import jax
from jax import numpy as jnp

# Define a model using FLAX with functional programming style
@jax.jit
def model(params, inputs):
    dense = flax.nn.Dense(inputs.shape[-1], features=64)
    x = dense.initialize_carry(jax.random.PRNGKey(0), inputs)
    x = flax.nn.relu(x)
    output = flax.nn.Dense(x.shape[-1], features=10).initialize_carry(jax.random.PRNGKey(0), x)
    return output

# Train the model
optimizer = flax.optim.Adam(learning_rate=0.001).create(model.params)
for batch in dataset:
    optimizer = optimizer.train_step(batch)

        __
        __