SJChaudhuri

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Efficient-MaxViT

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• "torchvision.models.efficientnet.MBConv",
• "torch.storage._load_from_bytes",
• "torch.nn.modules.container.Sequential",
• "torchvision.models.maxvit.MaxVitBlock",
• "torch.nn.modules.flatten.Flatten",
• "torchvision.models.maxvit.WindowPartition",
• "torchvision.models.efficientnet.EfficientNet",
• "torchvision.models.maxvit.RelativePositionalMultiHeadAttention",
• "torch.nn.modules.dropout.Dropout",
• "torchvision.models.efficientnet.FusedMBConv",
• "torch.nn.modules.pooling.AvgPool2d",
• "torchvision.models.maxvit.WindowDepartition",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torchvision.models.maxvit.PartitionAttentionLayer",
• "torch.nn.modules.activation.SiLU",
• "torchvision.models.maxvit.MBConv",
• "torchvision.models.maxvit.SwapAxes",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.conv.Conv2d",
• "torch._utils._rebuild_tensor_v2",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.container.ModuleList",
• "torchvision.models.maxvit.MaxVitLayer",
• "torch.nn.modules.activation.Tanh",
• "torchvision.ops.misc.SqueezeExcitation",
• "torch.nn.modules.activation.GELU",
• "torchvision.models.maxvit.MaxVit",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.normalization.LayerNorm",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torchvision.ops.stochastic_depth.StochasticDepth",
• "torch.nn.modules.activation.Sigmoid",
• "torchvision.ops.misc.Conv2dNormActivation",
• "collections.OrderedDict"

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