Table 2 All layers with weights and trainable parameters in the proposed method
From: ET-GRU: using multi-layer gated recurrent units to identify electron transport proteins
Layer | Weights | Parameters |
|---|---|---|
Conv1d (20, 200, 3) | ((200, 20, 3), (200,)) | 12,200 |
AvgPool1d (3) | 0 | 0 |
Conv1d (200, 200, 3) | ((200, 200, 3), (200,)) | 120,200 |
AvgPool1d (3) | 0 | 0 |
GRU (200, 200, 1) | ((600, 200), (600, 200), (600,), (600,)) | 241,200 |
Linear (200, 32) | ((32, 200), (32,)) | 6432 |
Dropout (0.5) | 0 | 0 |
Linear (32, 1) | ((1, 32), (1,)) | 33 |
Sigmoid () | 0 | 0 |