prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  run_wrapper() got an unexpected keyword argument 'pure'
  While running a fitting on a classifier (*output[0]* with data *output[1]* to *output[4]*), I get the following error; I think it's packages issue;
  
     > output[0].fit(output[1], output[2], output[3], output[4])
     > File "/usr/local/lib/python3.8/dist-packages/autosklearn/estimators.py", line 1045, in fit
       super().fit(
     > File "/usr/local/lib/python3.8/dist-packages/autosklearn/estimators.py", line 375, in fit
       self.automl_.fit(load_models=self.load_models, **kwargs)
     > File "/usr/local/lib/python3.8/dist-packages/autosklearn/automl.py", line 2056, in fit
       return super().fit(
     > File "/usr/local/lib/python3.8/dist-packages/autosklearn/automl.py", line 931, in fit
       _proc_smac.run_smbo()
     > File "/usr/local/lib/python3.8/dist-packages/autosklearn/smbo.py", line 498, in run_smbo
       smac.optimize()
     > File "/usr/local/lib/python3.8/dist-packages/smac/facade/smac_ac_facade.py", line 720, in optimize
       incumbent = self.solver.run()
     > File "/usr/local/lib/python3.8/dist-packages/smac/optimizer/smbo.py", line 287, in run
       self.tae_runner.submit_run(run_info=run_info)
     > File "/usr/local/lib/python3.8/dist-packages/smac/tae/dask_runner.py", line 166, in submit_run
       self.client.submit(
     > File "/usr/local/lib/python3.8/dist-packages/autosklearn/util/single_thread_client.py", line 59, in submit
       return DummyFuture(func(*args, **kwargs))
   > **TypeError: run_wrapper() got an unexpected keyword argument 'pure'**
  
  It seems like it's an error with Dask. Here are the installed packages on ubuntu 18.04
  
  pandas==1.3.0
  scikit-learn==0.24
  dask==2021.12.0
  auto-sklearn==0.14.5    #AutoML
  tensorflow==2.8.0
  
  I've tried all versions of dask from 2021.12.0 to 2022.02.0 (Current) and nothing seems to work. Downgrading to auto-sklearn 0.14.4 and lower didn't solve the problem.
  
  </issue>
  <code>
  [start of autosklearn/util/single_thread_client.py]
  1 import typing
  2 from pathlib import Path
  3 
  4 import dask.distributed
  5 
  6 
  7 class DummyFuture(dask.distributed.Future):
  8     """
  9     A class that mimics a distributed Future, the outcome of
  10     performing submit on a distributed client.
  11     """
  12     def __init__(self, result: typing.Any) -> None:
  13         self._result = result  # type: typing.Any
  14 
  15     def result(self, timeout: typing.Optional[int] = None) -> typing.Any:
  16         return self._result
  17 
  18     def cancel(self) -> None:
  19         pass
  20 
  21     def done(self) -> bool:
  22         return True
  23 
  24     def __repr__(self) -> str:
  25         return "DummyFuture: {}".format(self._result)
  26 
  27     def __del__(self) -> None:
  28         pass
  29 
  30 
  31 class SingleThreadedClient(dask.distributed.Client):
  32     """
  33     A class to Mock the Distributed Client class, in case
  34     Auto-Sklearn is meant to run in the current Thread.
  35     """
  36     def __init__(self) -> None:
  37 
  38         # Raise a not implemented error if using a method from Client
  39         implemented_methods = ['submit', 'close', 'shutdown', 'write_scheduler_file',
  40                                '_get_scheduler_info', 'nthreads']
  41         method_list = [func for func in dir(dask.distributed.Client) if callable(
  42             getattr(dask.distributed.Client, func)) and not func.startswith('__')]
  43         for method in method_list:
  44             if method in implemented_methods:
  45                 continue
  46             setattr(self, method, self._unsupported_method)
  47         pass
  48 
  49     def _unsupported_method(self) -> None:
  50         raise NotImplementedError()
  51 
  52     def submit(
  53         self,
  54         func: typing.Callable,
  55         *args: typing.List,
  56         priority: int = 0,
  57         **kwargs: typing.Dict,
  58     ) -> typing.Any:
  59         return DummyFuture(func(*args, **kwargs))
  60 
  61     def close(self) -> None:
  62         pass
  63 
  64     def shutdown(self) -> None:
  65         pass
  66 
  67     def write_scheduler_file(self, scheduler_file: str) -> None:
  68         Path(scheduler_file).touch()
  69         return
  70 
  71     def _get_scheduler_info(self) -> typing.Dict:
  72         return {
  73             'workers': ['127.0.0.1'],
  74             'type': 'Scheduler',
  75         }
  76 
  77     def nthreads(self) -> typing.Dict:
  78         return {
  79             '127.0.0.1': 1,
  80         }
  81 
  82     def __repr__(self) -> str:
  83         return 'SingleThreadedClient()'
  84 
  85     def __del__(self) -> None:
  86         pass
  87
  [end of autosklearn/util/single_thread_client.py]
  [start of autosklearn/__version__.py]
  1 """Version information."""
  2 
  3 # The following line *must* be the last in the module, exactly as formatted:
  4 __version__ = "0.14.4"
  5
  [end of autosklearn/__version__.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/autosklearn/__version__.py b/autosklearn/__version__.py
  --- a/autosklearn/__version__.py
  +++ b/autosklearn/__version__.py
  @@ -1,4 +1,4 @@
   """Version information."""
   
   # The following line *must* be the last in the module, exactly as formatted:
  -__version__ = "0.14.4"
  +__version__ = "0.14.6"
  diff --git a/autosklearn/util/single_thread_client.py b/autosklearn/util/single_thread_client.py
  --- a/autosklearn/util/single_thread_client.py
  +++ b/autosklearn/util/single_thread_client.py
  @@ -1,5 +1,6 @@
   import typing
   from pathlib import Path
  +from typing import Any
   
   import dask.distributed
   
  @@ -9,6 +10,7 @@
       A class that mimics a distributed Future, the outcome of
       performing submit on a distributed client.
       """
  +
       def __init__(self, result: typing.Any) -> None:
           self._result = result  # type: typing.Any
   
  @@ -33,13 +35,24 @@
       A class to Mock the Distributed Client class, in case
       Auto-Sklearn is meant to run in the current Thread.
       """
  +
       def __init__(self) -> None:
   
           # Raise a not implemented error if using a method from Client
  -        implemented_methods = ['submit', 'close', 'shutdown', 'write_scheduler_file',
  -                               '_get_scheduler_info', 'nthreads']
  -        method_list = [func for func in dir(dask.distributed.Client) if callable(
  -            getattr(dask.distributed.Client, func)) and not func.startswith('__')]
  +        implemented_methods = [
  +            "submit",
  +            "close",
  +            "shutdown",
  +            "write_scheduler_file",
  +            "_get_scheduler_info",
  +            "nthreads",
  +        ]
  +        method_list = [
  +            func
  +            for func in dir(dask.distributed.Client)
  +            if callable(getattr(dask.distributed.Client, func))
  +            and not func.startswith("__")
  +        ]
           for method in method_list:
               if method in implemented_methods:
                   continue
  @@ -54,8 +67,24 @@
           func: typing.Callable,
           *args: typing.List,
           priority: int = 0,
  -        **kwargs: typing.Dict,
  +        key: Any = None,
  +        workers: Any = None,
  +        resources: Any = None,
  +        retries: Any = None,
  +        fifo_timeout: Any = "100 ms",
  +        allow_other_workers: Any = False,
  +        actor: Any = False,
  +        actors: Any = False,
  +        pure: Any = None,
  +        **kwargs: Any,
       ) -> typing.Any:
  +        """
  +        Note
  +        ----
  +        The keyword arguments caught in `dask.distributed.Client` need to
  +        be specified here so they don't get passed in as ``**kwargs`` to the
  +        ``func``.
  +        """
           return DummyFuture(func(*args, **kwargs))
   
       def close(self) -> None:
  @@ -70,17 +99,17 @@
   
       def _get_scheduler_info(self) -> typing.Dict:
           return {
  -            'workers': ['127.0.0.1'],
  -            'type': 'Scheduler',
  +            "workers": ["127.0.0.1"],
  +            "type": "Scheduler",
           }
   
       def nthreads(self) -> typing.Dict:
           return {
  -            '127.0.0.1': 1,
  +            "127.0.0.1": 1,
           }
   
       def __repr__(self) -> str:
  -        return 'SingleThreadedClient()'
  +        return "SingleThreadedClient()"
   
       def __del__(self) -> None:
           pass
  
verification_info: {"golden_diff": "diff --git a/autosklearn/__version__.py b/autosklearn/__version__.py\n--- a/autosklearn/__version__.py\n+++ b/autosklearn/__version__.py\n@@ -1,4 +1,4 @@\n \"\"\"Version information.\"\"\"\n \n # The following line *must* be the last in the module, exactly as formatted:\n-__version__ = \"0.14.4\"\n+__version__ = \"0.14.6\"\ndiff --git a/autosklearn/util/single_thread_client.py b/autosklearn/util/single_thread_client.py\n--- a/autosklearn/util/single_thread_client.py\n+++ b/autosklearn/util/single_thread_client.py\n@@ -1,5 +1,6 @@\n import typing\n from pathlib import Path\n+from typing import Any\n \n import dask.distributed\n \n@@ -9,6 +10,7 @@\n     A class that mimics a distributed Future, the outcome of\n     performing submit on a distributed client.\n     \"\"\"\n+\n     def __init__(self, result: typing.Any) -> None:\n         self._result = result  # type: typing.Any\n \n@@ -33,13 +35,24 @@\n     A class to Mock the Distributed Client class, in case\n     Auto-Sklearn is meant to run in the current Thread.\n     \"\"\"\n+\n     def __init__(self) -> None:\n \n         # Raise a not implemented error if using a method from Client\n-        implemented_methods = ['submit', 'close', 'shutdown', 'write_scheduler_file',\n-                               '_get_scheduler_info', 'nthreads']\n-        method_list = [func for func in dir(dask.distributed.Client) if callable(\n-            getattr(dask.distributed.Client, func)) and not func.startswith('__')]\n+        implemented_methods = [\n+            \"submit\",\n+            \"close\",\n+            \"shutdown\",\n+            \"write_scheduler_file\",\n+            \"_get_scheduler_info\",\n+            \"nthreads\",\n+        ]\n+        method_list = [\n+            func\n+            for func in dir(dask.distributed.Client)\n+            if callable(getattr(dask.distributed.Client, func))\n+            and not func.startswith(\"__\")\n+        ]\n         for method in method_list:\n             if method in implemented_methods:\n                 continue\n@@ -54,8 +67,24 @@\n         func: typing.Callable,\n         *args: typing.List,\n         priority: int = 0,\n-        **kwargs: typing.Dict,\n+        key: Any = None,\n+        workers: Any = None,\n+        resources: Any = None,\n+        retries: Any = None,\n+        fifo_timeout: Any = \"100 ms\",\n+        allow_other_workers: Any = False,\n+        actor: Any = False,\n+        actors: Any = False,\n+        pure: Any = None,\n+        **kwargs: Any,\n     ) -> typing.Any:\n+        \"\"\"\n+        Note\n+        ----\n+        The keyword arguments caught in `dask.distributed.Client` need to\n+        be specified here so they don't get passed in as ``**kwargs`` to the\n+        ``func``.\n+        \"\"\"\n         return DummyFuture(func(*args, **kwargs))\n \n     def close(self) -> None:\n@@ -70,17 +99,17 @@\n \n     def _get_scheduler_info(self) -> typing.Dict:\n         return {\n-            'workers': ['127.0.0.1'],\n-            'type': 'Scheduler',\n+            \"workers\": [\"127.0.0.1\"],\n+            \"type\": \"Scheduler\",\n         }\n \n     def nthreads(self) -> typing.Dict:\n         return {\n-            '127.0.0.1': 1,\n+            \"127.0.0.1\": 1,\n         }\n \n     def __repr__(self) -> str:\n-        return 'SingleThreadedClient()'\n+        return \"SingleThreadedClient()\"\n \n     def __del__(self) -> None:\n         pass\n", "issue": "run_wrapper() got an unexpected keyword argument 'pure'\nWhile running a fitting on a classifier (*output[0]* with data *output[1]* to *output[4]*), I get the following error; I think it's packages issue;\r\n\r\n   > output[0].fit(output[1], output[2], output[3], output[4])\r\n   > File \"/usr/local/lib/python3.8/dist-packages/autosklearn/estimators.py\", line 1045, in fit\r\n     super().fit(\r\n   > File \"/usr/local/lib/python3.8/dist-packages/autosklearn/estimators.py\", line 375, in fit\r\n     self.automl_.fit(load_models=self.load_models, **kwargs)\r\n   > File \"/usr/local/lib/python3.8/dist-packages/autosklearn/automl.py\", line 2056, in fit\r\n     return super().fit(\r\n   > File \"/usr/local/lib/python3.8/dist-packages/autosklearn/automl.py\", line 931, in fit\r\n     _proc_smac.run_smbo()\r\n   > File \"/usr/local/lib/python3.8/dist-packages/autosklearn/smbo.py\", line 498, in run_smbo\r\n     smac.optimize()\r\n   > File \"/usr/local/lib/python3.8/dist-packages/smac/facade/smac_ac_facade.py\", line 720, in optimize\r\n     incumbent = self.solver.run()\r\n   > File \"/usr/local/lib/python3.8/dist-packages/smac/optimizer/smbo.py\", line 287, in run\r\n     self.tae_runner.submit_run(run_info=run_info)\r\n   > File \"/usr/local/lib/python3.8/dist-packages/smac/tae/dask_runner.py\", line 166, in submit_run\r\n     self.client.submit(\r\n   > File \"/usr/local/lib/python3.8/dist-packages/autosklearn/util/single_thread_client.py\", line 59, in submit\r\n     return DummyFuture(func(*args, **kwargs))\r\n > **TypeError: run_wrapper() got an unexpected keyword argument 'pure'**\r\n\r\nIt seems like it's an error with Dask. Here are the installed packages on ubuntu 18.04\r\n\r\npandas==1.3.0\r\nscikit-learn==0.24\r\ndask==2021.12.0\r\nauto-sklearn==0.14.5    #AutoML\r\ntensorflow==2.8.0\r\n\r\nI've tried all versions of dask from 2021.12.0 to 2022.02.0 (Current) and nothing seems to work. Downgrading to auto-sklearn 0.14.4 and lower didn't solve the problem.\n", "before_files": [{"content": "import typing\nfrom pathlib import Path\n\nimport dask.distributed\n\n\nclass DummyFuture(dask.distributed.Future):\n    \"\"\"\n    A class that mimics a distributed Future, the outcome of\n    performing submit on a distributed client.\n    \"\"\"\n    def __init__(self, result: typing.Any) -> None:\n        self._result = result  # type: typing.Any\n\n    def result(self, timeout: typing.Optional[int] = None) -> typing.Any:\n        return self._result\n\n    def cancel(self) -> None:\n        pass\n\n    def done(self) -> bool:\n        return True\n\n    def __repr__(self) -> str:\n        return \"DummyFuture: {}\".format(self._result)\n\n    def __del__(self) -> None:\n        pass\n\n\nclass SingleThreadedClient(dask.distributed.Client):\n    \"\"\"\n    A class to Mock the Distributed Client class, in case\n    Auto-Sklearn is meant to run in the current Thread.\n    \"\"\"\n    def __init__(self) -> None:\n\n        # Raise a not implemented error if using a method from Client\n        implemented_methods = ['submit', 'close', 'shutdown', 'write_scheduler_file',\n                               '_get_scheduler_info', 'nthreads']\n        method_list = [func for func in dir(dask.distributed.Client) if callable(\n            getattr(dask.distributed.Client, func)) and not func.startswith('__')]\n        for method in method_list:\n            if method in implemented_methods:\n                continue\n            setattr(self, method, self._unsupported_method)\n        pass\n\n    def _unsupported_method(self) -> None:\n        raise NotImplementedError()\n\n    def submit(\n        self,\n        func: typing.Callable,\n        *args: typing.List,\n        priority: int = 0,\n        **kwargs: typing.Dict,\n    ) -> typing.Any:\n        return DummyFuture(func(*args, **kwargs))\n\n    def close(self) -> None:\n        pass\n\n    def shutdown(self) -> None:\n        pass\n\n    def write_scheduler_file(self, scheduler_file: str) -> None:\n        Path(scheduler_file).touch()\n        return\n\n    def _get_scheduler_info(self) -> typing.Dict:\n        return {\n            'workers': ['127.0.0.1'],\n            'type': 'Scheduler',\n        }\n\n    def nthreads(self) -> typing.Dict:\n        return {\n            '127.0.0.1': 1,\n        }\n\n    def __repr__(self) -> str:\n        return 'SingleThreadedClient()'\n\n    def __del__(self) -> None:\n        pass\n", "path": "autosklearn/util/single_thread_client.py"}, {"content": "\"\"\"Version information.\"\"\"\n\n# The following line *must* be the last in the module, exactly as formatted:\n__version__ = \"0.14.4\"\n", "path": "autosklearn/__version__.py"}]}