neural_compressor.data.datasets.coco_dataset
¶
Built-in COCO datasets class for multiple framework backends.
Module Contents¶
Classes¶
Helper function for TensorflowModelZooBertDataset. |
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Tensorflow COCO dataset in tf record format. |
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Coco raw dataset. |
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COCO npy dataset. |
- class neural_compressor.data.datasets.coco_dataset.ParseDecodeCoco¶
Helper function for TensorflowModelZooBertDataset.
Parse the features from sample.
- class neural_compressor.data.datasets.coco_dataset.COCORecordDataset¶
Bases:
neural_compressor.data.datasets.dataset.IterableDataset
Tensorflow COCO dataset in tf record format.
Root is a full path to tfrecord file, which contains the file name. Please use Resize transform when batch_size > 1
- Args: root (str): Root directory of dataset.
num_cores (int, default=28):The number of input Datasets to interleave from in parallel. transform (transform object, default=None): transform to process input data. filter (Filter objects, default=None): filter out examples according
to specific conditions.
- class neural_compressor.data.datasets.coco_dataset.COCORaw(root, img_dir='val2017', anno_dir='annotations/instances_val2017.json', transform=None, filter=filter)¶
Bases:
neural_compressor.data.datasets.dataset.Dataset
Coco raw dataset.
- Please arrange data in this way:
/root/img_dir/1.jpg /root/img_dir/2.jpg … /root/img_dir/n.jpg /root/anno_dir
Please use Resize transform when batch_size > 1
- Args: root (str): Root directory of dataset.
img_dir (str, default=’val2017’): image file directory. anno_dir (str, default=’annotations/instances_val2017.json’): annotation file directory. transform (transform object, default=None): transform to process input data. filter (Filter objects, default=None): filter out examples according
to specific conditions.
- class neural_compressor.data.datasets.coco_dataset.COCONpy(root, npy_dir='val2017', anno_dir='annotations/instances_val2017.json', transform=None, filter=None)¶
Bases:
neural_compressor.data.datasets.dataset.Dataset
COCO npy dataset.
- Please arrange data in this way:
/root/npy_dir/1.jpg.npy /root/npy_dir/2.jpg.npy … /root/npy_dir/n.jpg.npy /root/anno_dir
- Args: root (str): Root directory of dataset.
npy_dir (str, default=’val2017’): npy file directory. anno_dir (str, default=’annotations/instances_val2017.json’): annotation file directory. transform (transform object, default=None): transform to process input data. filter (Filter objects, default=None): filter out examples according
to specific conditions.