "infer", "inference", "eval", "evaluation" for a inference workflow, other unsupported string will raise a ValueError. default to `None` for only using meta properties. - workflow: specifies the workflow type: "train" or "training" for a training workflow, - or "infer", "inference", "eval", "evaluation" for a inference workflow, - other unsupported string will raise a ValueError. - default to `None` for common workflow. properties_path: the path to the JSON file of properties. If `workflow_type` is specified, properties will be loaded from the file based on the provided `workflow_type` and meta. If no `workflow_type` is specified, properties will default to loading from "meta". If `properties_path` is None, default properties @@ -65,17 +61,9 @@ class BundleWorkflow(ABC): supported_train_type: tuple = ("train", "training") supported_infer_type: tuple = ("infer", "inference", "eval", "evaluation") - @deprecated_arg( - "workflow", - since="1.2", - removed="1.5", - new_name="workflow_type", - msg_suffix="please use `workflow_type` instead.", - ) def __init__( self, workflow_type: str | None = None, - workflow: str | None = None, properties_path: PathLike | None = None, meta_file: str | Sequence[str] | None = None, logging_file: str | None = None, @@ -102,7 +90,6 @@ def __init__( ) meta_file = None - workflow_type = workflow if workflow is not None else workflow_type if workflow_type is not None: if workflow_type.lower() in self.supported_train_type: workflow_type = "train" @@ -403,10 +390,6 @@ class ConfigWorkflow(BundleWorkflow): or "infer", "inference", "eval", "evaluation" for a inference workflow, other unsupported string will raise a ValueError. default to `None` for common workflow. - workflow: specifies the workflow type: "train" or "training" for a training workflow, - or "infer", "inference", "eval", "evaluation" for a inference workflow, - other unsupported string will raise a ValueError. - default to `None` for common workflow. properties_path: the path to the JSON file of properties. If `workflow_type` is specified, properties will be loaded from the file based on the provided `workflow_type` and meta. If no `workflow_type` is specified, properties will default to loading from "train". If `properties_path` is None, default properties @@ -419,13 +402,6 @@ class ConfigWorkflow(BundleWorkflow): """ - @deprecated_arg( - "workflow", - since="1.2", - removed="1.5", - new_name="workflow_type", - msg_suffix="please use `workflow_type` instead.", - ) def __init__( self, config_file: str | Sequence[str], @@ -436,11 +412,9 @@ def __init__( final_id: str = "finalize", tracking: str | dict | None = None, workflow_type: str | None = "train", - workflow: str | None = None, properties_path: PathLike | None = None, **override: Any, ) -> None: - workflow_type = workflow if workflow is not None else workflow_type if config_file is not None: _config_files = ensure_tuple(config_file) config_root_path = Path(_config_files[0]).parent diff --git a/monai/metrics/__init__.py b/monai/metrics/__init__.py index 7176f3311f..ae20903cfd 100644 --- a/monai/metrics/__init__.py +++ b/monai/metrics/__init__.py @@ -19,7 +19,7 @@ from .fid import FIDMetric, compute_frechet_distance from .froc import compute_fp_tp_probs, compute_fp_tp_probs_nd, compute_froc_curve_data, compute_froc_score from .generalized_dice import GeneralizedDiceScore, compute_generalized_dice -from .hausdorff_distance import HausdorffDistanceMetric, compute_hausdorff_distance, compute_percent_hausdorff_distance +from .hausdorff_distance import HausdorffDistanceMetric, compute_hausdorff_distance from .loss_metric import LossMetric from .meandice import DiceHelper, DiceMetric, compute_dice from .meaniou import MeanIoU, compute_iou diff --git a/monai/metrics/generalized_dice.py b/monai/metrics/generalized_dice.py index 516021949b..cecaab2efc 100644 --- a/monai/metrics/generalized_dice.py +++ b/monai/metrics/generalized_dice.py @@ -37,6 +37,8 @@ class GeneralizedDiceScore(CumulativeIterationMetric): reduction: Define mode of reduction to the metrics. Available reduction modes: {``"none"``, ``"mean"``, ``"sum"``, ``"mean_batch"``, ``"sum_batch"``, ``"mean_channel"``, ``"sum_channel"``}, default to ``"mean"``. if "none", will not do reduction. + Default value is changed from `MetricReduction.MEAN_BATCH` to `MetricReduction.MEAN` in v1.5.0. + Old versions computed `mean` when `mean_batch` was provided due to bug in reduction. weight_type: {``"square"``, ``"simple"``, ``"uniform"``}. Type of function to transform ground truth volume into a weight factor. Defaults to ``"square"``. @@ -44,21 +46,10 @@ class GeneralizedDiceScore(CumulativeIterationMetric): ValueError: When the `reduction` is not one of MetricReduction enum. """ - @deprecated_arg_default( - "reduction", - old_default=MetricReduction.MEAN_BATCH, - new_default=MetricReduction.MEAN, - since="1.4.0", - replaced="1.5.0", - msg_suffix=( - "Old versions computed `mean` when `mean_batch` was provided due to bug in reduction， " - "If you want to retain the old behavior (calculating the mean), please explicitly set the parameter to 'mean'." - ), - ) def __init__( self, include_background: bool = True, - reduction: MetricReduction | str = MetricReduction.MEAN_BATCH, + reduction: MetricReduction | str = MetricReduction.MEAN, weight_type: Weight | str = Weight.SQUARE, ) -> None: super().__init__() diff --git a/monai/metrics/hausdorff_distance.py b/monai/metrics/hausdorff_distance.py index d727eb0567..a86abd7aca 100644 --- a/monai/metrics/hausdorff_distance.py +++ b/monai/metrics/hausdorff_distance.py @@ -28,7 +28,7 @@ from .metric import CumulativeIterationMetric -__all__ = ["HausdorffDistanceMetric", "compute_hausdorff_distance", "compute_percent_hausdorff_distance"] +__all__ = ["HausdorffDistanceMetric", "compute_hausdorff_distance"] class HausdorffDistanceMetric(CumulativeIterationMetric): @@ -216,31 +216,3 @@ def _compute_percentile_hausdorff_distance( if 0 <= percentile <= 100: return torch.quantile(surface_distance, percentile / 100) raise ValueError(f"percentile should be a value between 0 and 100, get {percentile}.") - - -@deprecated(since="1.3.0", removed="1.5.0") -def compute_percent_hausdorff_distance( - edges_pred: np.ndarray, - edges_gt: np.ndarray, - distance_metric: str = "euclidean", - percentile: float | None = None, - spacing: int | float | np.ndarray | Sequence[int | float] | None = None, -) -> float: - """ - This function is used to compute the directed Hausdorff distance. - """ - - surface_distance: np.ndarray = get_surface_distance( # type: ignore - edges_pred, edges_gt, distance_metric=distance_metric, spacing=spacing - ) - - # for both pred and gt do not have foreground - if surface_distance.shape == (0,): - return np.nan - - if not percentile: - return surface_distance.max() # type: ignore[no-any-return] - - if 0 <= percentile <= 100: - return np.percentile(surface_distance, percentile) # type: ignore[no-any-return] - raise ValueError(f"percentile should be a value between 0 and 100, get {percentile}.") diff --git a/monai/metrics/utils.py b/monai/metrics/utils.py index 96d60c9098..c777cbabe1 100644 --- a/monai/metrics/utils.py +++ b/monai/metrics/utils.py @@ -131,9 +131,6 @@ def do_metric_reduction( return f, not_nans -@deprecated_arg_default( - name="always_return_as_numpy", since="1.3.0", replaced="1.5.0", old_default=True, new_default=False -) @deprecated_arg( name="always_return_as_numpy", since="1.5.0", @@ -146,7 +143,7 @@ def get_mask_edges( label_idx: int = 1, crop: bool = True, spacing: Sequence | None = None, - always_return_as_numpy: bool = True, + always_return_as_numpy: bool = False, ) -> tuple[NdarrayTensor, NdarrayTensor]: """ Compute edges from binary segmentation masks. This @@ -175,6 +172,7 @@ def get_mask_edges( otherwise `scipy`'s binary erosion is used to calculate the edges. always_return_as_numpy: whether to a numpy array regardless of the input type. If False, return the same type as inputs. + The default value is changed from `True` to `False` in v1.5.0. """ # move in the funciton to avoid using all the GPUs cucim_binary_erosion, has_cucim_binary_erosion = optional_import("cucim.skimage.morphology", name="binary_erosion") diff --git a/monai/networks/nets/swin_unetr.py b/monai/networks/nets/swin_unetr.py index 22e1e6f659..895a0ec5f5 100644 --- a/monai/networks/nets/swin_unetr.py +++ b/monai/networks/nets/swin_unetr.py @@ -50,16 +50,8 @@ class SwinUNETR(nn.Module): " """ - @deprecated_arg( - name="img_size", - since="1.3", - removed="1.5", - msg_suffix="The img_size argument is not required anymore and " - "checks on the input size are run during forward().", - ) def __init__( self, - img_size: Sequence[int] | int, in_channels: int, out_channels: int, patch_size: int = 2, @@ -83,10 +75,6 @@ def __init__( ) -> None: """ Args: - img_size: spatial dimension of input image. - This argument is only used for checking that the input image size is divisible by the patch size. - The tensor passed to forward() can have a dynamic shape as long as its spatial dimensions are divisible by 2**5. - It will be removed in an upcoming version. in_channels: dimension of input channels. out_channels: dimension of output channels. patch_size: size of the patch token. diff --git a/monai/transforms/croppad/array.py b/monai/transforms/croppad/array.py index d5ca876e98..fb40ce0f5a 100644 --- a/monai/transforms/croppad/array.py +++ b/monai/transforms/croppad/array.py @@ -809,13 +809,12 @@ def threshold_at_one(x): """ - @deprecated_arg_default("allow_smaller", old_default=True, new_default=False, since="1.2", replaced="1.5") def __init__( self, select_fn: Callable = is_positive, channel_indices: IndexSelection | None = None, margin: Sequence[int] | int = 0, - allow_smaller: bool = True, + allow_smaller: bool = False, return_coords: bool = False, k_divisible: Sequence[int] | int = 1, mode: str = PytorchPadMode.CONSTANT, @@ -830,7 +829,8 @@ def __init__( margin: add margin value to spatial dims of the bounding box, if only 1 value provided, use it for all dims. allow_smaller: when computing box size with `margin`, whether to allow the image edges to be smaller than the final box edges. If `False`, part of a padded output box might be outside of the original image, if `True`, - the image edges will be used as the box edges. Default to `True`. + the image edges will be used as the box edges. Default to `False`. + The default value is changed from `True` to `False` in v1.5.0. return_coords: whether return the coordinates of spatial bounding box for foreground. k_divisible: make each spatial dimension to be divisible by k, default to 1. if `k_divisible` is an int, the same `k` be applied to all the input spatial dimensions. diff --git a/monai/transforms/croppad/dictionary.py b/monai/transforms/croppad/dictionary.py index cea11d9676..9a4a90542a 100644 --- a/monai/transforms/croppad/dictionary.py +++ b/monai/transforms/croppad/dictionary.py @@ -716,7 +716,6 @@ class CropForegroundd(Cropd): for more information. """ - @deprecated_arg_default("allow_smaller", old_default=True, new_default=False, since="1.2", replaced="1.5") def __init__( self, keys: KeysCollection, @@ -724,7 +723,7 @@ def __init__( select_fn: Callable = is_positive, channel_indices: IndexSelection | None = None, margin: Sequence[int] | int = 0, - allow_smaller: bool = True, + allow_smaller: bool = False, k_divisible: Sequence[int] | int = 1, mode: SequenceStr = PytorchPadMode.CONSTANT, start_coord_key: str | None = "foreground_start_coord", @@ -744,7 +743,8 @@ def __init__( margin: add margin value to spatial dims of the bounding box, if only 1 value provided, use it for all dims. allow_smaller: when computing box size with `margin`, whether to allow the image edges to be smaller than the final box edges. If `False`, part of a padded output box might be outside of the original image, if `True`, - the image edges will be used as the box edges. Default to `True`. + the image edges will be used as the box edges. Default to `False`. + The default value is changed from `True` to `False` in v1.5.0. k_divisible: make each spatial dimension to be divisible by k, default to 1. if `k_divisible` is an int, the same `k` be applied to all the input spatial dimensions. mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``, diff --git a/monai/transforms/utils.py b/monai/transforms/utils.py index 1ff0abc27c..537a25cd47 100644 --- a/monai/transforms/utils.py +++ b/monai/transforms/utils.py @@ -1067,13 +1067,12 @@ def _create_translate( return array_func(affine) # type: ignore -@deprecated_arg_default("allow_smaller", old_default=True, new_default=False, since="1.2", replaced="1.5") def generate_spatial_bounding_box( img: NdarrayOrTensor, select_fn: Callable = is_positive, channel_indices: IndexSelection | None = None, margin: Sequence[int] | int = 0, - allow_smaller: bool = True, + allow_smaller: bool = False, ) -> tuple[list[int], list[int]]: """ Generate the spatial bounding box of foreground in the image with start-end positions (inclusive). @@ -1093,8 +1092,9 @@ def generate_spatial_bounding_box( of image. if None, select foreground on the whole image. margin: add margin value to spatial dims of the bounding box, if only 1 value provided, use it for all dims. allow_smaller: when computing box size with `margin`, whether to allow the image edges to be smaller than the - final box edges. If `True`, the bounding boxes edges are aligned with the input image edges, if `False`, - the bounding boxes edges are aligned with the final box edges. Default to `True`. + final box edges. If `True`, the bounding boxes edges are aligned with the input image edges, if `False`, + the bounding boxes edges are aligned with the final box edges. Default to `False`. + The default value is changed from `True` to `False` in v1.5.0. """ check_non_lazy_pending_ops(img, name="generate_spatial_bounding_box") From a106e72316ba483562c811a0405381bf52cb7f8a Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 25 Apr 2025 13:59:36 +0000 Subject: [PATCH 2/7] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- monai/bundle/scripts.py | 2 -- monai/bundle/workflows.py | 2 +- monai/metrics/generalized_dice.py | 2 +- monai/metrics/hausdorff_distance.py | 3 +-- monai/metrics/utils.py | 1 - monai/networks/nets/swin_unetr.py | 1 - monai/transforms/croppad/array.py | 1 - monai/transforms/croppad/dictionary.py | 2 +- monai/transforms/utils.py | 1 - 9 files changed, 4 insertions(+), 11 deletions(-) diff --git a/monai/bundle/scripts.py b/monai/bundle/scripts.py index 6b3643bb24..95c08e3ed3 100644 --- a/monai/bundle/scripts.py +++ b/monai/bundle/scripts.py @@ -31,7 +31,6 @@ from monai._version import get_versions from monai.apps.utils import _basename, download_url, extractall, get_logger -from monai.bundle.config_item import ConfigComponent from monai.bundle.config_parser import ConfigParser from monai.bundle.utils import DEFAULT_INFERENCE, DEFAULT_METADATA, merge_kv from monai.bundle.workflows import BundleWorkflow, ConfigWorkflow @@ -48,7 +47,6 @@ from monai.utils import ( IgniteInfo, check_parent_dir, - deprecated_arg, ensure_tuple, get_equivalent_dtype, min_version, diff --git a/monai/bundle/workflows.py b/monai/bundle/workflows.py index 39cebbf84c..e045e82ec5 100644 --- a/monai/bundle/workflows.py +++ b/monai/bundle/workflows.py @@ -27,7 +27,7 @@ from monai.bundle.properties import InferProperties, MetaProperties, TrainProperties from monai.bundle.utils import DEFAULT_EXP_MGMT_SETTINGS, EXPR_KEY, ID_REF_KEY, ID_SEP_KEY from monai.config import PathLike -from monai.utils import BundleProperty, BundlePropertyConfig, deprecated_arg, ensure_tuple +from monai.utils import BundleProperty, BundlePropertyConfig, ensure_tuple __all__ = ["BundleWorkflow", "ConfigWorkflow"] diff --git a/monai/metrics/generalized_dice.py b/monai/metrics/generalized_dice.py index cecaab2efc..05eb94af48 100644 --- a/monai/metrics/generalized_dice.py +++ b/monai/metrics/generalized_dice.py @@ -14,7 +14,7 @@ import torch from monai.metrics.utils import do_metric_reduction, ignore_background -from monai.utils import MetricReduction, Weight, deprecated_arg, deprecated_arg_default, look_up_option +from monai.utils import MetricReduction, Weight, deprecated_arg, look_up_option from .metric import CumulativeIterationMetric diff --git a/monai/metrics/hausdorff_distance.py b/monai/metrics/hausdorff_distance.py index a86abd7aca..ce885b95f7 100644 --- a/monai/metrics/hausdorff_distance.py +++ b/monai/metrics/hausdorff_distance.py @@ -20,11 +20,10 @@ from monai.metrics.utils import ( do_metric_reduction, get_edge_surface_distance, - get_surface_distance, ignore_background, prepare_spacing, ) -from monai.utils import MetricReduction, convert_data_type, deprecated +from monai.utils import MetricReduction, convert_data_type from .metric import CumulativeIterationMetric diff --git a/monai/metrics/utils.py b/monai/metrics/utils.py index c777cbabe1..972ec0061e 100644 --- a/monai/metrics/utils.py +++ b/monai/metrics/utils.py @@ -30,7 +30,6 @@ convert_to_numpy, convert_to_tensor, deprecated_arg, - deprecated_arg_default, ensure_tuple_rep, look_up_option, optional_import, diff --git a/monai/networks/nets/swin_unetr.py b/monai/networks/nets/swin_unetr.py index 895a0ec5f5..35d2db6887 100644 --- a/monai/networks/nets/swin_unetr.py +++ b/monai/networks/nets/swin_unetr.py @@ -25,7 +25,6 @@ from monai.networks.blocks import PatchEmbed, UnetOutBlock, UnetrBasicBlock, UnetrUpBlock from monai.networks.layers import DropPath, trunc_normal_ from monai.utils import ensure_tuple_rep, look_up_option, optional_import -from monai.utils.deprecate_utils import deprecated_arg rearrange, _ = optional_import("einops", name="rearrange") diff --git a/monai/transforms/croppad/array.py b/monai/transforms/croppad/array.py index fb40ce0f5a..fc0bafbcc4 100644 --- a/monai/transforms/croppad/array.py +++ b/monai/transforms/croppad/array.py @@ -51,7 +51,6 @@ TransformBackends, convert_data_type, convert_to_tensor, - deprecated_arg_default, ensure_tuple, ensure_tuple_rep, fall_back_tuple, diff --git a/monai/transforms/croppad/dictionary.py b/monai/transforms/croppad/dictionary.py index 9a4a90542a..462412686a 100644 --- a/monai/transforms/croppad/dictionary.py +++ b/monai/transforms/croppad/dictionary.py @@ -50,7 +50,7 @@ from monai.transforms.traits import LazyTrait, MultiSampleTrait from monai.transforms.transform import LazyTransform, MapTransform, Randomizable from monai.transforms.utils import is_positive -from monai.utils import MAX_SEED, Method, PytorchPadMode, deprecated_arg_default, ensure_tuple_rep +from monai.utils import MAX_SEED, Method, PytorchPadMode, ensure_tuple_rep __all__ = [ "Padd", diff --git a/monai/transforms/utils.py b/monai/transforms/utils.py index 537a25cd47..be5fdd512b 100644 --- a/monai/transforms/utils.py +++ b/monai/transforms/utils.py @@ -58,7 +58,6 @@ SplineMode, TraceKeys, TraceStatusKeys, - deprecated_arg_default, ensure_tuple, ensure_tuple_rep, ensure_tuple_size, From 815c500ffb2c8539b09de003bf21d6f742a542dc Mon Sep 17 00:00:00 2001 From: YunLiu <55491388+KumoLiu@users.noreply.github.com> Date: Sun, 27 Apr 2025 10:47:53 +0800 Subject: [PATCH 3/7] fix ci and format Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com> --- monai/bundle/scripts.py | 3 ++- monai/networks/nets/swin_unetr.py | 11 ++++------- monai/utils/jupyter_utils.py | 2 +- tests/networks/nets/test_swin_unetr.py | 26 ++++---------------------- 4 files changed, 11 insertions(+), 31 deletions(-) diff --git a/monai/bundle/scripts.py b/monai/bundle/scripts.py index 6b3643bb24..fcd941e76c 100644 --- a/monai/bundle/scripts.py +++ b/monai/bundle/scripts.py @@ -647,6 +647,7 @@ def load( workflow_name: str | BundleWorkflow | None = None, args_file: str | None = None, copy_model_args: dict | None = None, + net_override: dict | None = None, ) -> object | tuple[torch.nn.Module, dict, dict] | Any: """ Load model weights or TorchScript module of a bundle. @@ -692,7 +693,7 @@ def load( workflow_name: specified bundle workflow name, should be a string or class, default to "ConfigWorkflow". args_file: a JSON or YAML file to provide default values for all the args in "download" function. copy_model_args: other arguments for the `monai.networks.copy_model_state` function. - net_kwargs: other arguments that are used to instantiate the network class defined by `net_name`. + net_override: id-value pairs to override the parameters in the network of the bundle, default to `None`. Returns: 1. If `load_ts_module` is `False` and `model` is `None`, diff --git a/monai/networks/nets/swin_unetr.py b/monai/networks/nets/swin_unetr.py index 895a0ec5f5..b3ee041210 100644 --- a/monai/networks/nets/swin_unetr.py +++ b/monai/networks/nets/swin_unetr.py @@ -101,13 +101,13 @@ def __init__( Examples:: # for 3D single channel input with size (96,96,96), 4-channel output and feature size of 48. - >>> net = SwinUNETR(img_size=(96,96,96), in_channels=1, out_channels=4, feature_size=48) + >>> net = SwinUNETR(in_channels=1, out_channels=4, feature_size=48) # for 3D 4-channel input with size (128,128,128), 3-channel output and (2,4,2,2) layers in each stage. - >>> net = SwinUNETR(img_size=(128,128,128), in_channels=4, out_channels=3, depths=(2,4,2,2)) + >>> net = SwinUNETR(in_channels=4, out_channels=3, depths=(2,4,2,2)) # for 2D single channel input with size (96,96), 2-channel output and gradient checkpointing. - >>> net = SwinUNETR(img_size=(96,96), in_channels=3, out_channels=2, use_checkpoint=True, spatial_dims=2) + >>> net = SwinUNETR(in_channels=3, out_channels=2, use_checkpoint=True, spatial_dims=2) """ @@ -118,12 +118,9 @@ def __init__( self.patch_size = patch_size - img_size = ensure_tuple_rep(img_size, spatial_dims) patch_sizes = ensure_tuple_rep(self.patch_size, spatial_dims) window_size = ensure_tuple_rep(window_size, spatial_dims) - self._check_input_size(img_size) - if not (0 <= drop_rate <= 1): raise ValueError("dropout rate should be between 0 and 1.") @@ -1097,7 +1094,7 @@ def filter_swinunetr(key, value): from monai.networks.utils import copy_model_state from monai.networks.nets.swin_unetr import SwinUNETR, filter_swinunetr - model = SwinUNETR(img_size=(96, 96, 96), in_channels=1, out_channels=3, feature_size=48) + model = SwinUNETR(in_channels=1, out_channels=3, feature_size=48) resource = ( "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/ssl_pretrained_weights.pth" ) diff --git a/monai/utils/jupyter_utils.py b/monai/utils/jupyter_utils.py index c93e93dcb9..b1b43a6767 100644 --- a/monai/utils/jupyter_utils.py +++ b/monai/utils/jupyter_utils.py @@ -234,7 +234,7 @@ def plot_engine_status( def _get_loss_from_output( - output: list[torch.Tensor | dict[str, torch.Tensor]] | dict[str, torch.Tensor] | torch.Tensor, + output: list[torch.Tensor | dict[str, torch.Tensor]] | dict[str, torch.Tensor] | torch.Tensor ) -> torch.Tensor: """Returns a single value from the network output, which is a dict or tensor.""" diff --git a/tests/networks/nets/test_swin_unetr.py b/tests/networks/nets/test_swin_unetr.py index 2c4532ecc4..d321c777ba 100644 --- a/tests/networks/nets/test_swin_unetr.py +++ b/tests/networks/nets/test_swin_unetr.py @@ -51,7 +51,6 @@ "spatial_dims": len(img_size), "in_channels": in_channels, "out_channels": out_channels, - "img_size": img_size, "feature_size": feature_size, "depths": depth, "norm_name": norm_name, @@ -67,7 +66,7 @@ TEST_CASE_FILTER = [ [ - {"img_size": (96, 96, 96), "in_channels": 1, "out_channels": 14, "feature_size": 48, "use_checkpoint": True}, + {"in_channels": 1, "out_channels": 14, "feature_size": 48, "use_checkpoint": True}, "swinViT.layers1.0.blocks.0.norm1.weight", torch.tensor([0.9473, 0.9343, 0.8566, 0.8487, 0.8065, 0.7779, 0.6333, 0.5555]), ] @@ -85,30 +84,13 @@ def test_shape(self, input_param, input_shape, expected_shape): def test_ill_arg(self): with self.assertRaises(ValueError): - SwinUNETR( - in_channels=1, - out_channels=3, - img_size=(128, 128, 128), - feature_size=24, - norm_name="instance", - attn_drop_rate=4, - ) + SwinUNETR(spatial_dims=1, in_channels=1, out_channels=2, feature_size=48, norm_name="instance") with self.assertRaises(ValueError): - SwinUNETR(in_channels=1, out_channels=2, img_size=(96, 96), feature_size=48, norm_name="instance") + SwinUNETR(in_channels=1, out_channels=4, feature_size=50, norm_name="instance") with self.assertRaises(ValueError): - SwinUNETR(in_channels=1, out_channels=4, img_size=(96, 96, 96), feature_size=50, norm_name="instance") - - with self.assertRaises(ValueError): - SwinUNETR( - in_channels=1, - out_channels=3, - img_size=(85, 85, 85), - feature_size=24, - norm_name="instance", - drop_rate=0.4, - ) + SwinUNETR(in_channels=1, out_channels=3, feature_size=24, norm_name="instance", drop_rate=-1) def test_patch_merging(self): dim = 10 From a176ae10b83186c882f83ad5cbce4d5d4e854a3c Mon Sep 17 00:00:00 2001 From: YunLiu <55491388+KumoLiu@users.noreply.github.com> Date: Sun, 27 Apr 2025 11:38:36 +0800 Subject: [PATCH 4/7] fix isort Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com> --- monai/metrics/hausdorff_distance.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/monai/metrics/hausdorff_distance.py b/monai/metrics/hausdorff_distance.py index ce885b95f7..1b83c93e5b 100644 --- a/monai/metrics/hausdorff_distance.py +++ b/monai/metrics/hausdorff_distance.py @@ -17,12 +17,7 @@ import numpy as np import torch -from monai.metrics.utils import ( - do_metric_reduction, - get_edge_surface_distance, - ignore_background, - prepare_spacing, -) +from monai.metrics.utils import do_metric_reduction, get_edge_surface_distance, ignore_background, prepare_spacing from monai.utils import MetricReduction, convert_data_type from .metric import CumulativeIterationMetric From 617a0196fd798022edf700ddeab27fe0586f6bf4 Mon Sep 17 00:00:00 2001 From: YunLiu <55491388+KumoLiu@users.noreply.github.com> Date: Sun, 27 Apr 2025 17:15:05 +0800 Subject: [PATCH 5/7] fix format Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com> --- monai/utils/jupyter_utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/monai/utils/jupyter_utils.py b/monai/utils/jupyter_utils.py index b1b43a6767..c93e93dcb9 100644 --- a/monai/utils/jupyter_utils.py +++ b/monai/utils/jupyter_utils.py @@ -234,7 +234,7 @@ def plot_engine_status( def _get_loss_from_output( - output: list[torch.Tensor | dict[str, torch.Tensor]] | dict[str, torch.Tensor] | torch.Tensor + output: list[torch.Tensor | dict[str, torch.Tensor]] | dict[str, torch.Tensor] | torch.Tensor, ) -> torch.Tensor: """Returns a single value from the network output, which is a dict or tensor.""" From e6064f9cc24d228f9a91f52b3379fa5357b5fa4a Mon Sep 17 00:00:00 2001 From: YunLiu <55491388+KumoLiu@users.noreply.github.com> Date: Sun, 27 Apr 2025 18:56:08 +0800 Subject: [PATCH 6/7] fix mypy Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com> --- monai/apps/deepgrow/transforms.py | 4 ++-- monai/networks/schedulers/ddpm.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/monai/apps/deepgrow/transforms.py b/monai/apps/deepgrow/transforms.py index 721c0db489..d92a79a16a 100644 --- a/monai/apps/deepgrow/transforms.py +++ b/monai/apps/deepgrow/transforms.py @@ -441,8 +441,8 @@ def __call__(self, data): if np.all(np.less(current_size, self.spatial_size)): cropper = SpatialCrop(roi_center=center, roi_size=self.spatial_size) - box_start = np.array([s.start for s in cropper.slices]) - box_end = np.array([s.stop for s in cropper.slices]) + box_start = [s.start for s in cropper.slices] + box_end = [s.stop for s in cropper.slices] else: cropper = SpatialCrop(roi_start=box_start, roi_end=box_end) diff --git a/monai/networks/schedulers/ddpm.py b/monai/networks/schedulers/ddpm.py index d64e11d379..b196181eb1 100644 --- a/monai/networks/schedulers/ddpm.py +++ b/monai/networks/schedulers/ddpm.py @@ -238,7 +238,7 @@ def step( pred_prev_sample = pred_original_sample_coeff * pred_original_sample + current_sample_coeff * sample # 6. Add noise - variance = 0 + variance: torch.Tensor | int = 0 if timestep > 0: noise = torch.randn( model_output.size(), From 110ed9dbefdb4e344dc3ffaa09db285be0368f45 Mon Sep 17 00:00:00 2001 From: monai-bot Date: Fri, 9 May 2025 10:43:31 +0000 Subject: [PATCH 7/7] [MONAI] algo_template hash update Signed-off-by: monai-bot --- monai/utils/misc.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/monai/utils/misc.py b/monai/utils/misc.py index 866ca26f40..369333f122 100644 --- a/monai/utils/misc.py +++ b/monai/utils/misc.py @@ -546,7 +546,7 @@ def doc_images() -> str | None: @staticmethod def algo_hash() -> str | None: - return os.environ.get("MONAI_ALGO_HASH", "4c18daf") + return os.environ.get("MONAI_ALGO_HASH", "21ed8e5") @staticmethod def trace_transform() -> str | None: