src/proteingnn/util.py
def evaluate_versions(class_: Any, dataset: Any, ckpt: AnyPath, is_graph: bool = True, logdir: AnyPath = 'Log', log_name: Optional[str] = 'default',
                      deep: bool = True, metric_name: Optional[str] = None, sort_order: str = 'min')\
        -> List[Dict[str, float]]:
    """Evaluate all checkpoints on x, y.

    Args:
        x: Model input.
        y: Target output.
        class_: Model class.

        logdir: Version directory to look underneath from.
        log_name: Name of log directory.
        deep: Search for version directory in depth for non-standard directory hierarchy.
        metric_name: Name of the best metric. Requires checkpoint name format as -
            {anything}{metric_name}={metric_value}.ckpt
        sort_order: Sort order to choose best metric from. Apply only when metric_name is specified.
            Available options - 'min' or 'max'.
    """
    return [evaluate_ckpt(class_=class_, dataset=dataset, ckpt=ckpt, is_graph=is_graph) for ckpt in
            get_checkpoints(logdir=logdir, log_name=log_name, deep=deep, metric_name=metric_name, sort_order=sort_order)]
Evaluate all checkpoints on x, y.

    Args:
        x: Model input.
        y: Target output.
        class_: Model class.

        logdir: Version directory to look underneath from.
        log_name: Name of log directory.
        deep: Search for version directory in depth for non-standard directory hierarchy.
        metric_name: Name of the best metric. Requires checkpoint name format as -
            {anything}{metric_name}={metric_value}.ckpt
        sort_order: Sort order to choose best metric from. Apply only when metric_name is specified.
            Available options - 'min' or 'max'.
    
Evaluate all checkpoints on x, y.
Evaluate all checkpoints on x y .
def evaluate_versions(class_: Any, dataset: Any, ckpt: AnyPath, is_graph: bool = True, logdir: AnyPath = 'Log', log_name: Optional[str] = 'default',
                      deep: bool = True, metric_name: Optional[str] = None, sort_order: str = 'min')\
        -> List[Dict[str, float]]:
    return [evaluate_ckpt(class_=class_, dataset=dataset, ckpt=ckpt, is_graph=is_graph) for ckpt in
            get_checkpoints(logdir=logdir, log_name=log_name, deep=deep, metric_name=metric_name, sort_order=sort_order)]
def evaluate_versions ( class_ : Any , dataset : Any , ckpt : AnyPath , is_graph : bool = True , logdir : AnyPath = 'Log' , log_name : Optional [ str ] = 'default' , deep : bool = True , metric_name : Optional [ str ] = None , sort_order : str = 'min' ) -> List [ Dict [ str , float ] ] : return [ evaluate_ckpt ( class_ = class_ , dataset = dataset , ckpt = ckpt , is_graph = is_graph ) for ckpt in get_checkpoints ( logdir = logdir , log_name = log_name , deep = deep , metric_name = metric_name , sort_order = sort_order ) ]
Evaluate all checkpoints on x, y.
Evaluate all checkpoints on x y .
"""Evaluate all checkpoints on x, y.

    Args:
        x: Model input.
        y: Target output.
        class_: Model class.

        logdir: Version directory to look underneath from.
        log_name: Name of log directory.
        deep: Search for version directory in depth for non-standard directory hierarchy.
        metric_name: Name of the best metric. Requires checkpoint name format as -
            {anything}{metric_name}={metric_value}.ckpt
        sort_order: Sort order to choose best metric from. Apply only when metric_name is specified.
            Available options - 'min' or 'max'.
    """
class_
Any
None
dataset
Any
ckpt
AnyPath
is_graph
bool
logdir
AnyPath
Version directory to look underneath from.
Version directory to look underneath from .
log_name
Optional[str]
Name of log directory.
Name of log directory .
deep
bool
Search for version directory in depth for non-standard directory hierarchy.
Search for version directory in depth for non - standard directory hierarchy .
metric_name
Optional[str]
Name of the best metric. Requires checkpoint name format as
{anything}{metric_name}={metric_value}.ckpt
Name of the best metric . Requires checkpoint name format as { anything } { metric_name } = { metric_value } . ckpt
sort_order
str
Sort order to choose best metric from. Apply only when metric_name is specified.
Available options - 'min' or 'max'.
Sort order to choose best metric from . Apply only when metric_name is specified . Available options - ' min ' or ' max ' .
x
None
y
None