We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Observation 'Bitcode' without going through a temporary file.
## 🚀 Feature

Have an observation which just returns the bytes of the bitcode, rather than the file. Going through a temporary file is a (tiny) bit annoying.

```
env.observation["Bitcode"] -> bytes
env.bitcode == env.observation["Bitcode"]
```
## Motivation

I'm passing bitcode to LLVM tools. They will accept bitcode on stdin and emit it to stdout. No need for a temporary file.

## Pitch

Don't use a file when a `bytes` will do? 

## Alternatives

Keep using a file.


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `compiler_gym/spaces/sequence.py`
Content:
```
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, Tuple
6 
7 from gym.spaces import Space
8 
9 from compiler_gym.spaces.scalar import Scalar
10 
11 
12 class Sequence(Space):
13     """A sequence of values. Each element of the sequence is of `dtype`. The
14     length of the sequence is bounded by `size_range`.
15 
16     Example:
17 
18     ::
19 
20         >>> space = Sequence(size_range=(0, None), dtype=str)
21         >>> space.contains("Hello, world!")
22         True
23 
24     ::
25 
26         >>> space = Sequence(size_range=(256, 256), dtype=bytes)
27         >>> space.contains("Hello, world!")
28         False
29 
30     :ivar size_range: A tuple indicating the `(lower, upper)` bounds for
31         sequence lengths. An upper bound of `None` means no upper bound. All
32         sequences must have a lower bound of length >= 0.
33     :ivar dtype: The data type for each element in a sequence.
34     :ivar opaque_data_format: An optional string describing an opaque data
35         format, e.g. a data structure that is serialized to a string/binary
36         array for transmission to the client. It is up to the client and service
37         to agree on how to decode observations using this value. For example,
38         an opaque_data_format of `string_json` could be used to indicate that
39         the observation is a string-serialized JSON value.
40     """
41 
42     def __init__(
43         self,
44         size_range: Tuple[int, Optional[int]] = (0, None),
45         dtype=bytes,
46         opaque_data_format: Optional[str] = None,
47         scalar_range: Optional[Scalar] = None,
48     ):
49         """Constructor.
50 
51         :param size_range: A tuple indicating the `(lower, upper)` bounds for
52             sequence lengths. An upper bound of `None` means no upper bound. All
53             sequences must have a lower bound of length >= 0.
54         :param dtype: The data type for each element in a sequence.
55         :param opaque_data_format: An optional string describing an opaque data
56             format, e.g. a data structure that is serialized to a string/binary
57             array for transmission to the client. It is up to the client and
58             service to agree on how to decode observations using this value. For
59             example, an opaque_data_format of `string_json` could be used to
60             indicate that the observation is a string-serialized JSON value.
61         :param scalar_range: If specified, this denotes the legal range of
62             each element in the sequence. This is enforced by
63             :meth:`contains() <compiler_gym.spaces.Sequence.contains>` checks.
64         """
65         self.size_range = size_range
66         self.dtype = dtype
67         self.opaque_data_format = opaque_data_format
68         self.scalar_range = scalar_range
69 
70     def __repr__(self) -> str:
71         upper_bound = "inf" if self.size_range[1] is None else self.size_range[1]
72         d = f" -> {self.opaque_data_format}" if self.opaque_data_format else ""
73         return (
74             f"{self.dtype.__name__}_list<>[{int(self.size_range[0])},{upper_bound}]){d}"
75         )
76 
77     def contains(self, x):
78         lower_bound = self.size_range[0]
79         upper_bound = float("inf") if self.size_range[1] is None else self.size_range[1]
80         if not (lower_bound <= len(x) <= upper_bound):
81             return False
82         for element in x:
83             if not isinstance(element, self.dtype):
84                 return False
85 
86         # Run the bounds check on every scalar element, if there is a scalar
87         # range specified.
88         if self.scalar_range:
89             return all(self.scalar_range.contains(s) for s in x)
90 
91         return True
92 
93     def sample(self):
94         """
95         .. warning::
96             The `Sequence` space cannot be sampled from.
97 
98         :raises NotImplementedError: Not supported.
99         """
100         raise NotImplementedError
101 
102     def __eq__(self, other):
103         if not isinstance(other, Sequence):
104             return False
105         return (
106             self.size_range == other.size_range
107             and self.dtype == other.dtype
108             and self.opaque_data_format == other.opaque_data_format
109         )
110
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/compiler_gym/spaces/sequence.py b/compiler_gym/spaces/sequence.py
--- a/compiler_gym/spaces/sequence.py
+++ b/compiler_gym/spaces/sequence.py
@@ -79,9 +79,18 @@
         upper_bound = float("inf") if self.size_range[1] is None else self.size_range[1]
         if not (lower_bound <= len(x) <= upper_bound):
             return False
-        for element in x:
-            if not isinstance(element, self.dtype):
+
+        # TODO(cummins): The dtype API is inconsistent. When dtype=str or
+        # dtype=bytes, we expect this to be the type of the entire sequence. But
+        # for dtype=int, we expect this to be the type of each element. We
+        # should distinguish these differences better.
+        if self.dtype in {str, bytes}:
+            if not isinstance(x, self.dtype):
                 return False
+        else:
+            for element in x:
+                if not isinstance(element, self.dtype):
+                    return False
 
         # Run the bounds check on every scalar element, if there is a scalar
         # range specified.

{"golden_diff": "diff --git a/compiler_gym/spaces/sequence.py b/compiler_gym/spaces/sequence.py\n--- a/compiler_gym/spaces/sequence.py\n+++ b/compiler_gym/spaces/sequence.py\n@@ -79,9 +79,18 @@\n         upper_bound = float(\"inf\") if self.size_range[1] is None else self.size_range[1]\n         if not (lower_bound <= len(x) <= upper_bound):\n             return False\n-        for element in x:\n-            if not isinstance(element, self.dtype):\n+\n+        # TODO(cummins): The dtype API is inconsistent. When dtype=str or\n+        # dtype=bytes, we expect this to be the type of the entire sequence. But\n+        # for dtype=int, we expect this to be the type of each element. We\n+        # should distinguish these differences better.\n+        if self.dtype in {str, bytes}:\n+            if not isinstance(x, self.dtype):\n                 return False\n+        else:\n+            for element in x:\n+                if not isinstance(element, self.dtype):\n+                    return False\n \n         # Run the bounds check on every scalar element, if there is a scalar\n         # range specified.\n", "issue": "Observation 'Bitcode' without going through a temporary file.\n## \ud83d\ude80 Feature\r\n\r\nHave an observation which just returns the bytes of the bitcode, rather than the file. Going through a temporary file is a (tiny) bit annoying.\r\n\r\n```\r\nenv.observation[\"Bitcode\"] -> bytes\r\nenv.bitcode == env.observation[\"Bitcode\"]\r\n```\r\n## Motivation\r\n\r\nI'm passing bitcode to LLVM tools. They will accept bitcode on stdin and emit it to stdout. No need for a temporary file.\r\n\r\n## Pitch\r\n\r\nDon't use a file when a `bytes` will do? \r\n\r\n## Alternatives\r\n\r\nKeep using a file.\r\n\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, Tuple\n\nfrom gym.spaces import Space\n\nfrom compiler_gym.spaces.scalar import Scalar\n\n\nclass Sequence(Space):\n    \"\"\"A sequence of values. Each element of the sequence is of `dtype`. The\n    length of the sequence is bounded by `size_range`.\n\n    Example:\n\n    ::\n\n        >>> space = Sequence(size_range=(0, None), dtype=str)\n        >>> space.contains(\"Hello, world!\")\n        True\n\n    ::\n\n        >>> space = Sequence(size_range=(256, 256), dtype=bytes)\n        >>> space.contains(\"Hello, world!\")\n        False\n\n    :ivar size_range: A tuple indicating the `(lower, upper)` bounds for\n        sequence lengths. An upper bound of `None` means no upper bound. All\n        sequences must have a lower bound of length >= 0.\n    :ivar dtype: The data type for each element in a sequence.\n    :ivar opaque_data_format: An optional string describing an opaque data\n        format, e.g. a data structure that is serialized to a string/binary\n        array for transmission to the client. It is up to the client and service\n        to agree on how to decode observations using this value. For example,\n        an opaque_data_format of `string_json` could be used to indicate that\n        the observation is a string-serialized JSON value.\n    \"\"\"\n\n    def __init__(\n        self,\n        size_range: Tuple[int, Optional[int]] = (0, None),\n        dtype=bytes,\n        opaque_data_format: Optional[str] = None,\n        scalar_range: Optional[Scalar] = None,\n    ):\n        \"\"\"Constructor.\n\n        :param size_range: A tuple indicating the `(lower, upper)` bounds for\n            sequence lengths. An upper bound of `None` means no upper bound. All\n            sequences must have a lower bound of length >= 0.\n        :param dtype: The data type for each element in a sequence.\n        :param opaque_data_format: An optional string describing an opaque data\n            format, e.g. a data structure that is serialized to a string/binary\n            array for transmission to the client. It is up to the client and\n            service to agree on how to decode observations using this value. For\n            example, an opaque_data_format of `string_json` could be used to\n            indicate that the observation is a string-serialized JSON value.\n        :param scalar_range: If specified, this denotes the legal range of\n            each element in the sequence. This is enforced by\n            :meth:`contains() <compiler_gym.spaces.Sequence.contains>` checks.\n        \"\"\"\n        self.size_range = size_range\n        self.dtype = dtype\n        self.opaque_data_format = opaque_data_format\n        self.scalar_range = scalar_range\n\n    def __repr__(self) -> str:\n        upper_bound = \"inf\" if self.size_range[1] is None else self.size_range[1]\n        d = f\" -> {self.opaque_data_format}\" if self.opaque_data_format else \"\"\n        return (\n            f\"{self.dtype.__name__}_list<>[{int(self.size_range[0])},{upper_bound}]){d}\"\n        )\n\n    def contains(self, x):\n        lower_bound = self.size_range[0]\n        upper_bound = float(\"inf\") if self.size_range[1] is None else self.size_range[1]\n        if not (lower_bound <= len(x) <= upper_bound):\n            return False\n        for element in x:\n            if not isinstance(element, self.dtype):\n                return False\n\n        # Run the bounds check on every scalar element, if there is a scalar\n        # range specified.\n        if self.scalar_range:\n            return all(self.scalar_range.contains(s) for s in x)\n\n        return True\n\n    def sample(self):\n        \"\"\"\n        .. warning::\n            The `Sequence` space cannot be sampled from.\n\n        :raises NotImplementedError: Not supported.\n        \"\"\"\n        raise NotImplementedError\n\n    def __eq__(self, other):\n        if not isinstance(other, Sequence):\n            return False\n        return (\n            self.size_range == other.size_range\n            and self.dtype == other.dtype\n            and self.opaque_data_format == other.opaque_data_format\n        )\n", "path": "compiler_gym/spaces/sequence.py"}], "after_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, Tuple\n\nfrom gym.spaces import Space\n\nfrom compiler_gym.spaces.scalar import Scalar\n\n\nclass Sequence(Space):\n    \"\"\"A sequence of values. Each element of the sequence is of `dtype`. The\n    length of the sequence is bounded by `size_range`.\n\n    Example:\n\n    ::\n\n        >>> space = Sequence(size_range=(0, None), dtype=str)\n        >>> space.contains(\"Hello, world!\")\n        True\n\n    ::\n\n        >>> space = Sequence(size_range=(256, 256), dtype=bytes)\n        >>> space.contains(\"Hello, world!\")\n        False\n\n    :ivar size_range: A tuple indicating the `(lower, upper)` bounds for\n        sequence lengths. An upper bound of `None` means no upper bound. All\n        sequences must have a lower bound of length >= 0.\n    :ivar dtype: The data type for each element in a sequence.\n    :ivar opaque_data_format: An optional string describing an opaque data\n        format, e.g. a data structure that is serialized to a string/binary\n        array for transmission to the client. It is up to the client and service\n        to agree on how to decode observations using this value. For example,\n        an opaque_data_format of `string_json` could be used to indicate that\n        the observation is a string-serialized JSON value.\n    \"\"\"\n\n    def __init__(\n        self,\n        size_range: Tuple[int, Optional[int]] = (0, None),\n        dtype=bytes,\n        opaque_data_format: Optional[str] = None,\n        scalar_range: Optional[Scalar] = None,\n    ):\n        \"\"\"Constructor.\n\n        :param size_range: A tuple indicating the `(lower, upper)` bounds for\n            sequence lengths. An upper bound of `None` means no upper bound. All\n            sequences must have a lower bound of length >= 0.\n        :param dtype: The data type for each element in a sequence.\n        :param opaque_data_format: An optional string describing an opaque data\n            format, e.g. a data structure that is serialized to a string/binary\n            array for transmission to the client. It is up to the client and\n            service to agree on how to decode observations using this value. For\n            example, an opaque_data_format of `string_json` could be used to\n            indicate that the observation is a string-serialized JSON value.\n        :param scalar_range: If specified, this denotes the legal range of\n            each element in the sequence. This is enforced by\n            :meth:`contains() <compiler_gym.spaces.Sequence.contains>` checks.\n        \"\"\"\n        self.size_range = size_range\n        self.dtype = dtype\n        self.opaque_data_format = opaque_data_format\n        self.scalar_range = scalar_range\n\n    def __repr__(self) -> str:\n        upper_bound = \"inf\" if self.size_range[1] is None else self.size_range[1]\n        d = f\" -> {self.opaque_data_format}\" if self.opaque_data_format else \"\"\n        return (\n            f\"{self.dtype.__name__}_list<>[{int(self.size_range[0])},{upper_bound}]){d}\"\n        )\n\n    def contains(self, x):\n        lower_bound = self.size_range[0]\n        upper_bound = float(\"inf\") if self.size_range[1] is None else self.size_range[1]\n        if not (lower_bound <= len(x) <= upper_bound):\n            return False\n\n        # TODO(cummins): The dtype API is inconsistent. When dtype=str or\n        # dtype=bytes, we expect this to be the type of the entire sequence. But\n        # for dtype=int, we expect this to be the type of each element. We\n        # should distinguish these differences better.\n        if self.dtype in {str, bytes}:\n            if not isinstance(x, self.dtype):\n                return False\n        else:\n            for element in x:\n                if not isinstance(element, self.dtype):\n                    return False\n\n        # Run the bounds check on every scalar element, if there is a scalar\n        # range specified.\n        if self.scalar_range:\n            return all(self.scalar_range.contains(s) for s in x)\n\n        return True\n\n    def sample(self):\n        \"\"\"\n        .. warning::\n            The `Sequence` space cannot be sampled from.\n\n        :raises NotImplementedError: Not supported.\n        \"\"\"\n        raise NotImplementedError\n\n    def __eq__(self, other):\n        if not isinstance(other, Sequence):\n            return False\n        return (\n            self.size_range == other.size_range\n            and self.dtype == other.dtype\n            and self.opaque_data_format == other.opaque_data_format\n        )\n", "path": "compiler_gym/spaces/sequence.py"}]}