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um_anlp_tutorial_image_to_caption_dogs_and_babies

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• "x_transformers.attend.create_causal_mask",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.linear.Identity",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.conv.Conv2d",
• "torch.nn.functional.softmax",
• "transformers.models.swin.modeling_swin.SwinForImageClassification",
• "__builtin__.set",
• "transformers.models.swin.modeling_swin.SwinDropPath",
• "transformers.models.swin.modeling_swin.SwinSelfAttention",
• "transformers.models.swin.configuration_swin.SwinConfig",
• "transformers.models.swin.modeling_swin.SwinEmbeddings",
• "x_transformers.x_transformers.TransformerWrapper",
• "transformers.models.swin.modeling_swin.SwinPatchEmbeddings",
• "x_transformers.x_transformers.FeedForward",
• "torch.nn.modules.activation.GELU",
• "torch.nn.modules.sparse.Embedding",
• "torch._utils._rebuild_tensor_v2",
• "transformers.models.swin.modeling_swin.SwinLayer",
• "x_transformers.attend.Attend",
• "transformers.models.swin.modeling_swin.SwinPatchMerging",
• "transformers.models.swin.modeling_swin.SwinModel",
• "transformers.models.swin.modeling_swin.SwinStage",
• "transformers.models.swin.modeling_swin.SwinAttention",
• "transformers.models.vit.image_processing_vit.ViTImageProcessor",
• "x_transformers.x_transformers.AbsolutePositionalEmbedding",
• "torch.nn.modules.container.ModuleList",
• "torch.FloatStorage",
• "collections.OrderedDict",
• "__main__.SwinEncoder",
• "transformers.activations.GELUActivation",
• "torch.nn.modules.dropout.Dropout",
• "torch.nn.modules.normalization.LayerNorm",
• "torch._C._nn.gelu",
• "transformers.models.swin.modeling_swin.SwinOutput",
• "transformers.models.swin.modeling_swin.SwinIntermediate",
• "torch.nn.modules.pooling.AdaptiveAvgPool1d",
• "x_transformers.attend.EfficientAttentionConfig",
• "x_transformers.x_transformers.TokenEmbedding",
• "functools.partial",
• "x_transformers.x_transformers.Residual",
• "x_transformers.x_transformers.Attention",
• "torch.LongStorage",
• "transformers.models.swin.modeling_swin.SwinSelfOutput",
• "torch.float32",
• "transformers.models.swin.modeling_swin.SwinEncoder",
• "x_transformers.autoregressive_wrapper.AutoregressiveWrapper",
• "x_transformers.x_transformers.Decoder"

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