diff --git a/bob/bio/base/transformers/algorithm.py b/bob/bio/base/transformers/algorithm.py
index 16bcf1c94111f3158827522d411f0f59e4c092e2..e046842f437dcefd0b02b5f1a9d9466de95e39ae 100644
--- a/bob/bio/base/transformers/algorithm.py
+++ b/bob/bio/base/transformers/algorithm.py
@@ -26,56 +26,56 @@ class AlgorithmTransformer(TransformerMixin, BaseEstimator):
Parameters
----------
- callable: ``collections.callable``
+ instance: ``collections.callable``
Callable function that instantiates the bob.bio.base.algorithm.Algorithm
"""
def __init__(
- self, callable, projector_file=None, **kwargs,
+ self, instance, projector_file=None, **kwargs,
):
- if not isinstance(callable, Algorithm):
+ if not isinstance(instance, Algorithm):
raise ValueError(
- "`callable` should be an instance of `bob.bio.base.extractor.Algorithm`"
+ "`instance` should be an instance of `bob.bio.base.extractor.Algorithm`"
)
- if callable.requires_projector_training and (
+ if instance.requires_projector_training and (
projector_file is None or projector_file == ""
):
raise ValueError(
- f"`projector_file` needs to be set if extractor {callable} requires training"
+ f"`projector_file` needs to be set if extractor {instance} requires training"
)
- if not is_picklable(callable):
- raise ValueError(f"{callable} needs to be picklable")
+ if not is_picklable(instance):
+ raise ValueError(f"{instance} needs to be picklable")
- self.callable = callable
+ self.instance = instance
self.projector_file = projector_file
super().__init__(**kwargs)
def fit(self, X, y=None):
- if not self.callable.requires_projector_training:
+ if not self.instance.requires_projector_training:
return self
training_data = X
- if self.callable.split_training_features_by_client:
+ if self.instance.split_training_features_by_client:
training_data = split_X_by_y(X, y)
os.makedirs(os.path.dirname(self.projector_file), exist_ok=True)
- self.callable.train_projector(training_data, self.projector_file)
+ self.instance.train_projector(training_data, self.projector_file)
return self
def transform(self, X, metadata=None):
if metadata is None:
- return [self.callable.project(data) for data in X]
+ return [self.instance.project(data) for data in X]
else:
return [
- self.callable.project(data, metadata)
+ self.instance.project(data, metadata)
for data, metadata in zip(X, metadata)
]
def _more_tags(self):
return {
- "stateless": not self.callable.requires_projector_training,
- "requires_fit": self.callable.requires_projector_training,
+ "stateless": not self.instance.requires_projector_training,
+ "requires_fit": self.instance.requires_projector_training,
}
diff --git a/bob/bio/base/transformers/extractor.py b/bob/bio/base/transformers/extractor.py
index ab28508f228c40c35297f1f2713ca30b4cfd4335..303859543fc8cadaaa735169c964941e2ccc3c82 100644
--- a/bob/bio/base/transformers/extractor.py
+++ b/bob/bio/base/transformers/extractor.py
@@ -13,7 +13,7 @@ class ExtractorTransformer(TransformerMixin, BaseEstimator):
Parameters
----------
- callable: ``collections.Callable``
+ instance: ``collections.callable``
Instance of `bob.bio.base.extractor.Extractor`
model_path: ``str``
@@ -22,44 +22,44 @@ class ExtractorTransformer(TransformerMixin, BaseEstimator):
"""
def __init__(
- self, callable, model_path=None, **kwargs,
+ self, instance, model_path=None, **kwargs,
):
- if not isinstance(callable, Extractor):
+ if not isinstance(instance, Extractor):
raise ValueError(
- "`callable` should be an instance of `bob.bio.base.extractor.Extractor`"
+ "`instance` should be an instance of `bob.bio.base.extractor.Extractor`"
)
- if callable.requires_training and (model_path is None or model_path == ""):
+ if instance.requires_training and (model_path is None or model_path == ""):
raise ValueError(
- f"`model_path` needs to be set if extractor {callable} requires training"
+ f"`model_path` needs to be set if extractor {instance} requires training"
)
- self.callable = callable
+ self.instance = instance
self.model_path = model_path
super().__init__(**kwargs)
def fit(self, X, y=None):
- if not self.callable.requires_training:
+ if not self.instance.requires_training:
return self
training_data = X
- if self.callable.split_training_data_by_client:
+ if self.instance.split_training_data_by_client:
training_data = split_X_by_y(X, y)
- self.callable.train(training_data, self.model_path)
+ self.instance.train(training_data, self.model_path)
return self
def transform(self, X, metadata=None):
if metadata is None:
- return [self.callable(data) for data in X]
+ return [self.instance(data) for data in X]
else:
return [
- self.callable(data, metadata) for data, metadata in zip(X, metadata)
+ self.instance(data, metadata) for data, metadata in zip(X, metadata)
]
def _more_tags(self):
return {
- "stateless": not self.callable.requires_training,
- "requires_fit": self.callable.requires_training,
+ "stateless": not self.instance.requires_training,
+ "requires_fit": self.instance.requires_training,
}
diff --git a/bob/bio/base/transformers/preprocessor.py b/bob/bio/base/transformers/preprocessor.py
index 1cddda6713117cceb5cb0035b77dde624c0145db..acb7824d888643c5acbb084619307bceb10ba494 100644
--- a/bob/bio/base/transformers/preprocessor.py
+++ b/bob/bio/base/transformers/preprocessor.py
@@ -11,7 +11,7 @@ class PreprocessorTransformer(TransformerMixin, BaseEstimator):
Parameters
----------
- callable: ``collections.Callable``
+ instance: ``collections.callable``
Instance of `bob.bio.base.preprocessor.Preprocessor`
@@ -19,21 +19,21 @@ class PreprocessorTransformer(TransformerMixin, BaseEstimator):
def __init__(
self,
- callable,
+ instance,
**kwargs,
):
- if not isinstance(callable, Preprocessor):
- raise ValueError("`callable` should be an instance of `bob.bio.base.preprocessor.Preprocessor`")
+ if not isinstance(instance, Preprocessor):
+ raise ValueError("`instance` should be an instance of `bob.bio.base.preprocessor.Preprocessor`")
- self.callable = callable
+ self.instance = instance
super().__init__(**kwargs)
def transform(self, X, annotations=None):
if annotations is None:
- return [self.callable(data) for data in X]
+ return [self.instance(data) for data in X]
else:
- return [self.callable(data, annot) for data, annot in zip(X, annotations)]
+ return [self.instance(data, annot) for data, annot in zip(X, annotations)]
def _more_tags(self):
return {"stateless": True, "requires_fit": False}