prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  PyTorch dependency is lacking version constraint
  ## 🐛 Bug description
  
  <!-- A clear and concise description of what the bug is. -->
  PyTorch is a dependency of Ignite and, thus, is specified in `setup.py`
  
  https://github.com/pytorch/ignite/blob/4b311cc82fe45b3082661125cd7ee54007283fb0/setup.py#L24-L26
  
  and `conda.recipe/meta.yaml`:
  
  https://github.com/pytorch/ignite/blob/4b311cc82fe45b3082661125cd7ee54007283fb0/conda.recipe/meta.yaml#L15-L23
  
  The PyTorch dependency is lacking a version constraint which may work fine right now, but there is no guarantee that Ignite will be compatible with any future major PyTorch release (e.g. PyTorch v2.x).
  
  I suggest to constrain the PyTorch version that Ignite is compatible with, e.g. `>=1.0,<2` or `<2` if any `0.x` and `1.x` version works. If PyTorch has a new major release, even previous Ignite versions can become compatible with the new major PyTorch release (especially if no changes to the code are necessary) by making new bug fix releases with relaxed version constraints to include the new PyTorch version.
  
  In my opinion, it is highly preferable to be conservative about dependency version constraints through a [compatible release constraint](https://www.python.org/dev/peps/pep-0440/#compatible-release) in case the dependency conforms with semantic versioning. It is impossible to guarantee compatibility with a future major release of a dependency as its API can change arbitrarily.
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `setup.py`
  Content:
  ```
  1 import os
  2 import io
  3 import re
  4 from setuptools import setup, find_packages
  5 
  6 
  7 def read(*names, **kwargs):
  8     with io.open(os.path.join(os.path.dirname(__file__), *names), encoding=kwargs.get("encoding", "utf8")) as fp:
  9         return fp.read()
  10 
  11 
  12 def find_version(*file_paths):
  13     version_file = read(*file_paths)
  14     version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", version_file, re.M)
  15     if version_match:
  16         return version_match.group(1)
  17     raise RuntimeError("Unable to find version string.")
  18 
  19 
  20 readme = read("README.md")
  21 
  22 VERSION = find_version("ignite", "__init__.py")
  23 
  24 requirements = [
  25     "torch",
  26 ]
  27 
  28 setup(
  29     # Metadata
  30     name="pytorch-ignite",
  31     version=VERSION,
  32     author="PyTorch Core Team",
  33     author_email="soumith@pytorch.org",
  34     url="https://github.com/pytorch/ignite",
  35     description="A lightweight library to help with training neural networks in PyTorch.",
  36     long_description_content_type="text/markdown",
  37     long_description=readme,
  38     license="BSD",
  39     # Package info
  40     packages=find_packages(exclude=("tests", "tests.*",)),
  41     zip_safe=True,
  42     install_requires=requirements,
  43 )
  44
  ```
  --- 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()
  
  ```
  
golden_diff: diff --git a/setup.py b/setup.py
  --- a/setup.py
  +++ b/setup.py
  @@ -22,7 +22,7 @@
   VERSION = find_version("ignite", "__init__.py")
   
   requirements = [
  -    "torch",
  +    "torch>=1.0,<2",
   ]
   
   setup(
  
verification_info: {"golden_diff": "diff --git a/setup.py b/setup.py\n--- a/setup.py\n+++ b/setup.py\n@@ -22,7 +22,7 @@\n VERSION = find_version(\"ignite\", \"__init__.py\")\n \n requirements = [\n-    \"torch\",\n+    \"torch>=1.0,<2\",\n ]\n \n setup(\n", "issue": "PyTorch dependency is lacking version constraint\n## \ud83d\udc1b Bug description\r\n\r\n<!-- A clear and concise description of what the bug is. -->\r\nPyTorch is a dependency of Ignite and, thus, is specified in `setup.py`\r\n\r\nhttps://github.com/pytorch/ignite/blob/4b311cc82fe45b3082661125cd7ee54007283fb0/setup.py#L24-L26\r\n\r\nand `conda.recipe/meta.yaml`:\r\n\r\nhttps://github.com/pytorch/ignite/blob/4b311cc82fe45b3082661125cd7ee54007283fb0/conda.recipe/meta.yaml#L15-L23\r\n\r\nThe PyTorch dependency is lacking a version constraint which may work fine right now, but there is no guarantee that Ignite will be compatible with any future major PyTorch release (e.g. PyTorch v2.x).\r\n\r\nI suggest to constrain the PyTorch version that Ignite is compatible with, e.g. `>=1.0,<2` or `<2` if any `0.x` and `1.x` version works. If PyTorch has a new major release, even previous Ignite versions can become compatible with the new major PyTorch release (especially if no changes to the code are necessary) by making new bug fix releases with relaxed version constraints to include the new PyTorch version.\r\n\r\nIn my opinion, it is highly preferable to be conservative about dependency version constraints through a [compatible release constraint](https://www.python.org/dev/peps/pep-0440/#compatible-release) in case the dependency conforms with semantic versioning. It is impossible to guarantee compatibility with a future major release of a dependency as its API can change arbitrarily.\n", "before_files": [{"content": "import os\nimport io\nimport re\nfrom setuptools import setup, find_packages\n\n\ndef read(*names, **kwargs):\n    with io.open(os.path.join(os.path.dirname(__file__), *names), encoding=kwargs.get(\"encoding\", \"utf8\")) as fp:\n        return fp.read()\n\n\ndef find_version(*file_paths):\n    version_file = read(*file_paths)\n    version_match = re.search(r\"^__version__ = ['\\\"]([^'\\\"]*)['\\\"]\", version_file, re.M)\n    if version_match:\n        return version_match.group(1)\n    raise RuntimeError(\"Unable to find version string.\")\n\n\nreadme = read(\"README.md\")\n\nVERSION = find_version(\"ignite\", \"__init__.py\")\n\nrequirements = [\n    \"torch\",\n]\n\nsetup(\n    # Metadata\n    name=\"pytorch-ignite\",\n    version=VERSION,\n    author=\"PyTorch Core Team\",\n    author_email=\"soumith@pytorch.org\",\n    url=\"https://github.com/pytorch/ignite\",\n    description=\"A lightweight library to help with training neural networks in PyTorch.\",\n    long_description_content_type=\"text/markdown\",\n    long_description=readme,\n    license=\"BSD\",\n    # Package info\n    packages=find_packages(exclude=(\"tests\", \"tests.*\",)),\n    zip_safe=True,\n    install_requires=requirements,\n)\n", "path": "setup.py"}], "after_files": [{"content": "import os\nimport io\nimport re\nfrom setuptools import setup, find_packages\n\n\ndef read(*names, **kwargs):\n    with io.open(os.path.join(os.path.dirname(__file__), *names), encoding=kwargs.get(\"encoding\", \"utf8\")) as fp:\n        return fp.read()\n\n\ndef find_version(*file_paths):\n    version_file = read(*file_paths)\n    version_match = re.search(r\"^__version__ = ['\\\"]([^'\\\"]*)['\\\"]\", version_file, re.M)\n    if version_match:\n        return version_match.group(1)\n    raise RuntimeError(\"Unable to find version string.\")\n\n\nreadme = read(\"README.md\")\n\nVERSION = find_version(\"ignite\", \"__init__.py\")\n\nrequirements = [\n    \"torch>=1.0,<2\",\n]\n\nsetup(\n    # Metadata\n    name=\"pytorch-ignite\",\n    version=VERSION,\n    author=\"PyTorch Core Team\",\n    author_email=\"soumith@pytorch.org\",\n    url=\"https://github.com/pytorch/ignite\",\n    description=\"A lightweight library to help with training neural networks in PyTorch.\",\n    long_description_content_type=\"text/markdown\",\n    long_description=readme,\n    license=\"BSD\",\n    # Package info\n    packages=find_packages(exclude=(\"tests\", \"tests.*\",)),\n    zip_safe=True,\n    install_requires=requirements,\n)\n", "path": "setup.py"}]}