We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Could not find a version that satisfies the requirement cupy-cuda102==6.0.0 
```
ERROR: Could not find a version that satisfies the requirement cupy-cuda102==6.0.0 (from versions: 7.2.0, 7.3.0, 7.4.0, 7.5.0, 7.6.0, 8.0.0a1, 8.0.0b1, 8.0.0b2, 8.0.0b3, 8.0.0b4)
``` 
cupy-cuda102 doesn't have version 6.0.0 , upgrade ```CHAINER_VERSION := 6.0.0``` to ```CHAINER_VERSION := 7.4.0```, please

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `tools/check_install.py`
Content:
```
1 #!/usr/bin/env python3
2 
3 """Script to check whether the installation is done correctly."""
4 
5 # Copyright 2018 Nagoya University (Tomoki Hayashi)
6 #  Apache 2.0  (http://www.apache.org/licenses/LICENSE-2.0)
7 
8 import argparse
9 import importlib
10 import logging
11 import sys
12 
13 from distutils.version import LooseVersion
14 
15 
16 # NOTE: add the libraries which are not included in setup.py
17 MANUALLY_INSTALLED_LIBRARIES = [
18     ("espnet", None),
19     ("kaldiio", None),
20     ("matplotlib", None),
21     ("chainer", ("6.0.0")),
22     ("chainer_ctc", None),
23     ("warprnnt_pytorch", ("0.1")),
24 ]
25 
26 # NOTE: list all torch versions which are compatible with espnet
27 COMPATIBLE_TORCH_VERSIONS = (
28     "0.4.1",
29     "1.0.0",
30     "1.0.1",
31     "1.0.1.post2",
32     "1.1.0",
33     "1.2.0",
34     "1.3.0",
35     "1.3.1",
36     "1.4.0",
37     "1.5.0",
38     "1.5.1",
39 )
40 
41 
42 def main(args):
43     """Check the installation."""
44     parser = argparse.ArgumentParser()
45     parser.add_argument(
46         "--no-cuda",
47         action="store_true",
48         default=False,
49         help="Disable cuda-related tests",
50     )
51     args = parser.parse_args(args)
52 
53     logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
54     logging.info(f"python version = {sys.version}")
55 
56     library_list = []
57 
58     if not args.no_cuda:
59         library_list.append(("cupy", ("6.0.0")))
60 
61     # check torch installation at first
62     try:
63         import torch
64 
65         logging.info(f"pytorch version = {torch.__version__}")
66         if torch.__version__ not in COMPATIBLE_TORCH_VERSIONS:
67             logging.warning(f"{torch.__version__} is not tested. please be careful.")
68     except ImportError:
69         logging.warning("torch is not installed.")
70         logging.warning("please try to setup again and then re-run this script.")
71         sys.exit(1)
72 
73     # warpctc can be installed only for pytorch < 1.2
74     if LooseVersion(torch.__version__) < LooseVersion("1.2.0"):
75         library_list.append(("warpctc_pytorch", ("0.1.1", "0.1.3")))
76 
77     library_list.extend(MANUALLY_INSTALLED_LIBRARIES)
78 
79     # check library availableness
80     logging.info("library availableness check start.")
81     logging.info("# libraries to be checked = %d" % len(library_list))
82     is_correct_installed_list = []
83     for idx, (name, version) in enumerate(library_list):
84         try:
85             importlib.import_module(name)
86             logging.info("--> %s is installed." % name)
87             is_correct_installed_list.append(True)
88         except ImportError:
89             logging.warning("--> %s is not installed." % name)
90             is_correct_installed_list.append(False)
91     logging.info("library availableness check done.")
92     logging.info(
93         "%d / %d libraries are correctly installed."
94         % (sum(is_correct_installed_list), len(library_list))
95     )
96 
97     if len(library_list) != sum(is_correct_installed_list):
98         logging.warning("please try to setup again and then re-run this script.")
99         sys.exit(1)
100 
101     # check library version
102     num_version_specified = sum(
103         [True if v is not None else False for n, v in library_list]
104     )
105     logging.info("library version check start.")
106     logging.info("# libraries to be checked = %d" % num_version_specified)
107     is_correct_version_list = []
108     for idx, (name, version) in enumerate(library_list):
109         if version is not None:
110             # Note: temp. fix for warprnnt_pytorch
111             # not found version with importlib
112             if name == "warprnnt_pytorch":
113                 import pkg_resources
114 
115                 vers = pkg_resources.get_distribution(name).version
116             else:
117                 vers = importlib.import_module(name).__version__
118             if vers is not None:
119                 is_correct = vers in version
120                 if is_correct:
121                     logging.info("--> %s version is matched (%s)." % (name, vers))
122                     is_correct_version_list.append(True)
123                 else:
124                     logging.warning(
125                         "--> %s version is incorrect (%s is not in %s)."
126                         % (name, vers, str(version))
127                     )
128                     is_correct_version_list.append(False)
129             else:
130                 logging.info(
131                     "--> %s has no version info, but version is specified." % name
132                 )
133                 logging.info("--> maybe it is better to reinstall the latest version.")
134                 is_correct_version_list.append(False)
135     logging.info("library version check done.")
136     logging.info(
137         "%d / %d libraries are correct version."
138         % (sum(is_correct_version_list), num_version_specified)
139     )
140 
141     if sum(is_correct_version_list) != num_version_specified:
142         logging.info("please try to setup again and then re-run this script.")
143         sys.exit(1)
144 
145     # check cuda availableness
146     if args.no_cuda:
147         logging.info("cuda availableness check skipped.")
148     else:
149         logging.info("cuda availableness check start.")
150         import chainer
151         import torch
152 
153         try:
154             assert torch.cuda.is_available()
155             logging.info("--> cuda is available in torch.")
156         except AssertionError:
157             logging.warning("--> it seems that cuda is not available in torch.")
158         try:
159             assert torch.backends.cudnn.is_available()
160             logging.info("--> cudnn is available in torch.")
161         except AssertionError:
162             logging.warning("--> it seems that cudnn is not available in torch.")
163         try:
164             assert chainer.backends.cuda.available
165             logging.info("--> cuda is available in chainer.")
166         except AssertionError:
167             logging.warning("--> it seems that cuda is not available in chainer.")
168         try:
169             assert chainer.backends.cuda.cudnn_enabled
170             logging.info("--> cudnn is available in chainer.")
171         except AssertionError:
172             logging.warning("--> it seems that cudnn is not available in chainer.")
173         try:
174             from cupy.cuda import nccl  # NOQA
175 
176             logging.info("--> nccl is installed.")
177         except ImportError:
178             logging.warning(
179                 "--> it seems that nccl is not installed. multi-gpu is not enabled."
180             )
181             logging.warning(
182                 "--> if you want to use multi-gpu, please install it and then re-setup."
183             )
184         try:
185             assert torch.cuda.device_count() > 1
186             logging.info(
187                 f"--> multi-gpu is available (#gpus={torch.cuda.device_count()})."
188             )
189         except AssertionError:
190             logging.warning("--> it seems that only single gpu is available.")
191             logging.warning("--> maybe your machine has only one gpu.")
192         logging.info("cuda availableness check done.")
193 
194     logging.info("installation check is done.")
195 
196 
197 if __name__ == "__main__":
198     main(sys.argv[1:])
199
```
--- 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/tools/check_install.py b/tools/check_install.py
--- a/tools/check_install.py
+++ b/tools/check_install.py
@@ -48,14 +48,22 @@
         default=False,
         help="Disable cuda-related tests",
     )
+    parser.add_argument(
+        "--no-cupy",
+        action="store_true",
+        default=False,
+        help="Disable cupy test",
+    )
     args = parser.parse_args(args)
 
     logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
     logging.info(f"python version = {sys.version}")
 
     library_list = []
+    if args.no_cuda:
+        args.no_cupy = True
 
-    if not args.no_cuda:
+    if not args.no_cupy:
         library_list.append(("cupy", ("6.0.0")))
 
     # check torch installation at first

{"golden_diff": "diff --git a/tools/check_install.py b/tools/check_install.py\n--- a/tools/check_install.py\n+++ b/tools/check_install.py\n@@ -48,14 +48,22 @@\n         default=False,\n         help=\"Disable cuda-related tests\",\n     )\n+    parser.add_argument(\n+        \"--no-cupy\",\n+        action=\"store_true\",\n+        default=False,\n+        help=\"Disable cupy test\",\n+    )\n     args = parser.parse_args(args)\n \n     logging.basicConfig(level=logging.INFO, format=\"%(levelname)s: %(message)s\")\n     logging.info(f\"python version = {sys.version}\")\n \n     library_list = []\n+    if args.no_cuda:\n+        args.no_cupy = True\n \n-    if not args.no_cuda:\n+    if not args.no_cupy:\n         library_list.append((\"cupy\", (\"6.0.0\")))\n \n     # check torch installation at first\n", "issue": "Could not find a version that satisfies the requirement cupy-cuda102==6.0.0 \n```\r\nERROR: Could not find a version that satisfies the requirement cupy-cuda102==6.0.0 (from versions: 7.2.0, 7.3.0, 7.4.0, 7.5.0, 7.6.0, 8.0.0a1, 8.0.0b1, 8.0.0b2, 8.0.0b3, 8.0.0b4)\r\n``` \r\ncupy-cuda102 doesn't have version 6.0.0 , upgrade ```CHAINER_VERSION := 6.0.0``` to ```CHAINER_VERSION := 7.4.0```, please\n", "before_files": [{"content": "#!/usr/bin/env python3\n\n\"\"\"Script to check whether the installation is done correctly.\"\"\"\n\n# Copyright 2018 Nagoya University (Tomoki Hayashi)\n#  Apache 2.0  (http://www.apache.org/licenses/LICENSE-2.0)\n\nimport argparse\nimport importlib\nimport logging\nimport sys\n\nfrom distutils.version import LooseVersion\n\n\n# NOTE: add the libraries which are not included in setup.py\nMANUALLY_INSTALLED_LIBRARIES = [\n    (\"espnet\", None),\n    (\"kaldiio\", None),\n    (\"matplotlib\", None),\n    (\"chainer\", (\"6.0.0\")),\n    (\"chainer_ctc\", None),\n    (\"warprnnt_pytorch\", (\"0.1\")),\n]\n\n# NOTE: list all torch versions which are compatible with espnet\nCOMPATIBLE_TORCH_VERSIONS = (\n    \"0.4.1\",\n    \"1.0.0\",\n    \"1.0.1\",\n    \"1.0.1.post2\",\n    \"1.1.0\",\n    \"1.2.0\",\n    \"1.3.0\",\n    \"1.3.1\",\n    \"1.4.0\",\n    \"1.5.0\",\n    \"1.5.1\",\n)\n\n\ndef main(args):\n    \"\"\"Check the installation.\"\"\"\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\n        \"--no-cuda\",\n        action=\"store_true\",\n        default=False,\n        help=\"Disable cuda-related tests\",\n    )\n    args = parser.parse_args(args)\n\n    logging.basicConfig(level=logging.INFO, format=\"%(levelname)s: %(message)s\")\n    logging.info(f\"python version = {sys.version}\")\n\n    library_list = []\n\n    if not args.no_cuda:\n        library_list.append((\"cupy\", (\"6.0.0\")))\n\n    # check torch installation at first\n    try:\n        import torch\n\n        logging.info(f\"pytorch version = {torch.__version__}\")\n        if torch.__version__ not in COMPATIBLE_TORCH_VERSIONS:\n            logging.warning(f\"{torch.__version__} is not tested. please be careful.\")\n    except ImportError:\n        logging.warning(\"torch is not installed.\")\n        logging.warning(\"please try to setup again and then re-run this script.\")\n        sys.exit(1)\n\n    # warpctc can be installed only for pytorch < 1.2\n    if LooseVersion(torch.__version__) < LooseVersion(\"1.2.0\"):\n        library_list.append((\"warpctc_pytorch\", (\"0.1.1\", \"0.1.3\")))\n\n    library_list.extend(MANUALLY_INSTALLED_LIBRARIES)\n\n    # check library availableness\n    logging.info(\"library availableness check start.\")\n    logging.info(\"# libraries to be checked = %d\" % len(library_list))\n    is_correct_installed_list = []\n    for idx, (name, version) in enumerate(library_list):\n        try:\n            importlib.import_module(name)\n            logging.info(\"--> %s is installed.\" % name)\n            is_correct_installed_list.append(True)\n        except ImportError:\n            logging.warning(\"--> %s is not installed.\" % name)\n            is_correct_installed_list.append(False)\n    logging.info(\"library availableness check done.\")\n    logging.info(\n        \"%d / %d libraries are correctly installed.\"\n        % (sum(is_correct_installed_list), len(library_list))\n    )\n\n    if len(library_list) != sum(is_correct_installed_list):\n        logging.warning(\"please try to setup again and then re-run this script.\")\n        sys.exit(1)\n\n    # check library version\n    num_version_specified = sum(\n        [True if v is not None else False for n, v in library_list]\n    )\n    logging.info(\"library version check start.\")\n    logging.info(\"# libraries to be checked = %d\" % num_version_specified)\n    is_correct_version_list = []\n    for idx, (name, version) in enumerate(library_list):\n        if version is not None:\n            # Note: temp. fix for warprnnt_pytorch\n            # not found version with importlib\n            if name == \"warprnnt_pytorch\":\n                import pkg_resources\n\n                vers = pkg_resources.get_distribution(name).version\n            else:\n                vers = importlib.import_module(name).__version__\n            if vers is not None:\n                is_correct = vers in version\n                if is_correct:\n                    logging.info(\"--> %s version is matched (%s).\" % (name, vers))\n                    is_correct_version_list.append(True)\n                else:\n                    logging.warning(\n                        \"--> %s version is incorrect (%s is not in %s).\"\n                        % (name, vers, str(version))\n                    )\n                    is_correct_version_list.append(False)\n            else:\n                logging.info(\n                    \"--> %s has no version info, but version is specified.\" % name\n                )\n                logging.info(\"--> maybe it is better to reinstall the latest version.\")\n                is_correct_version_list.append(False)\n    logging.info(\"library version check done.\")\n    logging.info(\n        \"%d / %d libraries are correct version.\"\n        % (sum(is_correct_version_list), num_version_specified)\n    )\n\n    if sum(is_correct_version_list) != num_version_specified:\n        logging.info(\"please try to setup again and then re-run this script.\")\n        sys.exit(1)\n\n    # check cuda availableness\n    if args.no_cuda:\n        logging.info(\"cuda availableness check skipped.\")\n    else:\n        logging.info(\"cuda availableness check start.\")\n        import chainer\n        import torch\n\n        try:\n            assert torch.cuda.is_available()\n            logging.info(\"--> cuda is available in torch.\")\n        except AssertionError:\n            logging.warning(\"--> it seems that cuda is not available in torch.\")\n        try:\n            assert torch.backends.cudnn.is_available()\n            logging.info(\"--> cudnn is available in torch.\")\n        except AssertionError:\n            logging.warning(\"--> it seems that cudnn is not available in torch.\")\n        try:\n            assert chainer.backends.cuda.available\n            logging.info(\"--> cuda is available in chainer.\")\n        except AssertionError:\n            logging.warning(\"--> it seems that cuda is not available in chainer.\")\n        try:\n            assert chainer.backends.cuda.cudnn_enabled\n            logging.info(\"--> cudnn is available in chainer.\")\n        except AssertionError:\n            logging.warning(\"--> it seems that cudnn is not available in chainer.\")\n        try:\n            from cupy.cuda import nccl  # NOQA\n\n            logging.info(\"--> nccl is installed.\")\n        except ImportError:\n            logging.warning(\n                \"--> it seems that nccl is not installed. multi-gpu is not enabled.\"\n            )\n            logging.warning(\n                \"--> if you want to use multi-gpu, please install it and then re-setup.\"\n            )\n        try:\n            assert torch.cuda.device_count() > 1\n            logging.info(\n                f\"--> multi-gpu is available (#gpus={torch.cuda.device_count()}).\"\n            )\n        except AssertionError:\n            logging.warning(\"--> it seems that only single gpu is available.\")\n            logging.warning(\"--> maybe your machine has only one gpu.\")\n        logging.info(\"cuda availableness check done.\")\n\n    logging.info(\"installation check is done.\")\n\n\nif __name__ == \"__main__\":\n    main(sys.argv[1:])\n", "path": "tools/check_install.py"}], "after_files": [{"content": "#!/usr/bin/env python3\n\n\"\"\"Script to check whether the installation is done correctly.\"\"\"\n\n# Copyright 2018 Nagoya University (Tomoki Hayashi)\n#  Apache 2.0  (http://www.apache.org/licenses/LICENSE-2.0)\n\nimport argparse\nimport importlib\nimport logging\nimport sys\n\nfrom distutils.version import LooseVersion\n\n\n# NOTE: add the libraries which are not included in setup.py\nMANUALLY_INSTALLED_LIBRARIES = [\n    (\"espnet\", None),\n    (\"kaldiio\", None),\n    (\"matplotlib\", None),\n    (\"chainer\", (\"6.0.0\")),\n    (\"chainer_ctc\", None),\n    (\"warprnnt_pytorch\", (\"0.1\")),\n]\n\n# NOTE: list all torch versions which are compatible with espnet\nCOMPATIBLE_TORCH_VERSIONS = (\n    \"0.4.1\",\n    \"1.0.0\",\n    \"1.0.1\",\n    \"1.0.1.post2\",\n    \"1.1.0\",\n    \"1.2.0\",\n    \"1.3.0\",\n    \"1.3.1\",\n    \"1.4.0\",\n    \"1.5.0\",\n    \"1.5.1\",\n)\n\n\ndef main(args):\n    \"\"\"Check the installation.\"\"\"\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\n        \"--no-cuda\",\n        action=\"store_true\",\n        default=False,\n        help=\"Disable cuda-related tests\",\n    )\n    parser.add_argument(\n        \"--no-cupy\",\n        action=\"store_true\",\n        default=False,\n        help=\"Disable cupy test\",\n    )\n    args = parser.parse_args(args)\n\n    logging.basicConfig(level=logging.INFO, format=\"%(levelname)s: %(message)s\")\n    logging.info(f\"python version = {sys.version}\")\n\n    library_list = []\n    if args.no_cuda:\n        args.no_cupy = True\n\n    if not args.no_cupy:\n        library_list.append((\"cupy\", (\"6.0.0\")))\n\n    # check torch installation at first\n    try:\n        import torch\n\n        logging.info(f\"pytorch version = {torch.__version__}\")\n        if torch.__version__ not in COMPATIBLE_TORCH_VERSIONS:\n            logging.warning(f\"{torch.__version__} is not tested. please be careful.\")\n    except ImportError:\n        logging.warning(\"torch is not installed.\")\n        logging.warning(\"please try to setup again and then re-run this script.\")\n        sys.exit(1)\n\n    # warpctc can be installed only for pytorch < 1.2\n    if LooseVersion(torch.__version__) < LooseVersion(\"1.2.0\"):\n        library_list.append((\"warpctc_pytorch\", (\"0.1.1\", \"0.1.3\")))\n\n    library_list.extend(MANUALLY_INSTALLED_LIBRARIES)\n\n    # check library availableness\n    logging.info(\"library availableness check start.\")\n    logging.info(\"# libraries to be checked = %d\" % len(library_list))\n    is_correct_installed_list = []\n    for idx, (name, version) in enumerate(library_list):\n        try:\n            importlib.import_module(name)\n            logging.info(\"--> %s is installed.\" % name)\n            is_correct_installed_list.append(True)\n        except ImportError:\n            logging.warning(\"--> %s is not installed.\" % name)\n            is_correct_installed_list.append(False)\n    logging.info(\"library availableness check done.\")\n    logging.info(\n        \"%d / %d libraries are correctly installed.\"\n        % (sum(is_correct_installed_list), len(library_list))\n    )\n\n    if len(library_list) != sum(is_correct_installed_list):\n        logging.warning(\"please try to setup again and then re-run this script.\")\n        sys.exit(1)\n\n    # check library version\n    num_version_specified = sum(\n        [True if v is not None else False for n, v in library_list]\n    )\n    logging.info(\"library version check start.\")\n    logging.info(\"# libraries to be checked = %d\" % num_version_specified)\n    is_correct_version_list = []\n    for idx, (name, version) in enumerate(library_list):\n        if version is not None:\n            # Note: temp. fix for warprnnt_pytorch\n            # not found version with importlib\n            if name == \"warprnnt_pytorch\":\n                import pkg_resources\n\n                vers = pkg_resources.get_distribution(name).version\n            else:\n                vers = importlib.import_module(name).__version__\n            if vers is not None:\n                is_correct = vers in version\n                if is_correct:\n                    logging.info(\"--> %s version is matched (%s).\" % (name, vers))\n                    is_correct_version_list.append(True)\n                else:\n                    logging.warning(\n                        \"--> %s version is incorrect (%s is not in %s).\"\n                        % (name, vers, str(version))\n                    )\n                    is_correct_version_list.append(False)\n            else:\n                logging.info(\n                    \"--> %s has no version info, but version is specified.\" % name\n                )\n                logging.info(\"--> maybe it is better to reinstall the latest version.\")\n                is_correct_version_list.append(False)\n    logging.info(\"library version check done.\")\n    logging.info(\n        \"%d / %d libraries are correct version.\"\n        % (sum(is_correct_version_list), num_version_specified)\n    )\n\n    if sum(is_correct_version_list) != num_version_specified:\n        logging.info(\"please try to setup again and then re-run this script.\")\n        sys.exit(1)\n\n    # check cuda availableness\n    if args.no_cuda:\n        logging.info(\"cuda availableness check skipped.\")\n    else:\n        logging.info(\"cuda availableness check start.\")\n        import chainer\n        import torch\n\n        try:\n            assert torch.cuda.is_available()\n            logging.info(\"--> cuda is available in torch.\")\n        except AssertionError:\n            logging.warning(\"--> it seems that cuda is not available in torch.\")\n        try:\n            assert torch.backends.cudnn.is_available()\n            logging.info(\"--> cudnn is available in torch.\")\n        except AssertionError:\n            logging.warning(\"--> it seems that cudnn is not available in torch.\")\n        try:\n            assert chainer.backends.cuda.available\n            logging.info(\"--> cuda is available in chainer.\")\n        except AssertionError:\n            logging.warning(\"--> it seems that cuda is not available in chainer.\")\n        try:\n            assert chainer.backends.cuda.cudnn_enabled\n            logging.info(\"--> cudnn is available in chainer.\")\n        except AssertionError:\n            logging.warning(\"--> it seems that cudnn is not available in chainer.\")\n        try:\n            from cupy.cuda import nccl  # NOQA\n\n            logging.info(\"--> nccl is installed.\")\n        except ImportError:\n            logging.warning(\n                \"--> it seems that nccl is not installed. multi-gpu is not enabled.\"\n            )\n            logging.warning(\n                \"--> if you want to use multi-gpu, please install it and then re-setup.\"\n            )\n        try:\n            assert torch.cuda.device_count() > 1\n            logging.info(\n                f\"--> multi-gpu is available (#gpus={torch.cuda.device_count()}).\"\n            )\n        except AssertionError:\n            logging.warning(\"--> it seems that only single gpu is available.\")\n            logging.warning(\"--> maybe your machine has only one gpu.\")\n        logging.info(\"cuda availableness check done.\")\n\n    logging.info(\"installation check is done.\")\n\n\nif __name__ == \"__main__\":\n    main(sys.argv[1:])\n", "path": "tools/check_install.py"}]}