Enable progress bar under pmap

blackjax/adaptation/window_adaptation.py

@@ -334,16 +334,22 @@ def run(rng_key: PRNGKey, position: ArrayLikeTree, num_steps: int = 1000):
         if progress_bar:
             print("Running window adaptation")
             one_step_ = jax.jit(progress_bar_scan(num_steps)(one_step))
+            start_state = ((init_state, init_adaptation_state), -1)
         else:
             one_step_ = jax.jit(one_step)
+            start_state = (init_state, init_adaptation_state)
 
         keys = jax.random.split(rng_key, num_steps)
         schedule = build_schedule(num_steps)
         last_state, info = jax.lax.scan(
             one_step_,
-            (init_state, init_adaptation_state),
+            start_state,
             (jnp.arange(num_steps), keys, schedule),
         )
+
+        if progress_bar:
+            last_state, _ = last_state
+
         last_chain_state, last_warmup_state, *_ = last_state
 
         step_size, inverse_mass_matrix = adapt_final(last_warmup_state)

blackjax/progress_bar.py

@@ -14,56 +14,64 @@
 """Progress bar decorators for use with step functions.
 Adapted from Jeremie Coullon's blog post :cite:p:`progress_bar`.
 """
+from threading import Lock
+
 from fastprogress.fastprogress import progress_bar
 from jax import lax
 from jax.experimental import io_callback
+from jax.numpy import array
 
 
 def progress_bar_scan(num_samples, print_rate=None):
     "Progress bar for a JAX scan"
     progress_bars = {}
+    idx_counter = 0
+    lock = Lock()
 
     if print_rate is None:
         if num_samples > 20:
             print_rate = int(num_samples / 20)
         else:
             print_rate = 1  # if you run the sampler for less than 20 iterations
 
-    def _define_bar(arg):
-        del arg
-        progress_bars[0] = progress_bar(range(num_samples))
-        progress_bars[0].update(0)
+    def _calc_chain_idx(iter_num):
+        nonlocal idx_counter
+        with lock:
+            idx = idx_counter
+            idx_counter += 1
+        return idx
+
+    def _update_bar(arg, chain_id):
+        chain_id = int(chain_id)
+        if arg == 0:
+            chain_id = _calc_chain_idx(arg)
+            progress_bars[chain_id] = progress_bar(range(num_samples))
+            progress_bars[chain_id].update(0)
 
-    def _update_bar(arg):
-        progress_bars[0].update_bar(arg + 1)
+        progress_bars[chain_id].update_bar(arg + 1)
+        return chain_id
 
-    def _close_bar(arg):
-        del arg
-        progress_bars[0].on_iter_end()
+    def _close_bar(arg, chain_id):
+        progress_bars[int(chain_id)].on_iter_end()
 
-    def _update_progress_bar(iter_num):
+    def _update_progress_bar(iter_num, chain_id):
         "Updates progress bar of a JAX scan or loop"
-        _ = lax.cond(
-            iter_num == 0,
-            lambda _: io_callback(_define_bar, None, iter_num),
-            lambda _: None,
-            operand=None,
-        )
 
-        _ = lax.cond(
+        chain_id = lax.cond(
             # update every multiple of `print_rate` except at the end
             (iter_num % print_rate == 0) | (iter_num == (num_samples - 1)),
-            lambda _: io_callback(_update_bar, None, iter_num),
-            lambda _: None,
+            lambda _: io_callback(_update_bar, array(0), iter_num, chain_id),
+            lambda _: chain_id,
             operand=None,
         )
 
         _ = lax.cond(
             iter_num == num_samples - 1,
-            lambda _: io_callback(_close_bar, None, None),
+            lambda _: io_callback(_close_bar, None, iter_num + 1, chain_id),
             lambda _: None,
             operand=None,
         )
+        return chain_id
 
     def _progress_bar_scan(func):
         """Decorator that adds a progress bar to `body_fun` used in `lax.scan`.
@@ -77,8 +85,11 @@ def wrapper_progress_bar(carry, x):
                 iter_num, *_ = x
             else:
                 iter_num = x
-            _update_progress_bar(iter_num)
-            return func(carry, x)
+            subcarry, chain_id = carry
+            chain_id = _update_progress_bar(iter_num, chain_id)
+            subcarry, y = func(subcarry, x)
+
+            return (subcarry, chain_id), y
 
         return wrapper_progress_bar
 

blackjax/util.py

@@ -224,13 +224,19 @@ def one_step(average_and_state, xs, return_state):
 
     one_step = jax.jit(partial(one_step, return_state=return_state_history))
 
+    xs = (jnp.arange(num_steps), keys)
     if progress_bar:
         one_step = progress_bar_scan(num_steps)(one_step)
+        (((_, average), final_state), _), history = lax.scan(
+            one_step,
+            (((0, expectation(transform(initial_state))), initial_state), -1),
+            xs,
+        )
 
-    xs = (jnp.arange(num_steps), keys)
-    ((_, average), final_state), history = lax.scan(
-        one_step, ((0, expectation(transform(initial_state))), initial_state), xs
-    )
+    else:
+        ((_, average), final_state), history = lax.scan(
+            one_step, ((0, expectation(transform(initial_state))), initial_state), xs
+        )
 
     if not return_state_history:
         return average, transform(final_state)