Rename ClassificationInput to ClassificationInputMixin

CHANGELOG.md

@@ -20,6 +20,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Changed `Wav2Vec2Processor` to `AutoProcessor` and seperate it from backbone [optional] ([#1075](https://github.com/PyTorchLightning/lightning-flash/pull/1075))
 
+- Renamed `ClassificationInput` to `ClassificationInputMixin` ([#1116](https://github.com/PyTorchLightning/lightning-flash/pull/1116))
+
 ### Deprecated
 
 ### Fixed

docs/source/api/data.rst

@@ -82,6 +82,17 @@ ___________________________
     ~flash.core.data.io.input.InputFormat
     ~flash.core.data.io.input.ImageLabelsMap
 
+flash.core.data.io.classification
+_________________________________
+
+.. autosummary::
+    :toctree: generated/
+    :nosignatures:
+    :template: classtemplate.rst
+
+    ~flash.core.data.io.classification_input.ClassificationState
+    ~flash.core.data.io.classification_input.ClassificationInputMixin
+
 flash.core.data.process
 _______________________
 

docs/source/template/data.rst

@@ -27,9 +27,9 @@ Each :class:`~flash.core.data.io.input.Input` has 2 methods:
 By default these methods just return their input, so you don't need both a :meth:`~flash.core.data.io.input.Input.load_data` and a :meth:`~flash.core.data.io.input.Input.load_sample` to create a :class:`~flash.core.data.io.input.Input`.
 Where possible, you should override one of our existing :class:`~flash.core.data.io.input.Input` classes.
 
-Let's start by implementing a ``TemplateNumpyClassificationInput``, which overrides :class:`~flash.core.data.io.classification_input.ClassificationInput`.
+Let's start by implementing a ``TemplateNumpyClassificationInput``, which overrides :class:`~flash.core.data.io.classification_input.ClassificationInputMixin`.
 The main :class:`~flash.core.data.io.input.Input` method that we have to implement is :meth:`~flash.core.data.io.input.Input.load_data`.
-:class:`~flash.core.data.io.classification_input.ClassificationInput` provides utilities for handling targets within flash which need to be called from the :meth:`~flash.core.data.io.input.Input.load_data` and :meth:`~flash.core.data.io.input.Input.load_sample`.
+:class:`~flash.core.data.io.classification_input.ClassificationInputMixin` provides utilities for handling targets within flash which need to be called from the :meth:`~flash.core.data.io.input.Input.load_data` and :meth:`~flash.core.data.io.input.Input.load_sample`.
 In this ``Input``, we'll also set the ``num_features`` attribute so that we can access it later.
 
 Here's the code for our ``TemplateNumpyClassificationInput.load_data`` method:

flash/audio/classification/input.py

@@ -17,8 +17,8 @@
 import numpy as np
 import pandas as pd
 
-from flash.core.data.io.classification_input import ClassificationInput, ClassificationState
-from flash.core.data.io.input import DataKeys
+from flash.core.data.io.classification_input import ClassificationInputMixin, ClassificationState
+from flash.core.data.io.input import DataKeys, Input
 from flash.core.data.utilities.classification import TargetMode
 from flash.core.data.utilities.data_frame import read_csv, resolve_files, resolve_targets
 from flash.core.data.utilities.paths import filter_valid_files, has_file_allowed_extension, make_dataset, PATH_TYPE
@@ -37,7 +37,7 @@ def spectrogram_loader(filepath: str):
     return data
 
 
-class AudioClassificationInput(ClassificationInput):
+class AudioClassificationInput(Input, ClassificationInputMixin):
     @requires("audio")
     def load_sample(self, sample: Dict[str, Any]) -> Dict[str, Any]:
         h, w = sample[DataKeys.INPUT].shape[-2:]  # H x W

flash/core/data/io/classification_input.py

@@ -15,8 +15,7 @@
 from functools import lru_cache
 from typing import Any, List, Optional, Sequence
 
-from flash.core.data.io.input import Input
-from flash.core.data.properties import ProcessState
+from flash.core.data.properties import ProcessState, Properties
 from flash.core.data.utilities.classification import (
     get_target_details,
     get_target_formatter,
@@ -34,9 +33,9 @@ class ClassificationState(ProcessState):
     num_classes: Optional[int] = None
 
 
-class ClassificationInput(Input):
-    """The ``ClassificationInput`` class provides utility methods for handling classification targets.
-    :class:`~flash.core.data.io.input.Input` objects that extend ``ClassificationInput`` should do the following:
+class ClassificationInputMixin(Properties):
+    """The ``ClassificationInputMixin`` class provides utility methods for handling classification targets.
+    :class:`~flash.core.data.io.input.Input` objects that extend ``ClassificationInputMixin`` should do the following:
 
     * In the ``load_data`` method, include a call to ``load_target_metadata``. This will determine the format of the
       targets and store metadata like ``labels`` and ``num_classes``.
@@ -47,7 +46,7 @@ class ClassificationInput(Input):
     @property
     @lru_cache(maxsize=None)
     def target_formatter(self) -> TargetFormatter:
-        """Get the :class:`~flash.core.data.utiltiies.classification.TargetFormatter` to use when formatting
+        """Get the :class:`~flash.core.data.utilities.classification.TargetFormatter` to use when formatting
         targets.
 
         This property uses ``functools.lru_cache`` so that we only instantiate the formatter once.

flash/graph/classification/input.py

@@ -16,7 +16,7 @@
 from torch.utils.data import Dataset
 
 from flash.core.data.data_module import DatasetInput
-from flash.core.data.io.classification_input import ClassificationInput, ClassificationState
+from flash.core.data.io.classification_input import ClassificationInputMixin, ClassificationState
 from flash.core.data.io.input import DataKeys
 from flash.core.utilities.imports import _GRAPH_AVAILABLE, requires
 
@@ -26,7 +26,7 @@
     from torch_geometric.data import InMemoryDataset
 
 
-class GraphClassificationDatasetInput(DatasetInput, ClassificationInput):
+class GraphClassificationDatasetInput(DatasetInput, ClassificationInputMixin):
     @requires("graph")
     def load_data(self, dataset: Dataset) -> Dataset:
         if not self.predicting:

flash/image/classification/input.py

@@ -16,7 +16,7 @@
 
 import pandas as pd
 
-from flash.core.data.io.classification_input import ClassificationInput, ClassificationState
+from flash.core.data.io.classification_input import ClassificationInputMixin, ClassificationState
 from flash.core.data.io.input import DataKeys
 from flash.core.data.utilities.classification import TargetMode
 from flash.core.data.utilities.data_frame import read_csv, resolve_files, resolve_targets
@@ -34,7 +34,7 @@
     SampleCollection = None
 
 
-class ImageClassificationFilesInput(ClassificationInput, ImageFilesInput):
+class ImageClassificationFilesInput(ClassificationInputMixin, ImageFilesInput):
     def load_data(self, files: List[PATH_TYPE], targets: Optional[List[Any]] = None) -> List[Dict[str, Any]]:
         if targets is None:
             return super().load_data(files)
@@ -74,7 +74,7 @@ def predict_load_data(data: SampleCollection) -> List[Dict[str, Any]]:
         return super().load_data(data.values("filepath"))
 
 
-class ImageClassificationTensorInput(ClassificationInput, ImageTensorInput):
+class ImageClassificationTensorInput(ClassificationInputMixin, ImageTensorInput):
     def load_data(self, tensor: Any, targets: Optional[List[Any]] = None) -> List[Dict[str, Any]]:
         if targets is not None:
             self.load_target_metadata(targets)
@@ -87,7 +87,7 @@ def load_sample(self, sample: Dict[str, Any]) -> Dict[str, Any]:
         return sample
 
 
-class ImageClassificationNumpyInput(ClassificationInput, ImageNumpyInput):
+class ImageClassificationNumpyInput(ClassificationInputMixin, ImageNumpyInput):
     def load_data(self, array: Any, targets: Optional[List[Any]] = None) -> List[Dict[str, Any]]:
         if targets is not None:
             self.load_target_metadata(targets)

flash/tabular/classification/input.py

@@ -13,8 +13,8 @@
 # limitations under the License.
 from typing import Any, Dict, List, Optional, Union
 
-from flash import DataKeys
-from flash.core.data.io.classification_input import ClassificationInput
+from flash.core.data.io.classification_input import ClassificationInputMixin
+from flash.core.data.io.input import DataKeys
 from flash.core.data.utilities.data_frame import read_csv, resolve_targets
 from flash.core.utilities.imports import _PANDAS_AVAILABLE
 from flash.tabular.input import TabularDataFrameInput
@@ -25,7 +25,7 @@
     DataFrame = object
 
 
-class TabularClassificationDataFrameInput(TabularDataFrameInput, ClassificationInput):
+class TabularClassificationDataFrameInput(TabularDataFrameInput, ClassificationInputMixin):
     def load_data(
         self,
         data_frame: DataFrame,

flash/tabular/regression/input.py

@@ -15,7 +15,7 @@
 
 import numpy as np
 
-from flash import DataKeys
+from flash.core.data.io.input import DataKeys
 from flash.core.data.utilities.data_frame import read_csv
 from flash.core.utilities.imports import _PANDAS_AVAILABLE
 from flash.tabular.input import TabularDataFrameInput

flash/template/classification/data.py

@@ -20,7 +20,7 @@
 from flash.core.data.callback import BaseDataFetcher
 from flash.core.data.data_module import DataModule
 from flash.core.data.data_pipeline import DataPipelineState
-from flash.core.data.io.classification_input import ClassificationInput
+from flash.core.data.io.classification_input import ClassificationInputMixin
 from flash.core.data.io.input import DataKeys, Input
 from flash.core.data.io.input_transform import InputTransform
 from flash.core.data.utilities.samples import to_samples
@@ -34,7 +34,7 @@
     Bunch = object
 
 
-class TemplateNumpyClassificationInput(ClassificationInput):
+class TemplateNumpyClassificationInput(Input, ClassificationInputMixin):
     """An example data source that records ``num_features`` on the dataset."""
 
     def load_data(

flash/text/classification/input.py

@@ -16,8 +16,8 @@
 
 import pandas as pd
 
-from flash.core.data.io.classification_input import ClassificationInput, ClassificationState
-from flash.core.data.io.input import DataKeys
+from flash.core.data.io.classification_input import ClassificationInputMixin, ClassificationState
+from flash.core.data.io.input import DataKeys, Input
 from flash.core.data.utilities.classification import TargetMode
 from flash.core.data.utilities.paths import PATH_TYPE
 from flash.core.integrations.transformers.states import TransformersBackboneState
@@ -29,7 +29,7 @@
     Dataset = object
 
 
-class TextClassificationInput(ClassificationInput):
+class TextClassificationInput(Input, ClassificationInputMixin):
     @staticmethod
     def _resolve_target(target_keys: Union[str, List[str]], element: Dict[str, Any]) -> Dict[str, Any]:
         if not isinstance(target_keys, List):