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a16f583 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | import torch
from modelCNNMultiYear import Small3DCNN
from config import bands_list_order, window_size, time_before
def count_parameters(model):
"""Count the total number of trainable parameters in a PyTorch model."""
return sum(p.numel() for p in model.parameters() if p.requires_grad)
def main():
# Model configuration matching your training script
model = Small3DCNN(
input_channels=len(bands_list_order), # Number of input bands
input_height=window_size, # Spatial height
input_width=window_size, # Spatial width
input_time=time_before # Temporal dimension
)
# Count parameters
total_params = count_parameters(model)
# Print detailed breakdown
print("MultiYearCNN (Small3DCNN) Parameter Breakdown:")
for name, param in model.named_parameters():
if param.requires_grad:
print(f"{name}: {param.numel()} parameters")
print(f"\nTotal Trainable Parameters: {total_params:,}")
if __name__ == "__main__":
main()
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