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Revert "Update docs."
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This reverts commit 3dc9260.
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@karthikrangasai
karthikrangasai committed Mar 21, 2022
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Showing 9 changed files with 61 additions and 24 deletions.
2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -259,7 +259,7 @@ class MixUpInputTransform(InputTransform):

datamodule = ImageClassificationData.from_folders(
train_folder="data/train",
transform=MixUpInputTransform,
train_transform=MixUpInputTransform,
batch_size=2,
)

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4 changes: 2 additions & 2 deletions docs/source/integrations/icevision.rst
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Expand Up @@ -34,11 +34,11 @@ Here's an example:
from flash.core.integrations.icevision.transforms import IceVisionTransformAdapter
from flash.image import ObjectDetectionData
transform = {
train_transform = {
"per_sample_transform": IceVisionTransformAdapter([A.HorizontalFlip(), A.Normalize()]),
}
datamodule = ObjectDetectionData.from_coco(
...,
transform=transform,
train_transform=train_transform,
)
2 changes: 1 addition & 1 deletion docs/source/reference/image_classification.rst
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Expand Up @@ -142,7 +142,7 @@ Here's an example:
datamodule = ImageClassificationData.from_folders(
train_folder="data/hymenoptera_data/train/",
val_folder="data/hymenoptera_data/val/",
transform=ImageClassificationInputTransform,
train_transform=ImageClassificationInputTransform,
transform_kwargs=dict(image_size=(128, 128)),
batch_size=1,
)
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2 changes: 1 addition & 1 deletion docs/source/reference/object_detection.rst
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Expand Up @@ -112,6 +112,6 @@ creating a subclass of :class:`~flash.core.data.io.input_transform.InputTransfor
train_folder="data/coco128/images/train2017/",
train_ann_file="data/coco128/annotations/instances_train2017.json",
val_split=0.1,
transform=BrightnessContrastTransform,
train_transform=BrightnessContrastTransform,
batch_size=4,
)
2 changes: 1 addition & 1 deletion flash/audio/classification/data.py
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Expand Up @@ -401,7 +401,7 @@ def from_tensors(
target_formatter: Optionally provide a :class:`~flash.core.data.utilities.classification.TargetFormatter` to
control how targets are handled. See :ref:`formatting_classification_targets` for more details.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
train_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
data_module_kwargs: Additional keyword arguments to provide to the
:class:`~flash.core.data.data_module.DataModule` constructor.
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2 changes: 1 addition & 1 deletion flash/audio/speech_recognition/data.py
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Expand Up @@ -289,7 +289,7 @@ def from_json(
sampling_rate: Sampling rate to use when loading the audio files.
field: The field that holds the data in the JSON file.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
train_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
data_module_kwargs: Additional keyword arguments to provide to the
:class:`~flash.core.data.data_module.DataModule` constructor.
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22 changes: 16 additions & 6 deletions flash/template/classification/data.py
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Expand Up @@ -150,9 +150,14 @@ def from_numpy(
test_data: The numpy ``Array`` containing the test data.
test_targets: The sequence of test targets.
predict_data: The numpy ``Array`` containing the predict data.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
train_transform: The dictionary of transforms to use during training which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
val_transform: The dictionary of transforms to use during validation which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
test_transform: The dictionary of transforms to use during testing which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
predict_transform: The dictionary of transforms to use during predicting which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
Returns:
The constructed data module.
Expand Down Expand Up @@ -193,9 +198,14 @@ def from_sklearn(
val_bunch: The scikit-learn ``Bunch`` containing the validation data.
test_bunch: The scikit-learn ``Bunch`` containing the test data.
predict_bunch: The scikit-learn ``Bunch`` containing the predict data.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
train_transform: The dictionary of transforms to use during training which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
val_transform: The dictionary of transforms to use during validation which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
test_transform: The dictionary of transforms to use during testing which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
predict_transform: The dictionary of transforms to use during predicting which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
Returns:
The constructed data module.
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45 changes: 36 additions & 9 deletions flash/video/classification/data.py
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Expand Up @@ -114,7 +114,11 @@ def from_files(
test_files: The list of video files to use when testing.
test_targets: The list of targets to use when testing.
predict_files: The list of video files to use when predicting.
train_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when training.
val_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when validating.
test_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when testing.
predict_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when
predicting.
target_formatter: Optionally provide a :class:`~flash.core.data.utilities.classification.TargetFormatter` to
control how targets are handled. See :ref:`formatting_classification_targets` for more details.
clip_sampler: The clip sampler to use. One of: ``"uniform"``, ``"random"``, ``"constant_clips_per_video"``.
Expand Down Expand Up @@ -271,7 +275,11 @@ def from_folders(
val_folder: The folder containing videos to use when validating.
test_folder: The folder containing videos to use when testing.
predict_folder: The folder containing videos to use when predicting.
train_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when training.
val_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when validating.
test_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when testing.
predict_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when
predicting.
target_formatter: Optionally provide a :class:`~flash.core.data.utilities.classification.TargetFormatter` to
control how targets are handled. See :ref:`formatting_classification_targets` for more details.
clip_sampler: The clip sampler to use. One of: ``"uniform"``, ``"random"``, ``"constant_clips_per_video"``.
Expand All @@ -284,7 +292,6 @@ def from_folders(
videos.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
predict_input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the prediction data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
data_module_kwargs: Additional keyword arguments to provide to the
:class:`~flash.core.data.data_module.DataModule` constructor.
Expand Down Expand Up @@ -438,6 +445,11 @@ def from_data_frame(
predict_videos_root: The root directory containing predict videos.
predict_resolver: Optionally provide a function which converts an entry from the ``input_field`` into a
video file path.
train_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when training.
val_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when validating.
test_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when testing.
predict_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when
predicting.
target_formatter: Optionally provide a :class:`~flash.core.data.utilities.classification.TargetFormatter` to
control how targets are handled. See :ref:`formatting_classification_targets` for more details.
clip_sampler: The clip sampler to use. One of: ``"uniform"``, ``"random"``, ``"constant_clips_per_video"``.
Expand All @@ -450,7 +462,6 @@ def from_data_frame(
videos.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
predict_input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the prediction data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
data_module_kwargs: Additional keyword arguments to provide to the
:class:`~flash.core.data.data_module.DataModule` constructor.
Expand Down Expand Up @@ -626,6 +637,11 @@ def from_csv(
predict_videos_root: The root directory containing predict videos.
predict_resolver: Optionally provide a function which converts an entry from the ``input_field`` into a
video file path.
train_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when training.
val_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when validating.
test_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when testing.
predict_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when
predicting.
target_formatter: Optionally provide a :class:`~flash.core.data.utilities.classification.TargetFormatter` to
control how targets are handled. See :ref:`formatting_classification_targets` for more details.
clip_sampler: The clip sampler to use. One of: ``"uniform"``, ``"random"``, ``"constant_clips_per_video"``.
Expand All @@ -638,7 +654,6 @@ def from_csv(
videos.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
predict_input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the prediction data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
data_module_kwargs: Additional keyword arguments to provide to the
:class:`~flash.core.data.data_module.DataModule` constructor.
Expand Down Expand Up @@ -806,6 +821,11 @@ def from_fiftyone(
test_dataset: The ``SampleCollection`` to use when testing.
predict_dataset: The ``SampleCollection`` to use when predicting.
label_field: The field in the ``SampleCollection`` objects containing the targets.
train_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when training.
val_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when validating.
test_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when testing.
predict_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use when
predicting.
target_formatter: Optionally provide a :class:`~flash.core.data.utilities.classification.TargetFormatter` to
control how targets are handled. See :ref:`formatting_classification_targets` for more details.
clip_sampler: The clip sampler to use. One of: ``"uniform"``, ``"random"``, ``"constant_clips_per_video"``.
Expand All @@ -818,7 +838,6 @@ def from_fiftyone(
videos.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
predict_input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the prediction data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
data_module_kwargs: Additional keyword arguments to provide to the
:class:`~flash.core.data.data_module.DataModule` constructor.
Expand Down Expand Up @@ -969,8 +988,19 @@ def from_labelstudio(
val_data_folder: path to label studio data folder for validation data
test_data_folder: path to label studio data folder for test data
predict_data_folder: path to label studio data folder for predict data
train_transform: The dictionary of transforms to use during training which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
val_transform: The dictionary of transforms to use during validation which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
test_transform: The dictionary of transforms to use during testing which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
predict_transform: The dictionary of transforms to use during predicting which maps
:class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
data_fetcher: The :class:`~flash.core.data.callback.BaseDataFetcher` to pass to the
:class:`~flash.core.data.data_module.DataModule`.
input_transform: The :class:`~flash.core.data.io.input_transform.InputTransform` to pass to the
:class:`~flash.core.data.data_module.DataModule`. If ``None``, ``cls.input_transform_cls``
will be constructed and used.
val_split: The ``val_split`` argument to pass to the :class:`~flash.core.data.data_module.DataModule`.
multi_label: Whether the label are multi encoded.
clip_sampler: Defines how clips should be sampled from each video.
Expand All @@ -980,9 +1010,6 @@ def from_labelstudio(
if necessary, the distributed split.
decode_audio: If True, also decode audio from video.
decoder: Defines what type of decoder used to decode a video.
input_cls: The :class:`~flash.core.data.io.input.Input` type to use for loading the data.
transform: The :class:`~flash.core.data.io.input_transform.InputTransform` type to use.
transform_kwargs: Dict of keyword arguments to be provided when instantiating the transforms.
data_module_kwargs: Additional keyword arguments to use when constructing the datamodule.
Returns:
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4 changes: 2 additions & 2 deletions flash_examples/integrations/learn2learn/image_classification_imagenette_mini.py
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Expand Up @@ -34,7 +34,7 @@
train_dataset = l2l.vision.datasets.MiniImagenet(root="data", mode="train", download=True)
val_dataset = l2l.vision.datasets.MiniImagenet(root="data", mode="validation", download=True)

transform = {
train_transform = {
"per_sample_transform": nn.Sequential(
ApplyToKeys(
DataKeys.INPUT,
Expand Down Expand Up @@ -70,7 +70,7 @@
train_targets=torch.from_numpy(train_dataset.y.astype(int)),
val_data=val_dataset.x,
val_targets=torch.from_numpy(val_dataset.y.astype(int)),
transform=transform,
train_transform=train_transform,
)

model = ImageClassifier(
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