AudioEncoder( (base): HTSATWrapper( (htsat): HTSAT_Swin_Transformer( (spectrogram_extractor): Spectrogram( (stft): STFT( (conv_real): Conv1d(1, 513, kernel_size=(1024,), stride=(320,), bias=False) (conv_imag): Conv1d(1, 513, kernel_size=(1024,), stride=(320,), bias=False) ) ) (logmel_extractor): LogmelFilterBank() (spec_augmenter): SpecAugmentation( (time_dropper): DropStripes() (freq_dropper): DropStripes() ) (bn0): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (patch_embed): PatchEmbed( (proj): Conv2d(1, 96, kernel_size=(4, 4), stride=(4, 4)) (norm): LayerNorm((96,), eps=1e-05, elementwise_affine=True) ) (pos_drop): Dropout(p=0.0, inplace=False) (layers): ModuleList( (0): BasicLayer( dim=96, input_resolution=(64, 64), depth=2 (blocks): ModuleList( (0): SwinTransformerBlock( dim=96, input_resolution=(64, 64), num_heads=4, window_size=8, shift_size=0, mlp_ratio=4.0 (norm1): LayerNorm((96,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=96, window_size=(8, 8), num_heads=4 (qkv): Linear(in_features=96, out_features=288, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=96, out_features=96, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): Identity() (norm2): LayerNorm((96,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=96, out_features=384, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=384, out_features=96, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) (1): SwinTransformerBlock( dim=96, input_resolution=(64, 64), num_heads=4, window_size=8, shift_size=4, mlp_ratio=4.0 (norm1): LayerNorm((96,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=96, window_size=(8, 8), num_heads=4 (qkv): Linear(in_features=96, out_features=288, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=96, out_features=96, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((96,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=96, out_features=384, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=384, out_features=96, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) ) (downsample): PatchMerging( input_resolution=(64, 64), dim=96 (reduction): Linear(in_features=384, out_features=192, bias=False) (norm): LayerNorm((384,), eps=1e-05, elementwise_affine=True) ) ) (1): BasicLayer( dim=192, input_resolution=(32, 32), depth=2 (blocks): ModuleList( (0): SwinTransformerBlock( dim=192, input_resolution=(32, 32), num_heads=8, window_size=8, shift_size=0, mlp_ratio=4.0 (norm1): LayerNorm((192,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=192, window_size=(8, 8), num_heads=8 (qkv): Linear(in_features=192, out_features=576, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=192, out_features=192, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((192,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=192, out_features=768, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=768, out_features=192, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) (1): SwinTransformerBlock( dim=192, input_resolution=(32, 32), num_heads=8, window_size=8, shift_size=4, mlp_ratio=4.0 (norm1): LayerNorm((192,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=192, window_size=(8, 8), num_heads=8 (qkv): Linear(in_features=192, out_features=576, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=192, out_features=192, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((192,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=192, out_features=768, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=768, out_features=192, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) ) (downsample): PatchMerging( input_resolution=(32, 32), dim=192 (reduction): Linear(in_features=768, out_features=384, bias=False) (norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) ) ) (2): BasicLayer( dim=384, input_resolution=(16, 16), depth=6 (blocks): ModuleList( (0): SwinTransformerBlock( dim=384, input_resolution=(16, 16), num_heads=16, window_size=8, shift_size=0, mlp_ratio=4.0 (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=384, window_size=(8, 8), num_heads=16 (qkv): Linear(in_features=384, out_features=1152, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=384, out_features=384, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=384, out_features=1536, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=1536, out_features=384, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) (1): SwinTransformerBlock( dim=384, input_resolution=(16, 16), num_heads=16, window_size=8, shift_size=4, mlp_ratio=4.0 (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=384, window_size=(8, 8), num_heads=16 (qkv): Linear(in_features=384, out_features=1152, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=384, out_features=384, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=384, out_features=1536, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=1536, out_features=384, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) (2): SwinTransformerBlock( dim=384, input_resolution=(16, 16), num_heads=16, window_size=8, shift_size=0, mlp_ratio=4.0 (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=384, window_size=(8, 8), num_heads=16 (qkv): Linear(in_features=384, out_features=1152, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=384, out_features=384, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=384, out_features=1536, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=1536, out_features=384, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) (3): SwinTransformerBlock( dim=384, input_resolution=(16, 16), num_heads=16, window_size=8, shift_size=4, mlp_ratio=4.0 (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=384, window_size=(8, 8), num_heads=16 (qkv): Linear(in_features=384, out_features=1152, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=384, out_features=384, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=384, out_features=1536, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=1536, out_features=384, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) (4): SwinTransformerBlock( dim=384, input_resolution=(16, 16), num_heads=16, window_size=8, shift_size=0, mlp_ratio=4.0 (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=384, window_size=(8, 8), num_heads=16 (qkv): Linear(in_features=384, out_features=1152, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=384, out_features=384, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=384, out_features=1536, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=1536, out_features=384, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) (5): SwinTransformerBlock( dim=384, input_resolution=(16, 16), num_heads=16, window_size=8, shift_size=4, mlp_ratio=4.0 (norm1): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=384, window_size=(8, 8), num_heads=16 (qkv): Linear(in_features=384, out_features=1152, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=384, out_features=384, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((384,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=384, out_features=1536, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=1536, out_features=384, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) ) (downsample): PatchMerging( input_resolution=(16, 16), dim=384 (reduction): Linear(in_features=1536, out_features=768, bias=False) (norm): LayerNorm((1536,), eps=1e-05, elementwise_affine=True) ) ) (3): BasicLayer( dim=768, input_resolution=(8, 8), depth=2 (blocks): ModuleList( (0-1): 2 x SwinTransformerBlock( dim=768, input_resolution=(8, 8), num_heads=32, window_size=8, shift_size=0, mlp_ratio=4.0 (norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) (attn): WindowAttention( dim=768, window_size=(8, 8), num_heads=32 (qkv): Linear(in_features=768, out_features=2304, bias=True) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Linear(in_features=768, out_features=768, bias=True) (proj_drop): Dropout(p=0.0, inplace=False) (softmax): Softmax(dim=-1) ) (drop_path): DropPath() (norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) (mlp): Mlp( (fc1): Linear(in_features=768, out_features=3072, bias=True) (act): GELU(approximate='none') (fc2): Linear(in_features=3072, out_features=768, bias=True) (drop): Dropout(p=0.0, inplace=False) ) ) ) ) ) (norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) (avgpool): AdaptiveAvgPool1d(output_size=1) (maxpool): AdaptiveMaxPool1d(output_size=1) (tscam_conv): Conv2d(768, 527, kernel_size=(2, 3), stride=(1, 1), padding=(0, 1)) (head): Linear(in_features=527, out_features=527, bias=True) ) ) (projection): Projection( (linear1): Linear(in_features=768, out_features=1024, bias=False) (linear2): Linear(in_features=1024, out_features=1024, bias=False) (layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) (drop): Dropout(p=0.5, inplace=False) ) )