Transform jax samples

.github/workflows/jaxtests.yml

@@ -0,0 +1,64 @@
+name: jax-sampling
+
+on:
+  pull_request:
+  push:
+    branches: [master]
+
+jobs:
+  pytest:
+    strategy:
+      matrix:
+        os: [ubuntu-latest]
+        floatx: [float64]
+        test-subset:
+          - pymc3/tests/test_sampling_jax.py
+      fail-fast: false
+    runs-on: ${{ matrix.os }}
+    env:
+      TEST_SUBSET: ${{ matrix.test-subset }}
+      THEANO_FLAGS: floatX=${{ matrix.floatx }},gcc__cxxflags='-march=native'
+    defaults:
+      run:
+        shell: bash -l {0}
+    steps:
+      - uses: actions/checkout@v2
+      - name: Cache conda
+        uses: actions/cache@v1
+        env:
+          # Increase this value to reset cache if environment-dev-py39.yml has not changed
+          CACHE_NUMBER: 0
+        with:
+          path: ~/conda_pkgs_dir
+          key: ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-${{
+            hashFiles('conda-envs/environment-dev-py39.yml') }}
+      - name: Cache multiple paths
+        uses: actions/cache@v2
+        env:
+          # Increase this value to reset cache if requirements.txt has not changed
+          CACHE_NUMBER: 0
+        with:
+          path: |
+            ~/.cache/pip
+            $RUNNER_TOOL_CACHE/Python/*
+            ~\AppData\Local\pip\Cache
+          key: ${{ runner.os }}-build-${{ matrix.python-version }}-${{
+            hashFiles('requirements.txt') }}
+      - uses: conda-incubator/setup-miniconda@v2
+        with:
+          activate-environment: pymc3-dev-py39
+          channel-priority: strict
+          environment-file: conda-envs/environment-dev-py39.yml
+          use-only-tar-bz2: true # IMPORTANT: This needs to be set for caching to work properly!
+      - name: Install pymc3
+        run: |
+          conda activate pymc3-dev-py39
+          pip install -e .
+          python --version
+      - name: Install jax specific dependencies
+        run: |
+          conda activate pymc3-dev-py39
+          pip install numpyro tensorflow_probability
+      - name: Run tests
+        run: |
+          python -m pytest -vv --cov=pymc3 --cov-report=xml --cov-report term --durations=50 $TEST_SUBSET

.github/workflows/pytest.yml

@@ -27,6 +27,7 @@ jobs:
             --ignore=pymc3/tests/test_quadpotential.py
             --ignore=pymc3/tests/test_random.py
             --ignore=pymc3/tests/test_sampling.py
+            --ignore=pymc3/tests/test_sampling_jax.py
             --ignore=pymc3/tests/test_shape_handling.py
             --ignore=pymc3/tests/test_shared.py
             --ignore=pymc3/tests/test_smc.py

RELEASE-NOTES.md

@@ -5,7 +5,8 @@
 ### Breaking Changes
 
 ### New Features
-+ Automatic imputations now also work with `ndarray` data, not just `pd.Series` or `pd.DataFrame` (see[#4439](https://github.com/pymc-devs/pymc3/pull/4439)).
+- Automatic imputations now also work with `ndarray` data, not just `pd.Series` or `pd.DataFrame` (see[#4439](https://github.com/pymc-devs/pymc3/pull/4439)).
+- `pymc3.sampling_jax.sample_numpyro_nuts` now returns samples from transformed random variables, rather than from the unconstrained representation (see [#4427](https://github.com/pymc-devs/pymc3/pull/4427)).
 
 ### Maintenance
 - `math.log1mexp_numpy` no longer raises RuntimeWarning when given very small inputs. These were commonly observed during NUTS sampling (see [#4428](https://github.com/pymc-devs/pymc3/pull/4428)).

pymc3/sampling_jax.py

@@ -3,6 +3,8 @@
 import re
 import warnings
 
+from collections import defaultdict
+
 xla_flags = os.getenv("XLA_FLAGS", "").lstrip("--")
 xla_flags = re.sub(r"xla_force_host_platform_device_count=.+\s", "", xla_flags).split()
 os.environ["XLA_FLAGS"] = " ".join(["--xla_force_host_platform_device_count={}".format(100)])
@@ -121,6 +123,7 @@ def sample_numpyro_nuts(
     random_seed=10,
     model=None,
     progress_bar=True,
+    keep_untransformed=False,
 ):
     from numpyro.infer import MCMC, NUTS
 
@@ -175,8 +178,48 @@ def _sample(current_state, seed):
     # print("Sampling time = ", tic4 - tic3)
 
     posterior = {k: v for k, v in zip(rv_names, mcmc_samples)}
+    tic3 = pd.Timestamp.now()
+    posterior = _transform_samples(posterior, model, keep_untransformed=keep_untransformed)
+    tic4 = pd.Timestamp.now()
 
     az_trace = az.from_dict(posterior=posterior)
-    tic3 = pd.Timestamp.now()
     print("Compilation + sampling time = ", tic3 - tic2)
+    print("Transformation time = ", tic4 - tic3)
+
     return az_trace  # , leapfrogs_taken, tic3 - tic2
+
+
+def _transform_samples(samples, model, keep_untransformed=False):
+
+    # Find out which RVs we need to compute:
+    free_rv_names = {x.name for x in model.free_RVs}
+    unobserved_names = {x.name for x in model.unobserved_RVs}
+
+    names_to_compute = unobserved_names - free_rv_names
+    ops_to_compute = [x for x in model.unobserved_RVs if x.name in names_to_compute]
+
+    # Create function graph for these:
+    fgraph = theano.graph.fg.FunctionGraph(model.free_RVs, ops_to_compute)
+
+    # Jaxify, which returns a list of functions, one for each op
+    jax_fns = jax_funcify(fgraph)
+
+    # Put together the inputs
+    inputs = [samples[x.name] for x in model.free_RVs]
+
+    for cur_op, cur_jax_fn in zip(ops_to_compute, jax_fns):
+
+        # We need a function taking a single argument to run vmap, while the
+        # jax_fn takes a list, so:
+        result = jax.vmap(jax.vmap(cur_jax_fn))(*inputs)
+
+        # Add to sample dict
+        samples[cur_op.name] = result
+
+    # Discard unwanted transformed variables, if desired:
+    vars_to_keep = set(
+        pm.util.get_default_varnames(list(samples.keys()), include_transformed=keep_untransformed)
+    )
+    samples = {x: y for x, y in samples.items() if x in vars_to_keep}
+
+    return samples

pymc3/tests/test_sampling_jax.py

@@ -0,0 +1,19 @@
+import numpy as np
+
+import pymc3 as pm
+
+from pymc3.sampling_jax import sample_numpyro_nuts
+
+
+def test_transform_samples():
+
+    with pm.Model() as model:
+
+        sigma = pm.HalfNormal("sigma")
+        b = pm.Normal("b", sigma=sigma)
+        trace = sample_numpyro_nuts(keep_untransformed=True)
+
+    log_vals = trace.posterior["sigma_log__"].values
+    trans_vals = trace.posterior["sigma"].values
+
+    assert np.allclose(np.exp(log_vals), trans_vals)

scripts/check_all_tests_are_covered.py

@@ -12,13 +12,17 @@
 from pathlib import Path
 
 if __name__ == "__main__":
-    pytest_ci_job = Path(".github") / "workflows/pytest.yml"
-    txt = pytest_ci_job.read_text()
-    ignored_tests = set(re.findall(r"(?<=--ignore=)(pymc3/tests.*\.py)", txt))
-    non_ignored_tests = set(re.findall(r"(?<!--ignore=)(pymc3/tests.*\.py)", txt))
+    testing_workflows = ["jaxtests.yml", "pytest.yml"]
+    ignored = set()
+    non_ignored = set()
+    for wfyml in testing_workflows:
+        pytest_ci_job = Path(".github") / "workflows" / wfyml
+        txt = pytest_ci_job.read_text()
+        ignored = set(re.findall(r"(?<=--ignore=)(pymc3/tests.*\.py)", txt))
+        non_ignored = non_ignored.union(set(re.findall(r"(?<!--ignore=)(pymc3/tests.*\.py)", txt)))
     assert (
-        ignored_tests <= non_ignored_tests
-    ), f"The following tests are ignored by the first job but not run by the others: {ignored_tests.difference(non_ignored_tests)}"
+        ignored <= non_ignored
+    ), f"The following tests are ignored by the first job but not run by the others: {ignored.difference(non_ignored)}"
     assert (
-        ignored_tests >= non_ignored_tests
-    ), f"The following tests are run by multiple jobs: {non_ignored_tests.difference(ignored_tests)}"
+        ignored >= non_ignored
+    ), f"The following tests are run by multiple jobs: {non_ignored.difference(ignored)}"