Rebase fixes for service pool PR.

Author: Chris Cummins

compiler_gym/envs/compiler_env.py

@@ -65,244 +65,6 @@ def observation_space_spec(self) -> ObservationSpaceSpec:
     def observation_space_spec(
         self, observation_space_spec: Optional[ObservationSpaceSpec]
     ):
-<<<<<<< HEAD
-=======
-        """Construct and initialize a CompilerGym environment.
-
-        In normal use you should use :code:`gym.make(...)` rather than calling
-        the constructor directly.
-
-        :param service: The hostname and port of a service that implements the
-            CompilerGym service interface, or the path of a binary file which
-            provides the CompilerGym service interface when executed. See
-            :doc:`/compiler_gym/service` for details.
-
-        :param rewards: The reward spaces that this environment supports.
-            Rewards are typically calculated based on observations generated by
-            the service. See :class:`Reward <compiler_gym.spaces.Reward>` for
-            details.
-
-        :param benchmark: The benchmark to use for this environment. Either a
-            URI string, or a :class:`Benchmark
-            <compiler_gym.datasets.Benchmark>` instance. If not provided, the
-            first benchmark as returned by
-            :code:`next(env.datasets.benchmarks())` will be used as the default.
-
-        :param observation_space: Compute and return observations at each
-            :func:`step()` from this space. Accepts a string name or an
-            :class:`ObservationSpaceSpec
-            <compiler_gym.views.ObservationSpaceSpec>`. If not provided,
-            :func:`step()` returns :code:`None` for the observation value. Can
-            be set later using :meth:`env.observation_space
-            <compiler_gym.envs.CompilerEnv.observation_space>`. For available
-            spaces, see :class:`env.observation.spaces
-            <compiler_gym.views.ObservationView>`.
-
-        :param reward_space: Compute and return reward at each :func:`step()`
-            from this space. Accepts a string name or a :class:`Reward
-            <compiler_gym.spaces.Reward>`. If not provided, :func:`step()`
-            returns :code:`None` for the reward value. Can be set later using
-            :meth:`env.reward_space
-            <compiler_gym.envs.CompilerEnv.reward_space>`. For available spaces,
-            see :class:`env.reward.spaces <compiler_gym.views.RewardView>`.
-
-        :param action_space: The name of the action space to use. If not
-            specified, the default action space for this compiler is used.
-
-        :param derived_observation_spaces: An optional list of arguments to be
-            passed to :meth:`env.observation.add_derived_space()
-            <compiler_gym.views.observation.Observation.add_derived_space>`.
-
-        :param connection_settings: The settings used to establish a connection
-            with the remote service.
-
-        :param service_connection: An existing compiler gym service connection
-            to use.
-
-        :param service_pool: A service pool to use for acquiring a service
-            connection. If not specified, the :meth:`global service pool
-            <compiler_gym.service.ServiceConnectionPool.get>` is used.
-
-        :raises FileNotFoundError: If service is a path to a file that is not
-            found.
-
-        :raises TimeoutError: If the compiler service fails to initialize within
-            the parameters provided in :code:`connection_settings`.
-        """
-        # NOTE(cummins): Logger argument deprecated and scheduled to be removed
-        # in release 0.2.3.
-        if logger:
-            warnings.warn(
-                "The `logger` argument is deprecated on CompilerEnv.__init__() "
-                "and will be removed in a future release. All CompilerEnv "
-                "instances share a logger named compiler_gym.envs.compiler_env",
-                DeprecationWarning,
-            )
-
-        self.metadata = {"render.modes": ["human", "ansi"]}
-
-        # A compiler service supports multiple simultaneous environments. This
-        # session ID is used to identify this environment.
-        self._session_id: Optional[int] = None
-
-        self._service_endpoint: Union[str, Path] = service
-        self._connection_settings = connection_settings or ConnectionOpts()
-
-        if service_connection is None:
-            self._service_pool: Optional[ServiceConnectionPool] = (
-                ServiceConnectionPool.get() if service_pool is None else service_pool
-            )
-            self.service = self._service_pool.acquire(
-                endpoint=self._service_endpoint,
-                opts=self._connection_settings,
-            )
-        else:
-            self._service_pool: Optional[ServiceConnectionPool] = service_pool
-            self.service = service_connection
-
-        self.datasets = Datasets(datasets or [])
-
-        self.action_space_name = action_space
-
-        # If no reward space is specified, generate some from numeric observation spaces
-        rewards = rewards or [
-            DefaultRewardFromObservation(obs.name)
-            for obs in self.service.observation_spaces
-            if obs.default_observation.WhichOneof("value")
-            and isinstance(
-                getattr(
-                    obs.default_observation, obs.default_observation.WhichOneof("value")
-                ),
-                numbers.Number,
-            )
-        ]
-
-        # The benchmark that is currently being used, and the benchmark that
-        # will be used on the next call to reset(). These are equal except in
-        # the gap between the user setting the env.benchmark property while in
-        # an episode and the next call to env.reset().
-        self._benchmark_in_use: Optional[Benchmark] = None
-        self._benchmark_in_use_proto: BenchmarkProto = BenchmarkProto()
-        self._next_benchmark: Optional[Benchmark] = None
-        # Normally when the benchmark is changed the updated value is not
-        # reflected until the next call to reset(). We make an exception for the
-        # constructor-time benchmark as otherwise the behavior of the benchmark
-        # property is counter-intuitive:
-        #
-        #     >>> env = gym.make("example-v0", benchmark="foo")
-        #     >>> env.benchmark
-        #     None
-        #     >>> env.reset()
-        #     >>> env.benchmark
-        #     "foo"
-        #
-        # By forcing the _benchmark_in_use URI at constructor time, the first
-        # env.benchmark above returns the benchmark as expected.
-        try:
-            self.benchmark = benchmark or next(self.datasets.benchmarks())
-            self._benchmark_in_use = self._next_benchmark
-        except StopIteration:
-            # StopIteration raised on next(self.datasets.benchmarks()) if there
-            # are no benchmarks available. This is to allow CompilerEnv to be
-            # used without any datasets by setting a benchmark before/during the
-            # first reset() call.
-            pass
-
-        # Process the available action, observation, and reward spaces.
-        self.action_spaces = [
-            proto_to_action_space(space) for space in self.service.action_spaces
-        ]
-
-        self.observation = self._observation_view_type(
-            raw_step=self.raw_step,
-            spaces=self.service.observation_spaces,
-        )
-        self.reward = self._reward_view_type(rewards, self.observation)
-
-        # Register any derived observation spaces now so that the observation
-        # space can be set below.
-        for derived_observation_space in derived_observation_spaces or []:
-            self.observation.add_derived_space_internal(**derived_observation_space)
-
-        # Lazily evaluated version strings.
-        self._versions: Optional[GetVersionReply] = None
-
-        self.action_space: Optional[Space] = None
-        self.observation_space: Optional[Space] = None
-
-        # Mutable state initialized in reset().
-        self.reward_range: Tuple[float, float] = (-np.inf, np.inf)
-        self.episode_reward: Optional[float] = None
-        self.episode_start_time: float = time()
-        self.actions: List[ActionType] = []
-
-        # Initialize the default observation/reward spaces.
-        self.observation_space_spec: Optional[ObservationSpaceSpec] = None
-        self.reward_space_spec: Optional[Reward] = None
-        self.observation_space = observation_space
-        self.reward_space = reward_space
-
-    @property
-    @deprecated(
-        version="0.2.1",
-        reason=(
-            "The `CompilerEnv.logger` attribute is deprecated. All CompilerEnv "
-            "instances share a logger named compiler_gym.envs.compiler_env"
-        ),
-    )
-    def logger(self):
-        return _logger
-
-    @property
-    def versions(self) -> GetVersionReply:
-        """Get the version numbers from the compiler service."""
-        if self._versions is None:
-            self._versions = self.service(
-                self.service.stub.GetVersion, GetVersionRequest()
-            )
-        return self._versions
-
-    @property
-    def version(self) -> str:
-        """The version string of the compiler service."""
-        return self.versions.service_version
-
-    @property
-    def compiler_version(self) -> str:
-        """The version string of the underlying compiler that this service supports."""
-        return self.versions.compiler_version
-
-    def commandline(self) -> str:
-        """Interface for :class:`CompilerEnv <compiler_gym.envs.CompilerEnv>`
-        subclasses to provide an equivalent commandline invocation to the
-        current environment state.
-
-        See also :meth:`commandline_to_actions()
-        <compiler_gym.envs.CompilerEnv.commandline_to_actions>`.
-
-        Calling this method on a :class:`CompilerEnv
-        <compiler_gym.envs.CompilerEnv>` instance raises
-        :code:`NotImplementedError`.
-
-        :return: A string commandline invocation.
-        """
-        raise NotImplementedError("abstract method")
-
-    def commandline_to_actions(self, commandline: str) -> List[ActionType]:
-        """Interface for :class:`CompilerEnv <compiler_gym.envs.CompilerEnv>`
-        subclasses to convert from a commandline invocation to a sequence of
-        actions.
-
-        See also :meth:`commandline()
-        <compiler_gym.envs.CompilerEnv.commandline>`.
-
-        Calling this method on a :class:`CompilerEnv
-        <compiler_gym.envs.CompilerEnv>` instance raises
-        :code:`NotImplementedError`.
-
-        :return: A list of actions.
-        """
->>>>>>> 4a874cee (Fix typo in docstring.)
         raise NotImplementedError("abstract method")
 
     @property

compiler_gym/service/BUILD

@@ -12,6 +12,9 @@ py_library(
     deps = [
         ":compilation_session",
         ":connection",
+        # TODO(github.com/facebookresearch/CompilerGym/pull/633):
+        # add this after circular dependencies are resolved
+        # ":client_service_compiler_env",
         ":connection_pool",
         "//compiler_gym/service/proto",
     ],
@@ -72,5 +75,5 @@ py_library(
     visibility = ["//visibility:public"],
     deps = [
         ":connection",
-    ]
-)
+    ],
+)