Fix jax.tree_util future warnings (pyro-ppl#1464)

* Fix jax.tree_util future warnings

* fix docker link

* Filter out warnings in contrib modules

* fix lint

* bypass isort in cvae

* Fix lint

docker/release/Dockerfile

@@ -7,8 +7,7 @@ FROM nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04
 
 # declare the image name
 # note that this image uses Python 3.8
-ENV IMG_NAME=11.2.2-cudnn8-devel-ubuntu20.04 \
-    JAXLIB_CUDA=111
+ENV IMG_NAME=11.2.2-cudnn8-devel-ubuntu20.04
 
 # install python3 and pip on top of the base Ubuntu image
 RUN apt update && \
@@ -21,4 +20,4 @@ ENV PATH=/root/.local/bin:$PATH
 RUN pip3 install --user \
     # we pull wheels from google's api as per https://github.com/google/jax#installation
     # the pre-compiled wheels that google provides work for now. This may change in the future (and necessitate building from source)
-    numpyro[cuda${JAXLIB_CUDA}] -f https://storage.googleapis.com/jax-releases/jax_releases.html
+    numpyro[cuda] -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

examples/cvae-flax/main.py

@@ -5,12 +5,13 @@
 
 from data import load_dataset
 import matplotlib.pyplot as plt
-from models import BaselineNet, Decoder, Encoder, cvae_guide, cvae_model
 from train_baseline import train_baseline
 from train_cvae import train_cvae
 
 from numpyro.examples.datasets import MNIST
 
+from models import BaselineNet, Decoder, Encoder, cvae_guide, cvae_model  # isort:skip
+
 
 def main(args):
     train_init, train_fetch = load_dataset(

examples/cvae-flax/train_baseline.py

@@ -1,13 +1,13 @@
 # Copyright Contributors to the Pyro project.
 # SPDX-License-Identifier: Apache-2.0
 
-from models import cross_entropy_loss
-
 from flax.training.train_state import TrainState
 import jax
 from jax import lax, numpy as jnp, random
 import optax
 
+from models import cross_entropy_loss  # isort:skip
+
 
 def create_train_state(model, x, learning_rate_fn):
     params = model.init(random.PRNGKey(0), x)

numpyro/contrib/control_flow/scan.py

@@ -4,8 +4,9 @@
 from collections import OrderedDict
 from functools import partial
 
-from jax import device_put, lax, random, tree_flatten, tree_map, tree_unflatten
+from jax import device_put, lax, random
 import jax.numpy as jnp
+from jax.tree_util import tree_flatten, tree_map, tree_unflatten
 
 from numpyro import handlers
 from numpyro.ops.pytree import PytreeTrace

numpyro/contrib/tfp/mcmc.py

@@ -5,9 +5,10 @@
 from collections import namedtuple
 import inspect
 
-from jax import random, tree_map, vmap
+from jax import random, vmap
 from jax.flatten_util import ravel_pytree
 import jax.numpy as jnp
+from jax.tree_util import tree_map
 import tensorflow_probability.substrates.jax as tfp
 
 from numpyro.infer import init_to_uniform

numpyro/infer/util.py

@@ -10,11 +10,11 @@
 import numpy as np
 
 import jax
-from jax import device_get, jacfwd, lax, random, tree_flatten, value_and_grad
+from jax import device_get, jacfwd, lax, random, value_and_grad
 from jax.flatten_util import ravel_pytree
 from jax.lax import broadcast_shapes
 import jax.numpy as jnp
-from jax.tree_util import tree_map
+from jax.tree_util import tree_flatten, tree_map
 
 import numpyro
 from numpyro.distributions import constraints

setup.cfg

@@ -22,6 +22,7 @@ skip=docs
 filterwarnings = error
     ignore:numpy.ufunc size changed,:RuntimeWarning
     ignore:Using a non-tuple sequence:FutureWarning
+    ignore:jax.tree_structure is deprecated:FutureWarning
     ignore:numpy.linalg support is experimental:UserWarning
     ignore:scipy.linalg support is experimental:UserWarning
     once:No GPU:UserWarning

test/contrib/test_module.py

@@ -23,6 +23,10 @@
 import numpyro.distributions as dist
 from numpyro.infer import MCMC, NUTS
 
+pytestmark = pytest.mark.filterwarnings(
+    "ignore:jax.tree_.+ is deprecated:FutureWarning"
+)
+
 
 def haiku_model_by_shape(x, y):
     import haiku as hk

test/contrib/test_nested_sampling.py

@@ -13,6 +13,10 @@
 import numpyro.distributions as dist
 from numpyro.distributions.transforms import AffineTransform, ExpTransform
 
+pytestmark = pytest.mark.filterwarnings(
+    "ignore:jax.tree_.+ is deprecated:FutureWarning"
+)
+
 
 # Test helper to extract a few central moments from samples.
 def get_moments(x):