TCN(
(tcn): Sequential(
(0): TemporalBlock(
(conv1): Conv1d(3, 25, kernel_size=(7,), stride=(1,), padding=(6,))
(chomp1): Chomp1d()
(relu1): ReLU()
(dropout1): Dropout(p=0.0, inplace=False)
(conv2): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(6,))
(chomp2): Chomp1d()
(relu2): ReLU()
(dropout2): Dropout(p=0.0, inplace=False)
(net): Sequential(
(0): Conv1d(3, 25, kernel_size=(7,), stride=(1,), padding=(6,))
(1): Chomp1d()
(2): ReLU()
(3): Dropout(p=0.0, inplace=False)
(4): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(6,))
(5): Chomp1d()
(6): ReLU()
(7): Dropout(p=0.0, inplace=False)
)
(downsample): Conv1d(3, 25, kernel_size=(1,), stride=(1,))
(relu): ReLU()
)
(1): TemporalBlock(
(conv1): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(12,), dilation=(2,))
(chomp1): Chomp1d()
(relu1): ReLU()
(dropout1): Dropout(p=0.0, inplace=False)
(conv2): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(12,), dilation=(2,))
(chomp2): Chomp1d()
(relu2): ReLU()
(dropout2): Dropout(p=0.0, inplace=False)
(net): Sequential(
(0): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(12,), dilation=(2,))
(1): Chomp1d()
(2): ReLU()
(3): Dropout(p=0.0, inplace=False)
(4): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(12,), dilation=(2,))
(5): Chomp1d()
(6): ReLU()
(7): Dropout(p=0.0, inplace=False)
)
(relu): ReLU()
)
(2): TemporalBlock(
(conv1): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(24,), dilation=(4,))
(chomp1): Chomp1d()
(relu1): ReLU()
(dropout1): Dropout(p=0.0, inplace=False)
(conv2): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(24,), dilation=(4,))
(chomp2): Chomp1d()
(relu2): ReLU()
(dropout2): Dropout(p=0.0, inplace=False)
(net): Sequential(
(0): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(24,), dilation=(4,))
(1): Chomp1d()
(2): ReLU()
(3): Dropout(p=0.0, inplace=False)
(4): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(24,), dilation=(4,))
(5): Chomp1d()
(6): ReLU()
(7): Dropout(p=0.0, inplace=False)
)
(relu): ReLU()
)
(3): TemporalBlock(
(conv1): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(48,), dilation=(8,))
(chomp1): Chomp1d()
(relu1): ReLU()
(dropout1): Dropout(p=0.0, inplace=False)
(conv2): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(48,), dilation=(8,))
(chomp2): Chomp1d()
(relu2): ReLU()
(dropout2): Dropout(p=0.0, inplace=False)
(net): Sequential(
(0): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(48,), dilation=(8,))
(1): Chomp1d()
(2): ReLU()
(3): Dropout(p=0.0, inplace=False)
(4): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(48,), dilation=(8,))
(5): Chomp1d()
(6): ReLU()
(7): Dropout(p=0.0, inplace=False)
)
(relu): ReLU()
)
(4): TemporalBlock(
(conv1): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(96,), dilation=(16,))
(chomp1): Chomp1d()
(relu1): ReLU()
(dropout1): Dropout(p=0.0, inplace=False)
(conv2): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(96,), dilation=(16,))
(chomp2): Chomp1d()
(relu2): ReLU()
(dropout2): Dropout(p=0.0, inplace=False)
(net): Sequential(
(0): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(96,), dilation=(16,))
(1): Chomp1d()
(2): ReLU()
(3): Dropout(p=0.0, inplace=False)
(4): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(96,), dilation=(16,))
(5): Chomp1d()
(6): ReLU()
(7): Dropout(p=0.0, inplace=False)
)
(relu): ReLU()
)
(5): TemporalBlock(
(conv1): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(192,), dilation=(32,))
(chomp1): Chomp1d()
(relu1): ReLU()
(dropout1): Dropout(p=0.0, inplace=False)
(conv2): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(192,), dilation=(32,))
(chomp2): Chomp1d()
(relu2): ReLU()
(dropout2): Dropout(p=0.0, inplace=False)
(net): Sequential(
(0): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(192,), dilation=(32,))
(1): Chomp1d()
(2): ReLU()
(3): Dropout(p=0.0, inplace=False)
(4): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(192,), dilation=(32,))
(5): Chomp1d()
(6): ReLU()
(7): Dropout(p=0.0, inplace=False)
)
(relu): ReLU()
)
(6): TemporalBlock(
(conv1): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(384,), dilation=(64,))
(chomp1): Chomp1d()
(relu1): ReLU()
(dropout1): Dropout(p=0.0, inplace=False)
(conv2): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(384,), dilation=(64,))
(chomp2): Chomp1d()
(relu2): ReLU()
(dropout2): Dropout(p=0.0, inplace=False)
(net): Sequential(
(0): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(384,), dilation=(64,))
(1): Chomp1d()
(2): ReLU()
(3): Dropout(p=0.0, inplace=False)
(4): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(384,), dilation=(64,))
(5): Chomp1d()
(6): ReLU()
(7): Dropout(p=0.0, inplace=False)
)
(relu): ReLU()
)
(7): TemporalBlock(
(conv1): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(768,), dilation=(128,))
(chomp1): Chomp1d()
(relu1): ReLU()
(dropout1): Dropout(p=0.0, inplace=False)
(conv2): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(768,), dilation=(128,))
(chomp2): Chomp1d()
(relu2): ReLU()
(dropout2): Dropout(p=0.0, inplace=False)
(net): Sequential(
(0): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(768,), dilation=(128,))
(1): Chomp1d()
(2): ReLU()
(3): Dropout(p=0.0, inplace=False)
(4): Conv1d(25, 25, kernel_size=(7,), stride=(1,), padding=(768,), dilation=(128,))
(5): Chomp1d()
(6): ReLU()
(7): Dropout(p=0.0, inplace=False)
)
(relu): ReLU()
)
)
(gap): GAP1d(
(gap): AdaptiveAvgPool1d(output_size=1)
(flatten): Flatten(full=False)
)
(linear): Linear(in_features=25, out_features=2, bias=True)
)