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Turing currently generates initial params and passes it to external samplers:
Turing.jl/src/mcmc/external_sampler.jl
Lines 159 to 163 in 4dc7ad0
| # We need to extract the vectorised initial_params, because the later call to | |
| # AbstractMCMC.step only sees a `LogDensityModel` which expects `initial_params` | |
| # to be a vector. | |
| initial_params_vector = varinfo[:] | |
However, this might be a bit too simplistic. The HMC implementation for example currently tries a lot of times to generate initial parameters until it can find something where the logp and gradient are finite. Just giving it one attempt might make it hard to actually get started with sampling.
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