Debug

SOL provides a series of debug and visualization features.

Code Debugging

SOL’s generated code can be debugged by setting:

sol.config["jit::debug"]=True

Python based frameworks

For Python based frameworks you can then execute the following series of commands:

gdb python3
run myscript.py

or run interactively

gdb python3
run
# starting from here the Python console will be active.
# use CTRL+C to switch back to GDB
import framework
import sol
model = init_model()
sol_model = sol.optimize(...)

Computation Graph

Option Description
sol.config["compiler::debug"]=True plots the input CG, and a separate CG for every device and execution pass.
sol.config["compiler::debug_params"]=True adds also parameter and copy nodes to the output. All plots are in SVG format and stored in $CWD/.sol/debug.
sol.config["compiler::name"]="string" Can be used to assign a name to the debug output.
sol.config["compiler::debug_text"]=True Generates a textual representation of your computation graph, in case your graph is too complex.

Debug CG

Memory Consumption

sol.config["compiler::debug_memory_consumption"]=True

plots the memory consumption for all devices and execution passes in $CWD/.sol/debug/*_memory.svg.

Colors:

  • Blue: Fully managed by framework
  • Red: Allocated by SOL, freed by framework
  • Green: Fully managed by SOL

Labels:

  • inputs: Model inputs
  • parameters: Model parameters
  • outputs: Model outputs
  • gradients: Model gradients (only backward pass)
  • copies: Data shared between forward and backward pass in training
  • intermediate: Data shared between SOL fused layers
  • device: Temporary data stored in device main memory during execution of fused layer
  • core: Temporary data stored per core during execution of fused layer

Debug Memory