GWZhong

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CIDer

like 0

• "torch.nn.modules.activation.Tanh",
• "transformers.models.bert.configuration_bert.BertConfig",
• "modules.transformer.TransformerEncoder",
• "torch.nn.modules.activation.ReLU",
• "modules.position_embedding.PositionalEmbedding",
• "transformers.models.bert.modeling_bert.BertSelfOutput",
• "transformers.activations.GELUActivation",
• "transformers.models.bert.modeling_bert.BertModel",
• "transformers.models.bert.modeling_bert.BertOutput",
• "transformers.models.bert.tokenization_bert.BasicTokenizer",
• "torch.nn.modules.conv.Conv1d",
• "transformers.models.bert.tokenization_bert.WordpieceTokenizer",
• "tokenizers.AddedToken",
• "transformers.models.bert.modeling_bert.BertEmbeddings",
• "torch.FloatStorage",
• "transformers.models.bert.modeling_bert.BertPooler",
• "torch.LongStorage",
• "torch.nn.modules.linear.Linear",
• "torch._utils._rebuild_parameter",
• "__builtin__.set",
• "src.models.CIDERModel",
• "transformers.models.bert.modeling_bert.BertLayer",
• "transformers.models.bert.modeling_bert.BertIntermediate",
• "torch.nn.modules.container.Sequential",
• "modules.transformer.TransformerEncoderLayer",
• "transformers.models.bert.modeling_bert.BertEncoder",
• "modules.multimodal_multihead_attention.MultimodalMultiheadAttention",
• "src.models.BertTextEncoder",
• "transformers.tokenization_utils.Trie",
• "torch.nn.modules.normalization.LayerNorm",
• "modules.compressed_multihead_attention.CompressedMultiheadAttention",
• "collections.OrderedDict",
• "torch._C._nn.gelu",
• "torch.nn.modules.rnn.GRU",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.sparse.Embedding",
• "transformers.models.bert.modeling_bert.BertSdpaSelfAttention",
• "torch.nn.modules.container.ModuleList",
• "transformers.models.bert.tokenization_bert.BertTokenizer",
• "transformers.models.bert.modeling_bert.BertAttention",
• "src.models.NaiveAttention",
• "torch.nn.modules.dropout.Dropout"

How to fix it?

• "torch._utils._rebuild_parameter",
• "transformers.models.bert.modeling_bert.BertIntermediate",
• "torch.nn.modules.activation.Tanh",
• "transformers.models.bert.tokenization_bert.WordpieceTokenizer",
• "torch.nn.modules.activation.ReLU",
• "torch._utils._rebuild_tensor_v2",
• "transformers.models.bert.modeling_bert.BertLayer",
• "src.models.NaiveAttention",
• "tokenizers.AddedToken",
• "modules.compressed_multihead_attention.CompressedMultiheadAttention",
• "modules.multimodal_multihead_attention.MultimodalMultiheadAttention",
• "src.models.BertTextEncoder",
• "collections.OrderedDict",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.container.ModuleList",
• "transformers.activations.GELUActivation",
• "torch.nn.modules.rnn.GRU",
• "src.models.CIDERModel",
• "transformers.models.bert.tokenization_bert.BertTokenizer",
• "torch._C._nn.gelu",
• "transformers.models.bert.modeling_bert.BertModel",
• "transformers.models.bert.modeling_bert.BertAttention",
• "transformers.models.bert.modeling_bert.BertSdpaSelfAttention",
• "torch.LongStorage",
• "__builtin__.set",
• "transformers.models.bert.modeling_bert.BertSelfOutput",
• "transformers.models.bert.modeling_bert.BertEmbeddings",
• "transformers.models.bert.configuration_bert.BertConfig",
• "transformers.models.bert.tokenization_bert.BasicTokenizer",
• "torch.FloatStorage",
• "torch.nn.modules.container.Sequential",
• "transformers.models.bert.modeling_bert.BertPooler",
• "modules.transformer.TransformerEncoderLayer",
• "torch.nn.modules.normalization.LayerNorm",
• "transformers.models.bert.modeling_bert.BertOutput",
• "modules.transformer.TransformerEncoder",
• "transformers.tokenization_utils.Trie",
• "torch.nn.modules.dropout.Dropout",
• "torch.nn.modules.conv.Conv1d",
• "transformers.models.bert.modeling_bert.BertEncoder",
• "modules.position_embedding.PositionalEmbedding",
• "torch.nn.modules.sparse.Embedding"

How to fix it?