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Holocron
Holocron

Getting Started

  • Installation
  • Holocron Notebooks

Package Reference

  • holocron.models
    • ResNet
      • resnet18
      • resnet34
      • resnet50
      • resnet50d
      • resnet101
      • resnet152
    • ResNeXt
      • resnext50_32x4d
      • resnext101_32x8d
    • Res2Net
      • res2net50_26w_4s
    • TridentNet
      • tridentnet50
    • ConvNeXt
      • convnext_atto
      • convnext_femto
      • convnext_pico
      • convnext_nano
      • convnext_tiny
      • convnext_small
      • convnext_base
      • convnext_large
      • convnext_xl
    • PyConvResNet
      • pyconv_resnet50
      • pyconvhg_resnet50
    • ReXNet
      • rexnet1_0x
      • rexnet1_3x
      • rexnet1_5x
      • rexnet2_0x
      • rexnet2_2x
    • SKNet
      • sknet50
      • sknet101
      • sknet152
    • DarkNet
      • darknet24
    • DarkNetV2
      • darknet19
    • DarkNetV3
      • darknet53
    • DarkNetV4
      • cspdarknet53
      • cspdarknet53_mish
    • RepVGG
      • repvgg_a0
      • repvgg_a1
      • repvgg_a2
      • repvgg_b0
      • repvgg_b1
      • repvgg_b2
      • repvgg_b3
    • MobileOne
      • mobileone_s0
      • mobileone_s1
      • mobileone_s2
      • mobileone_s3
  • holocron.nn
  • holocron.nn.functional
  • holocron.ops
  • holocron.optim
  • holocron.trainer
  • holocron.transforms
  • holocron.utils
  • holocron.utils.data

Notes

  • Changelog
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tridentnet50¶

holocron.models.tridentnet50(pretrained: bool = False, progress: bool = True, **kwargs: Any) → ResNet[source]¶

TridentNet-50 from “Scale-Aware Trident Networks for Object Detection”

Parameters:
  • pretrained (bool) – If True, returns a model pre-trained on ImageNet

  • progress (bool) – If True, displays a progress bar of the download to stderr

  • kwargs – keyword args of _tridentnet

Returns:

classification model

Return type:

torch.nn.Module

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    • tridentnet50()