Fix: include root module in parameter calculation

[Yui-Arthur]

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Problem

When passing a single layer (e.g., nn.Conv2d) directly to profile(), the function reports 0 parameters. This happens because the parameter count of the root module itself was ignored during the dfs process.
(Fixes #115)

Changes

• Initialized total_params with module.total_params in dfs_count() to ensure the root module's parameters are included.

Minimal reproducible example (Issue #115)

from thop import profile
import torch
import torch.nn as nn

class test_model(nn.Module):
    def __init__(self):
        super().__init__()
        self.layer = nn.Conv2d(3, 10, (3,3))

    def forward(self, input):
        return self.layer(input)


layer = nn.Conv2d(3, 10, (3,3))
model = test_model()

macs, weight = profile(layer, torch.zeros(1,3,224,224))
print("Single Layer Profile Weights: ", weight)
# Single Layer Profile Weights:  280.0
macs, weight = profile(model, torch.zeros(1,3,224,224))
print("Model Profile Weights: ", weight)
# Model Profile Weights:  280.0

Before fix the single layer profile will got zero weights, after fix the profile can get correct weights

🛠️ PR Summary

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🌟 Summary

Fixes parameter counting in thop/profile.py by including the root module’s own parameters in the total. 🧮✅

📊 Key Changes

-Updates dfs_count() to initialize total_params from module.total_params.item() instead of 0.
-Makes parameter aggregation consistent with operation counting (which already includes the current module). 🔧

🎯 Purpose & Impact

-Prevents undercounting parameters for models where the top-level/root module has parameters. 🐛➡️✅
-Improves accuracy and trustworthiness of profiling outputs (params + ops) for end users running THOP profiling. 📈

[github-actions]

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[UltralyticsAssistant]

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[UltralyticsAssistant]

🔍 PR Review

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PR looks clean. The change correctly aligns parameter counting with ops counting by including the root module’s parameters. No issues found.

[Yui-Arthur]

Thank you for your submission, we really appreciate it. Like many open-source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution. You can sign the CLA by just posting a Pull Request Comment same as the below format.

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You can retrigger this bot by commenting recheck in this Pull Request. Posted by the CLA Assistant Lite bot.

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Superseded by new review

[UltralyticsAssistant]

🔍 PR Review 2

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Review complete. No issues found in the diff; the change correctly includes root module parameters without introducing problems.

Superseded by new review

[UltralyticsAssistant]

🔍 PR Review 3

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Clean change that correctly includes root module parameters in the DFS count. No issues found.

[Yui-Arthur]

I have read the CLA Document and I sign the CLA