Goal: Export Tensorflow graphs from Python for use in C

Direct Answer

Validate data/label shape and preprocessing first; only tune model hyperparameters after baseline correctness.

Recommended Workflow

1. Reproduce the requirement or issue in a minimal setup.
2. Confirm environment assumptions (version, config, permissions, and runtime context).
3. Apply the smallest targeted implementation change.
4. Re-validate with a representative real-world input.

Concrete Example

import numpy as np
probs = np.array([0.1, 0.7, 0.2])
print(probs.argmax())

Validation Checklist

• Expected output is produced for the primary scenario.
• Edge cases are handled explicitly.
• The change is reproducible in your target environment.

Common Pitfalls

• Shape mismatch between model outputs and labels.
• Data leakage from preprocessing.
• Tuning before baseline correctness.

Summary

Make the baseline behavior correct and observable first; optimize only after correctness is proven. Tags: TensorFlow, Python, C++, machine learning, graph export.