I want to see detail until layer.weight and layer.bias, and it seems this is only possible with verbose=2.
I tried setting max_depth=1000, but with verbose=1 the 'weight'/'bias' parameters are never shown in the summary.
With verbose=2, the weighs show up twice for some reason. Once at the top-level, and once under their actual layer (see below)
To Reproduce
import torch
import torch.nn as nn
from torchinfo import summary
model = nn.Sequential(
nn.Linear(10,10),
nn.Sequential(
nn.Linear(10,10),
nn.Linear(10,10)
)
)
model_stats = summary(
model,
input_data=torch.randn(size=(1, 10)),
verbose=2,
col_names=["output_size", "kernel_size", "num_params", "mult_adds"],
)
Describe the bug
I want to see detail until layer.weight and layer.bias, and it seems this is only possible with verbose=2. I tried setting max_depth=1000, but with verbose=1 the 'weight'/'bias' parameters are never shown in the summary.
With verbose=2, the weighs show up twice for some reason. Once at the top-level, and once under their actual layer (see below)
To Reproduce
Output:
Expected behavior