Informer(
(enc_embedding): DataEmbedding(
(value_embedding): TokenEmbedding(
(tokenConv): Conv1d(3, 624, kernel_size=(3,), stride=(1,), padding=(1,), padding_mode=circular)
)
(position_embedding): PositionalEmbedding()
(temporal_embedding): TimeFeatureEmbedding(
(embed): Linear(in_features=5, out_features=624, bias=True)
)
(dropout): Dropout(p=0.05, inplace=False)
)
(dec_embedding): DataEmbedding(
(value_embedding): TokenEmbedding(
(tokenConv): Conv1d(3, 624, kernel_size=(3,), stride=(1,), padding=(1,), padding_mode=circular)
)
(position_embedding): PositionalEmbedding()
(temporal_embedding): TimeFeatureEmbedding(
(embed): Linear(in_features=5, out_features=624, bias=True)
)
(dropout): Dropout(p=0.05, inplace=False)
)
(encoder): Encoder(
(attn_layers): ModuleList(
(0): EncoderLayer(
(attention): AttentionLayer(
(inner_attention): ProbAttention(
(dropout): Dropout(p=0.05, inplace=False)
)
(query_projection): Linear(in_features=624, out_features=616, bias=True)
(key_projection): Linear(in_features=624, out_features=616, bias=True)
(value_projection): Linear(in_features=624, out_features=616, bias=True)
(out_projection): Linear(in_features=616, out_features=624, bias=True)
)
(conv1): Conv1d(624, 2048, kernel_size=(1,), stride=(1,))
(conv2): Conv1d(2048, 624, kernel_size=(1,), stride=(1,))
(norm1): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
(norm2): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
(dropout): Dropout(p=0.05, inplace=False)
)
(1): EncoderLayer(
(attention): AttentionLayer(
(inner_attention): ProbAttention(
(dropout): Dropout(p=0.05, inplace=False)
)
(query_projection): Linear(in_features=624, out_features=616, bias=True)
(key_projection): Linear(in_features=624, out_features=616, bias=True)
(value_projection): Linear(in_features=624, out_features=616, bias=True)
(out_projection): Linear(in_features=616, out_features=624, bias=True)
)
(conv1): Conv1d(624, 2048, kernel_size=(1,), stride=(1,))
(conv2): Conv1d(2048, 624, kernel_size=(1,), stride=(1,))
(norm1): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
(norm2): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
(dropout): Dropout(p=0.05, inplace=False)
)
)
(conv_layers): ModuleList(
(0): ConvLayer(
(downConv): Conv1d(624, 624, kernel_size=(3,), stride=(1,), padding=(1,), padding_mode=circular)
(norm): BatchNorm1d(624, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(activation): ELU(alpha=1.0)
(maxPool): MaxPool1d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)
)
)
(norm): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
)
(decoder): Decoder(
(layers): ModuleList(
(0): DecoderLayer(
(self_attention): AttentionLayer(
(inner_attention): ProbAttention(
(dropout): Dropout(p=0.05, inplace=False)
)
(query_projection): Linear(in_features=624, out_features=616, bias=True)
(key_projection): Linear(in_features=624, out_features=616, bias=True)
(value_projection): Linear(in_features=624, out_features=616, bias=True)
(out_projection): Linear(in_features=616, out_features=624, bias=True)
)
(cross_attention): AttentionLayer(
(inner_attention): FullAttention(
(dropout): Dropout(p=0.05, inplace=False)
)
(query_projection): Linear(in_features=624, out_features=616, bias=True)
(key_projection): Linear(in_features=624, out_features=616, bias=True)
(value_projection): Linear(in_features=624, out_features=616, bias=True)
(out_projection): Linear(in_features=616, out_features=624, bias=True)
)
(conv1): Conv1d(624, 2048, kernel_size=(1,), stride=(1,))
(conv2): Conv1d(2048, 624, kernel_size=(1,), stride=(1,))
(norm1): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
(norm2): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
(norm3): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
(dropout): Dropout(p=0.05, inplace=False)
)
)
(norm): LayerNorm((624,), eps=1e-05, elementwise_affine=True)
)
(projection): Linear(in_features=624, out_features=1, bias=True)
)