Hi @shaahidh_shaji
If you need help compiling YOLO models, I would like to recommend a tool we developed known as the cloud compiler that compiles your checkpoint to hailo without any local setup. See Early Access to DeGirum Cloud Compiler. Please see it can help.
The timeout and mapping failures you’re seeing aren’t actually solved by setting allocator_param(timeout=100h). Even with that extended timeout, you’re hitting deeper architectural issues that no amount of waiting time will fix.
What’s Really Happening:
Your allocator_param(timeout=100h) just tells the compiler to keep trying for up to 100 hours before giving up. But the “Mapping Failed” errors with those reverts indicate structural problems that won’t resolve with more time:
3 inter-cluster connectivity reverts: The compiler can’t efficiently route data between clusters, usually because of bandwidth limits, poor layer partitioning, or overloaded cluster resources
1 pre-mapping validation revert: There are incompatible layer configurations, problematic quantization settings, or unresolvable operator fusions
The repeated Auto-Merger attempts show the compiler is trying to optimize layer merging but failing, likely due to your forced quantization ranges restricting merge flexibility.
Here’s what to try:
Fix the cluster issues:
Switch from single_context_flow() to multi_context_flow() for more flexible cluster assignment
Debug the problem layers:
Use dump_debug_graph(...) to see exactly which layers are causing the inter-cluster reverts
Rethink your quantization:
That quantization_param([conv42, conv53, conv63], force_range_out=[0.0, 1.0]) might be hurting more than helping
Try removing force_range_out and let the compiler choose optimal ranges
Tone down resource limits:
Your max_control_utilization=117.5% is over 100%, which can cause allocations that get rejected later