MCP not converged: PATH solver status is MCP_NoProgress.

[TianleLiu0303]

julia> DrivingExample.train_generative_model_with_driving_data()
Sampling initial states and goals...
Epoch 1
┌ Warning: Layer with Float32 parameters got Float64 input.
│ The input will be converted, but any earlier layers may be very slow.
│ layer = Dense(60 => 128, relu) # 7_808 parameters
│ summary(x) = "60×8540 Matrix{Float64}"
└ @ Flux ~/.julia/packages/Flux/HBF2N/src/layers/stateless.jl:60
┌ Warning: MCP not converged: PATH solver status is MCP_NoProgress.
└ @ ParametricMCPs ~/.julia/packages/ParametricMCPs/dAY45/src/solver.jl:50
┌ Warning: MCP not converged: PATH solver status is MCP_NoProgress.
└ @ ParametricMCPs ~/.julia/packages/ParametricMCPs/dAY45/src/solver.jl:50
┌ Warning: MCP not converged: PATH solver status is MCP_NoProgress.
└ @ ParametricMCPs ~/.julia/packages/ParametricMCPs/dAY45/src/solver.jl:50
┌ Warning: MCP not converged: PATH solver status is MCP_NoProgress.
└ @ ParametricMCPs ~/.julia/packages/ParametricMCPs/dAY45/src/solver.jl:50

[xinjie-liu]

Hi, could you provide a minimum piece of code to reproduce the warning?