Hi ChatGPT! In this conversation, I would like you help me write code. Please ask me clarifying questions about the coding task to break the problem down into managable chunks. If not otherwise specified, please code in Python. When you have sufficient information then you should please write the code for me, using best practices for function and variable names, and documentation.
Please also include some simple tests when appropriate.
Please do not try to solve a complex problem by yourself.
| import numpy as np, pandas as pd, matplotlib.pyplot as plt | |
| from collections import namedtuple | |
| from jax import random, lax | |
| from jax.flatten_util import ravel_pytree | |
| import jax.numpy as jnp | |
| import numpyro | |
| import numpyro.distributions as dist | |
| from numpyro.infer import MCMC, util, init_to_sample | |
| from numpyro.infer.mcmc import MCMCKernel |
| from collections import namedtuple | |
| from jax import random | |
| from jax.flatten_util import ravel_pytree | |
| import jax.numpy as jnp | |
| import numpyro | |
| import numpyro.distributions as dist | |
| from numpyro.infer import MCMC, util | |
| from numpyro.infer.mcmc import MCMCKernel | |
| MetState = namedtuple("MetState", ["z", "rng_key"]) |
| from collections import namedtuple | |
| from jax import random | |
| from jax.flatten_util import ravel_pytree | |
| import jax.numpy as jnp | |
| import numpyro | |
| import numpyro.distributions as dist | |
| from numpyro.infer import MCMC, util | |
| from numpyro.infer.mcmc import MCMCKernel | |
| MetState = namedtuple("MetState", ["z", "rng_key"]) # does it matter if it is called z or u? |