Pytorch查看神经网络结构和参数量

基本方法

print(model)
print(type(model))

# 模型参数
numEl_list = [p.numel() for p in model.parameters()]
total_params_mb = sum(numEl_list) / 1e6

print(f'Total parameters: {total_params_mb:.2f} MB')
# sum(numEl_list), numEl_list
print(sum(numEl_list))
print(numEl_list)

# 查看模型参数的基本方法
def get_param_count(model):
    return sum(p.numel() for p in model.parameters() if p.requires_grad)

param_count = get_param_count(model)
print(f"Model Parameter Count: {param_count}")

# 计算每层参数量和大小
def print_layer_params_count(model):
    for name, param in model.named_parameters():
        if param.requires_grad:
            print(f"{name} : {param.numel()}")
            print(f"{name} : {param.shape}")

print_layer_params_count(model)

使用Pytorch中的torchsummary包

from torchsummary import summary
summary(model, input_size=(1, 1, 128, 128, 32))

使用第三方库torchinfo

from torchinfo import summary
summary(model, input_size=(1, 1, 128, 128, 32))