Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
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Ch1 TFP: Specify the posterior sampler
Hi there,
This section:
], kernel_results = graph_sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=initial_chain_state,
kernel = kernel)
Is giving the following error:
TypeError: Tensor is unhashable. Instead, use tensor.ref() as the key.