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February 12, 2020 14:03
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jax learning step wrt non-diff'able parameterds like integers.
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import jax | |
import jax.experimental.optimizers | |
from jax.api import _check_inexact_input_vjp | |
from jax import tree_util as tu | |
import numpy as onp | |
def make_resilient_step(loss, sample_params, split, join, optimizer): | |
sample_learn_params, non_learn_params = split(sample_params) | |
def guarded_loss(learn_params, *args, **kwargs): | |
params = join(learn_params, non_learn_params) | |
return loss(params, *args, **kwargs) | |
d_guarded_loss = jax.grad(guarded_loss) | |
opt_init, opt_update, get_params = optimizer | |
opt_state = opt_init(sample_learn_params) | |
@jax.jit | |
def step(opt_state, *args, **kwargs): | |
params = get_params(opt_state) | |
loss = guarded_loss(params, *args, **kwargs) | |
g = d_guarded_loss(params, *args, **kwargs) | |
return loss, opt_update(1, g, opt_state) | |
return opt_state, step | |
def func(params): | |
return params["c"] ** 2 * params["d"] | |
def split(params): | |
def tell_include(leaf): | |
return jax.dtypes.issubdtype( | |
jax.core.get_aval(leaf).dtype, onp.inexact | |
) | |
flattened, tree_def = tu.tree_flatten(params) | |
to_include = [i for i in flattened if tell_include(i)] | |
to_exclude_and_idxs = [ | |
(i, val) for i, val in enumerate(flattened) if not tell_include(val) | |
] | |
return to_include, (tree_def, to_exclude_and_idxs) | |
def join(included, excluded): | |
tree_def, excluded_leaves = excluded | |
all_leaves = included.copy() | |
for idx, leave in excluded_leaves: | |
all_leaves.insert(idx, leave) | |
return tu.tree_unflatten(tree_def, all_leaves) | |
optimizer = ( | |
opt_init, | |
opt_update, | |
get_params, | |
) = jax.experimental.optimizers.adam(step_size=0.01) | |
initial_params = {"c": 2.0, "d": 1} | |
opt_state, step = make_resilient_step( | |
func, | |
initial_params, | |
split=split, | |
join=join, | |
optimizer=optimizer, | |
) | |
for i in range(1000): | |
l, opt_state = step(opt_state) | |
pars = get_params(opt_state) | |
final_pars = join(pars, split(initial_params)[1]) | |
print(final_pars) |
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