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Parameters
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block : Block
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Class for the residual block. Options are BasicBlockV1, BottleneckV1.
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layers : list of int
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Numbers of layers in each block
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classes : int, default 1000
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Number of classification classes.
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dilated : bool, default False
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Applying dilation strategy to pretrained ResNet yielding a stride-8 model,
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Normalization layer used in backbone network (default: :class:`mxnet.gluon.nn.BatchNorm`;
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Reference:
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- He, Kaiming, et al. "Deep residual learning for image recognition." Proceedings of the IEEE conference on computer vision and pattern recognition. 2016.
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- Yu, Fisher, and Vladlen Koltun. "Multi-scale context aggregation by dilated convolutions."
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