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torchvision tutorial: update deprecated pretrained=True #1998

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Aug 10, 2022
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torchvision tutorial: update deprecated pretrained=True #1998

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8 changes: 4 additions & 4 deletions intermediate_source/torchvision_tutorial.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -221,7 +221,7 @@ way of doing it:
from torchvision.models.detection.faster_rcnn import FastRCNNPredictor

# load a model pre-trained on COCO
model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)
model = torchvision.models.detection.fasterrcnn_resnet50_fpn(weights="DEFAULT")

# replace the classifier with a new one, that has
# num_classes which is user-defined
Expand All @@ -242,7 +242,7 @@ way of doing it:

# load a pre-trained model for classification and return
# only the features
backbone = torchvision.models.mobilenet_v2(pretrained=True).features
backbone = torchvision.models.mobilenet_v2(weights="DEFAULT").features
# FasterRCNN needs to know the number of
# output channels in a backbone. For mobilenet_v2, it's 1280
# so we need to add it here
Expand Down Expand Up @@ -291,7 +291,7 @@ be using Mask R-CNN:

def get_model_instance_segmentation(num_classes):
# load an instance segmentation model pre-trained on COCO
model = torchvision.models.detection.maskrcnn_resnet50_fpn(pretrained=True)
model = torchvision.models.detection.maskrcnn_resnet50_fpn(weights="DEFAULT")

# get number of input features for the classifier
in_features = model.roi_heads.box_predictor.cls_score.in_features
Expand Down Expand Up @@ -344,7 +344,7 @@ expects during training and inference time on sample data.

.. code:: python

model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)
model = torchvision.models.detection.fasterrcnn_resnet50_fpn(weights="DEFAULT")
dataset = PennFudanDataset('PennFudanPed', get_transform(train=True))
data_loader = torch.utils.data.DataLoader(
dataset, batch_size=2, shuffle=True, num_workers=4,
Expand Down