prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Logical Failure when combing TimeLimit Wrapper with IterateOverBenchmarks
  ## 🐛 Bug
  
  If an environment is first wrapper with TimeLimit before IterateOverBenchmarks, it will not return "done" as True. 
  
  ## To Reproduce
  
  Steps to reproduce the behavior:
  
  ```
  env = TimeLimit(env, step_limit) 
  env = CycleOverBenchmarks(env, benchmarks) 
  _, done, _, _ = env.reset()
  while not done:
      _, done, _, _ = env.step(0) 
  ```
  This will not finish. However, if the TimeLimit happens after the Cycle, it has normal behavior. 
  
  
  ## Additional context
  
  Assign it to me, I will fix it when I got time. 
  
  </issue>
  <code>
  [start of compiler_gym/wrappers/time_limit.py]
  1 # Copyright (c) Facebook, Inc. and its affiliates.
  2 #
  3 # This source code is licensed under the MIT license found in the
  4 # LICENSE file in the root directory of this source tree.
  5 from typing import Optional
  6 
  7 from compiler_gym.envs import CompilerEnv
  8 from compiler_gym.util.gym_type_hints import ActionType
  9 from compiler_gym.wrappers.core import CompilerEnvWrapper
  10 
  11 
  12 class TimeLimit(CompilerEnvWrapper):
  13     """A step-limited wrapper that is compatible with CompilerGym.
  14 
  15     Example usage:
  16 
  17         >>> env = TimeLimit(env, max_episode_steps=3)
  18         >>> env.reset()
  19         >>> _, _, done, _ = env.step(0)
  20         >>> _, _, done, _ = env.step(0)
  21         >>> _, _, done, _ = env.step(0)
  22         >>> done
  23         True
  24     """
  25 
  26     def __init__(self, env: CompilerEnv, max_episode_steps: Optional[int] = None):
  27         super().__init__(env=env)
  28         if max_episode_steps is None and self.env.spec is not None:
  29             max_episode_steps = env.spec.max_episode_steps
  30         if self.env.spec is not None:
  31             self.env.spec.max_episode_steps = max_episode_steps
  32         self._max_episode_steps = max_episode_steps
  33         self._elapsed_steps = None
  34 
  35     def step(self, action: ActionType, **kwargs):
  36         assert (
  37             self._elapsed_steps is not None
  38         ), "Cannot call env.step() before calling reset()"
  39         observation, reward, done, info = self.env.step(action, **kwargs)
  40         self._elapsed_steps += 1
  41         if self._elapsed_steps >= self._max_episode_steps:
  42             info["TimeLimit.truncated"] = not done
  43             done = True
  44         return observation, reward, done, info
  45 
  46     def reset(self, **kwargs):
  47         self._elapsed_steps = 0
  48         return self.env.reset(**kwargs)
  49 
  50     def fork(self) -> "TimeLimit":
  51         """Fork the wrapped environment.
  52 
  53         The time limit state of the forked environment is the same as the source
  54         state.
  55         """
  56         fkd = type(self)(env=self.env.fork(), max_episode_steps=self._max_episode_steps)
  57         fkd._elapsed_steps = self._elapsed_steps  # pylint: disable=protected-access
  58         return fkd
  59
  [end of compiler_gym/wrappers/time_limit.py]
  </code>
  
  I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
  <patch>
  diff --git a/file.py b/file.py
  --- a/file.py
  +++ b/file.py
  @@ -1,27 +1,35 @@
   def euclidean(a, b):
  -    while b:
  -        a, b = b, a % b
  -    return a
  +    if b == 0:
  +        return a
  +    return euclidean(b, a % b)
   
   
   def bresenham(x0, y0, x1, y1):
       points = []
       dx = abs(x1 - x0)
       dy = abs(y1 - y0)
  -    sx = 1 if x0 < x1 else -1
  -    sy = 1 if y0 < y1 else -1
  -    err = dx - dy
  +    x, y = x0, y0
  +    sx = -1 if x0 > x1 else 1
  +    sy = -1 if y0 > y1 else 1
   
  -    while True:
  -        points.append((x0, y0))
  -        if x0 == x1 and y0 == y1:
  -            break
  -        e2 = 2 * err
  -        if e2 > -dy:
  -            err -= dy
  -            x0 += sx
  -        if e2 < dx:
  -            err += dx
  -            y0 += sy
  +    if dx > dy:
  +        err = dx / 2.0
  +        while x != x1:
  +            points.append((x, y))
  +            err -= dy
  +            if err < 0:
  +                y += sy
  +                err += dx
  +            x += sx
  +    else:
  +        err = dy / 2.0
  +        while y != y1:
  +            points.append((x, y))
  +            err -= dx
  +            if err < 0:
  +                x += sx
  +                err += dy
  +            y += sy
  +
  +    points.append((x, y))
       return points
  
  </patch>
golden_diff: diff --git a/compiler_gym/wrappers/time_limit.py b/compiler_gym/wrappers/time_limit.py
  --- a/compiler_gym/wrappers/time_limit.py
  +++ b/compiler_gym/wrappers/time_limit.py
  @@ -2,7 +2,7 @@
   #
   # This source code is licensed under the MIT license found in the
   # LICENSE file in the root directory of this source tree.
  -from typing import Optional
  +from typing import Iterable, Optional
   
   from compiler_gym.envs import CompilerEnv
   from compiler_gym.util.gym_type_hints import ActionType
  @@ -32,12 +32,13 @@
           self._max_episode_steps = max_episode_steps
           self._elapsed_steps = None
   
  -    def step(self, action: ActionType, **kwargs):
  +    def multistep(self, actions: Iterable[ActionType], **kwargs):
  +        actions = list(actions)
           assert (
               self._elapsed_steps is not None
           ), "Cannot call env.step() before calling reset()"
  -        observation, reward, done, info = self.env.step(action, **kwargs)
  -        self._elapsed_steps += 1
  +        observation, reward, done, info = self.env.multistep(actions, **kwargs)
  +        self._elapsed_steps += len(actions)
           if self._elapsed_steps >= self._max_episode_steps:
               info["TimeLimit.truncated"] = not done
               done = True
  
verification_info: {"golden_diff": "diff --git a/compiler_gym/wrappers/time_limit.py b/compiler_gym/wrappers/time_limit.py\n--- a/compiler_gym/wrappers/time_limit.py\n+++ b/compiler_gym/wrappers/time_limit.py\n@@ -2,7 +2,7 @@\n #\n # This source code is licensed under the MIT license found in the\n # LICENSE file in the root directory of this source tree.\n-from typing import Optional\n+from typing import Iterable, Optional\n \n from compiler_gym.envs import CompilerEnv\n from compiler_gym.util.gym_type_hints import ActionType\n@@ -32,12 +32,13 @@\n         self._max_episode_steps = max_episode_steps\n         self._elapsed_steps = None\n \n-    def step(self, action: ActionType, **kwargs):\n+    def multistep(self, actions: Iterable[ActionType], **kwargs):\n+        actions = list(actions)\n         assert (\n             self._elapsed_steps is not None\n         ), \"Cannot call env.step() before calling reset()\"\n-        observation, reward, done, info = self.env.step(action, **kwargs)\n-        self._elapsed_steps += 1\n+        observation, reward, done, info = self.env.multistep(actions, **kwargs)\n+        self._elapsed_steps += len(actions)\n         if self._elapsed_steps >= self._max_episode_steps:\n             info[\"TimeLimit.truncated\"] = not done\n             done = True\n", "issue": "Logical Failure when combing TimeLimit Wrapper with IterateOverBenchmarks\n## \ud83d\udc1b Bug\r\n\r\nIf an environment is first wrapper with TimeLimit before IterateOverBenchmarks, it will not return \"done\" as True. \r\n\r\n## To Reproduce\r\n\r\nSteps to reproduce the behavior:\r\n\r\n```\r\nenv = TimeLimit(env, step_limit) \r\nenv = CycleOverBenchmarks(env, benchmarks) \r\n_, done, _, _ = env.reset()\r\nwhile not done:\r\n    _, done, _, _ = env.step(0) \r\n```\r\nThis will not finish. However, if the TimeLimit happens after the Cycle, it has normal behavior. \r\n\r\n\r\n## Additional context\r\n\r\nAssign it to me, I will fix it when I got time. \n", "before_files": [{"content": "# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\nfrom typing import Optional\n\nfrom compiler_gym.envs import CompilerEnv\nfrom compiler_gym.util.gym_type_hints import ActionType\nfrom compiler_gym.wrappers.core import CompilerEnvWrapper\n\n\nclass TimeLimit(CompilerEnvWrapper):\n    \"\"\"A step-limited wrapper that is compatible with CompilerGym.\n\n    Example usage:\n\n        >>> env = TimeLimit(env, max_episode_steps=3)\n        >>> env.reset()\n        >>> _, _, done, _ = env.step(0)\n        >>> _, _, done, _ = env.step(0)\n        >>> _, _, done, _ = env.step(0)\n        >>> done\n        True\n    \"\"\"\n\n    def __init__(self, env: CompilerEnv, max_episode_steps: Optional[int] = None):\n        super().__init__(env=env)\n        if max_episode_steps is None and self.env.spec is not None:\n            max_episode_steps = env.spec.max_episode_steps\n        if self.env.spec is not None:\n            self.env.spec.max_episode_steps = max_episode_steps\n        self._max_episode_steps = max_episode_steps\n        self._elapsed_steps = None\n\n    def step(self, action: ActionType, **kwargs):\n        assert (\n            self._elapsed_steps is not None\n        ), \"Cannot call env.step() before calling reset()\"\n        observation, reward, done, info = self.env.step(action, **kwargs)\n        self._elapsed_steps += 1\n        if self._elapsed_steps >= self._max_episode_steps:\n            info[\"TimeLimit.truncated\"] = not done\n            done = True\n        return observation, reward, done, info\n\n    def reset(self, **kwargs):\n        self._elapsed_steps = 0\n        return self.env.reset(**kwargs)\n\n    def fork(self) -> \"TimeLimit\":\n        \"\"\"Fork the wrapped environment.\n\n        The time limit state of the forked environment is the same as the source\n        state.\n        \"\"\"\n        fkd = type(self)(env=self.env.fork(), max_episode_steps=self._max_episode_steps)\n        fkd._elapsed_steps = self._elapsed_steps  # pylint: disable=protected-access\n        return fkd\n", "path": "compiler_gym/wrappers/time_limit.py"}]}