Show pickling issues in notebook on windows

RELEASE-NOTES.md

@@ -1,10 +1,15 @@
 # Release Notes
 
 ## PyMC3 3.9.x (on deck)
+
+### Maintenance
+- Fix an error on Windows and Mac where error message from unpickling models did not show up in the notebook, or where sampling froze when a worker process crashed (see [#3991](https://github.com/pymc-devs/pymc3/pull/3991)).
+
 ### Documentation
 - Notebook on [multilevel modeling](https://docs.pymc.io/notebooks/multilevel_modeling.html) has been rewritten to showcase ArviZ and xarray usage for inference result analysis (see [#3963](https://github.com/pymc-devs/pymc3/pull/3963))
 
 ### New features
+- Introduce optional arguments to `pm.sample`: `mp_ctx` to control how the processes for parallel sampling are started, and `pickle_backend` to specify which library is used to pickle models in parallel sampling when the multiprocessing cnotext is not of type `fork`. (see [#3991](https://github.com/pymc-devs/pymc3/pull/3991))
 - Add sampler stats `process_time_diff`, `perf_counter_diff` and `perf_counter_start`, that record wall and CPU times for each NUTS and HMC sample (see [ #3986](https://github.com/pymc-devs/pymc3/pull/3986)).
 
 ## PyMC3 3.9.2 (24 June 2020)

pymc3/__init__.py

@@ -27,12 +27,6 @@
         handler = logging.StreamHandler()
         _log.addHandler(handler)
 
-# Set start method to forkserver for MacOS to enable multiprocessing
-# Closes issue https://github.com/pymc-devs/pymc3/issues/3849
-sys = platform.system()
-if sys == "Darwin":
-    new_context = mp.get_context("forkserver")
-
 
 def __set_compiler_flags():
     # Workarounds for Theano compiler problems on various platforms

pymc3/parallel_sampling.py

@@ -17,10 +17,11 @@
 import ctypes
 import time
 import logging
+import pickle
 from collections import namedtuple
 import traceback
+import platform
 from pymc3.exceptions import SamplingError
-import errno
 
 import numpy as np
 from fastprogress.fastprogress import progress_bar
@@ -30,37 +31,6 @@
 logger = logging.getLogger("pymc3")
 
 
-def _get_broken_pipe_exception():
-    import sys
-
-    if sys.platform == "win32":
-        return RuntimeError(
-            "The communication pipe between the main process "
-            "and its spawned children is broken.\n"
-            "In Windows OS, this usually means that the child "
-            "process raised an exception while it was being "
-            "spawned, before it was setup to communicate to "
-            "the main process.\n"
-            "The exceptions raised by the child process while "
-            "spawning cannot be caught or handled from the "
-            "main process, and when running from an IPython or "
-            "jupyter notebook interactive kernel, the child's "
-            "exception and traceback appears to be lost.\n"
-            "A known way to see the child's error, and try to "
-            "fix or handle it, is to run the problematic code "
-            "as a batch script from a system's Command Prompt. "
-            "The child's exception will be printed to the "
-            "Command Promt's stderr, and it should be visible "
-            "above this error and traceback.\n"
-            "Note that if running a jupyter notebook that was "
-            "invoked from a Command Prompt, the child's "
-            "exception should have been printed to the Command "
-            "Prompt on which the notebook is running."
-        )
-    else:
-        return None
-
-
 class ParallelSamplingError(Exception):
     def __init__(self, message, chain, warnings=None):
         super().__init__(message)
@@ -104,26 +74,65 @@ def rebuild_exc(exc, tb):
 # ('start',)
 
 
-class _Process(multiprocessing.Process):
+class _Process:
     """Seperate process for each chain.
     We communicate with the main process using a pipe,
     and send finished samples using shared memory.
     """
 
-    def __init__(self, name:str, msg_pipe, step_method, shared_point, draws:int, tune:int, seed):
-        super().__init__(daemon=True, name=name)
+    def __init__(
+        self,
+        name: str,
+        msg_pipe,
+        step_method,
+        step_method_is_pickled,
+        shared_point,
+        draws: int,
+        tune: int,
+        seed,
+        pickle_backend,
+    ):
         self._msg_pipe = msg_pipe
         self._step_method = step_method
+        self._step_method_is_pickled = step_method_is_pickled
         self._shared_point = shared_point
         self._seed = seed
         self._tt_seed = seed + 1
         self._draws = draws
         self._tune = tune
+        self._pickle_backend = pickle_backend
+
+    def _unpickle_step_method(self):
+        unpickle_error = (
+            "The model could not be unpickled. This is required for sampling "
+            "with more than one core and multiprocessing context spawn "
+            "or forkserver."
+        )
+        if self._step_method_is_pickled:
+            if self._pickle_backend == 'pickle':
+                try:
+                    self._step_method = pickle.loads(self._step_method)
+                except Exception:
+                    raise ValueError(unpickle_error)
+            elif self._pickle_backend == 'dill':
+                try:
+                    import dill
+                except ImportError:
+                    raise ValueError(
+                        "dill must be installed for pickle_backend='dill'."
+                    )
+                try:
+                    self._step_method = dill.loads(self._step_method)
+                except Exception:
+                    raise ValueError(unpickle_error)
+            else:
+                raise ValueError("Unknown pickle backend")
 
     def run(self):
         try:
             # We do not create this in __init__, as pickling this
             # would destroy the shared memory.
+            self._unpickle_step_method()
             self._point = self._make_numpy_refs()
             self._start_loop()
         except KeyboardInterrupt:
@@ -219,10 +228,25 @@ def _collect_warnings(self):
             return []
 
 
+def _run_process(*args):
+    _Process(*args).run()
+
+
 class ProcessAdapter:
     """Control a Chain process from the main thread."""
 
-    def __init__(self, draws:int, tune:int, step_method, chain:int, seed, start):
+    def __init__(
+        self,
+        draws: int,
+        tune: int,
+        step_method,
+        step_method_pickled,
+        chain: int,
+        seed,
+        start,
+        mp_ctx,
+        pickle_backend,
+    ):
         self.chain = chain
         process_name = "worker_chain_%s" % chain
         self._msg_pipe, remote_conn = multiprocessing.Pipe()
@@ -237,7 +261,7 @@ def __init__(self, draws:int, tune:int, step_method, chain:int, seed, start):
             if size != ctypes.c_size_t(size).value:
                 raise ValueError("Variable %s is too large" % name)
 
-            array = multiprocessing.sharedctypes.RawArray("c", size)
+            array = mp_ctx.RawArray("c", size)
             self._shared_point[name] = array
             array_np = np.frombuffer(array, dtype).reshape(shape)
             array_np[...] = start[name]
@@ -246,27 +270,31 @@ def __init__(self, draws:int, tune:int, step_method, chain:int, seed, start):
         self._readable = True
         self._num_samples = 0
 
-        self._process = _Process(
-            process_name,
-            remote_conn,
-            step_method,
-            self._shared_point,
-            draws,
-            tune,
-            seed,
+        if step_method_pickled is not None:
+            step_method_send = step_method_pickled
+        else:
+            step_method_send = step_method
+
+        self._process = mp_ctx.Process(
+            daemon=True,
+            name=process_name,
+            target=_run_process,
+            args=(
+                process_name,
+                remote_conn,
+                step_method_send,
+                step_method_pickled is not None,
+                self._shared_point,
+                draws,
+                tune,
+                seed,
+                pickle_backend,
+            )
         )
-        try:
-            self._process.start()
-        except IOError as e:
-            # Something may have gone wrong during the fork / spawn
-            if e.errno == errno.EPIPE:
-                exc = _get_broken_pipe_exception()
-                if exc is not None:
-                    # Sleep a little to give the child process time to flush
-                    # all its error message
-                    time.sleep(0.2)
-                    raise exc
-            raise
+        self._process.start()
+        # Close the remote pipe, so that we get notified if the other
+        # end is closed.
+        remote_conn.close()
 
     @property
     def shared_point_view(self):
@@ -277,15 +305,38 @@ def shared_point_view(self):
             raise RuntimeError()
         return self._point
 
+    def _send(self, msg, *args):
+        try:
+            self._msg_pipe.send((msg, *args))
+        except Exception:
+            # try to recive an error message
+            message = None
+            try:
+                message = self._msg_pipe.recv()
+            except Exception:
+                pass
+            if message is not None and message[0] == "error":
+                warns, old_error = message[1:]
+                if warns is not None:
+                    error = ParallelSamplingError(
+                        str(old_error),
+                        self.chain,
+                        warns
+                    )
+                else:
+                    error = RuntimeError("Chain %s failed." % self.chain)
+                raise error from old_error
+            raise
+
     def start(self):
-        self._msg_pipe.send(("start",))
+        self._send("start")
 
     def write_next(self):
         self._readable = False
-        self._msg_pipe.send(("write_next",))
+        self._send("write_next")
 
     def abort(self):
-        self._msg_pipe.send(("abort",))
+        self._send("abort")
 
     def join(self, timeout=None):
         self._process.join(timeout)
@@ -324,7 +375,7 @@ def terminate_all(processes, patience=2):
         for process in processes:
             try:
                 process.abort()
-            except EOFError:
+            except Exception:
                 pass
 
         start_time = time.time()
@@ -353,23 +404,52 @@ def terminate_all(processes, patience=2):
 class ParallelSampler:
     def __init__(
         self,
-        draws:int,
-        tune:int,
-        chains:int,
-        cores:int,
-        seeds:list,
-        start_points:list,
+        draws: int,
+        tune: int,
+        chains: int,
+        cores: int,
+        seeds: list,
+        start_points: list,
         step_method,
-        start_chain_num:int=0,
-        progressbar:bool=True,
+        start_chain_num: int = 0,
+        progressbar: bool = True,
+        mp_ctx=None,
+        pickle_backend: str = 'pickle',
     ):
 
         if any(len(arg) != chains for arg in [seeds, start_points]):
             raise ValueError("Number of seeds and start_points must be %s." % chains)
 
+        if mp_ctx is None or isinstance(mp_ctx, str):
+            # Closes issue https://github.com/pymc-devs/pymc3/issues/3849
+            if platform.system() == 'Darwin':
+                mp_ctx = "forkserver"
+            mp_ctx = multiprocessing.get_context(mp_ctx)
+
+        step_method_pickled = None
+        if mp_ctx.get_start_method() != 'fork':
+            if pickle_backend == 'pickle':
+                step_method_pickled = pickle.dumps(step_method, protocol=-1)
+            elif pickle_backend == 'dill':
+                try:
+                    import dill
+                except ImportError:
+                    raise ValueError(
+                        "dill must be installed for pickle_backend='dill'."
+                    )
+                step_method_pickled = dill.dumps(step_method, protocol=-1)
+
         self._samplers = [
             ProcessAdapter(
-                draws, tune, step_method, chain + start_chain_num, seed, start
+                draws,
+                tune,
+                step_method,
+                step_method_pickled,
+                chain + start_chain_num,
+                seed,
+                start,
+                mp_ctx,
+                pickle_backend
             )
             for chain, seed, start in zip(range(chains), seeds, start_points)
         ]