prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Do we support GPU distributed training?
  Hi, thanks for the awesome project!
  
  Does the code base support distributed training? If not, is it possible to support it after some code modifications?
  
  By the way, what is the way to set batch size and gpu number if I want to use GPU to train the model?
  
  Thank you for your kind attention.
  
  </issue>
  <code>
  [start of setup.py]
  1 # Copyright 2019 The T5 Authors.
  2 #
  3 # Licensed under the Apache License, Version 2.0 (the "License");
  4 # you may not use this file except in compliance with the License.
  5 # You may obtain a copy of the License at
  6 #
  7 #     http://www.apache.org/licenses/LICENSE-2.0
  8 #
  9 # Unless required by applicable law or agreed to in writing, software
  10 # distributed under the License is distributed on an "AS IS" BASIS,
  11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12 # See the License for the specific language governing permissions and
  13 # limitations under the License.
  14 
  15 """Install T5."""
  16 
  17 import setuptools
  18 
  19 # Get the long description from the README file.
  20 with open('README.md') as fp:
  21   _LONG_DESCRIPTION = fp.read()
  22 
  23 setuptools.setup(
  24     name='t5',
  25     version='0.1.7',
  26     description='Text-to-text transfer transformer',
  27     long_description=_LONG_DESCRIPTION,
  28     long_description_content_type='text/markdown',
  29     author='Google Inc.',
  30     author_email='no-reply@google.com',
  31     url='http://github.com/google-research/text-to-text-transfer-transformer',
  32     license='Apache 2.0',
  33     packages=setuptools.find_packages(),
  34     package_data={
  35         '': ['*.gin'],
  36     },
  37     scripts=[],
  38     install_requires=[
  39         'absl-py',
  40         'allennlp',
  41         'babel',
  42         'future',
  43         'gin-config',
  44         'mesh-tensorflow[transformer]>=0.1.8',
  45         'nltk',
  46         'numpy',
  47         'pandas',
  48         'rouge-score',
  49         'sacrebleu',
  50         'scikit-learn',
  51         'scipy',
  52         'sentencepiece',
  53         'six',
  54         'tensorflow-datasets>=1.3.2',
  55         'tensorflow-text==1.15.0rc0',
  56     ],
  57     extras_require={
  58         'tensorflow': ['tensorflow==1.15'],
  59         'gcp': ['gevent', 'google-api-python-client', 'google-compute-engine',
  60                 'google-cloud-storage', 'oauth2client'],
  61     },
  62     entry_points={
  63         'console_scripts': [
  64             't5_mesh_transformer = '
  65             't5.models.mesh_transformer_main:console_entry_point',
  66         ],
  67     },
  68     classifiers=[
  69         'Development Status :: 4 - Beta',
  70         'Intended Audience :: Developers',
  71         'Intended Audience :: Science/Research',
  72         'License :: OSI Approved :: Apache Software License',
  73         'Topic :: Scientific/Engineering :: Artificial Intelligence',
  74     ],
  75     keywords='text nlp machinelearning',
  76 )
  77
  [end of setup.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/setup.py b/setup.py
  --- a/setup.py
  +++ b/setup.py
  @@ -22,7 +22,7 @@
   
   setuptools.setup(
       name='t5',
  -    version='0.1.7',
  +    version='0.1.8',
       description='Text-to-text transfer transformer',
       long_description=_LONG_DESCRIPTION,
       long_description_content_type='text/markdown',
  @@ -41,7 +41,7 @@
           'babel',
           'future',
           'gin-config',
  -        'mesh-tensorflow[transformer]>=0.1.8',
  +        'mesh-tensorflow[transformer]>=0.1.9',
           'nltk',
           'numpy',
           'pandas',
  
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 \n setuptools.setup(\n     name='t5',\n-    version='0.1.7',\n+    version='0.1.8',\n     description='Text-to-text transfer transformer',\n     long_description=_LONG_DESCRIPTION,\n     long_description_content_type='text/markdown',\n@@ -41,7 +41,7 @@\n         'babel',\n         'future',\n         'gin-config',\n-        'mesh-tensorflow[transformer]>=0.1.8',\n+        'mesh-tensorflow[transformer]>=0.1.9',\n         'nltk',\n         'numpy',\n         'pandas',\n", "issue": "Do we support GPU distributed training?\nHi, thanks for the awesome project!\r\n\r\nDoes the code base support distributed training? If not, is it possible to support it after some code modifications?\r\n\r\nBy the way, what is the way to set batch size and gpu number if I want to use GPU to train the model?\r\n\r\nThank you for your kind attention.\n", "before_files": [{"content": "# Copyright 2019 The T5 Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n\"\"\"Install T5.\"\"\"\n\nimport setuptools\n\n# Get the long description from the README file.\nwith open('README.md') as fp:\n  _LONG_DESCRIPTION = fp.read()\n\nsetuptools.setup(\n    name='t5',\n    version='0.1.7',\n    description='Text-to-text transfer transformer',\n    long_description=_LONG_DESCRIPTION,\n    long_description_content_type='text/markdown',\n    author='Google Inc.',\n    author_email='no-reply@google.com',\n    url='http://github.com/google-research/text-to-text-transfer-transformer',\n    license='Apache 2.0',\n    packages=setuptools.find_packages(),\n    package_data={\n        '': ['*.gin'],\n    },\n    scripts=[],\n    install_requires=[\n        'absl-py',\n        'allennlp',\n        'babel',\n        'future',\n        'gin-config',\n        'mesh-tensorflow[transformer]>=0.1.8',\n        'nltk',\n        'numpy',\n        'pandas',\n        'rouge-score',\n        'sacrebleu',\n        'scikit-learn',\n        'scipy',\n        'sentencepiece',\n        'six',\n        'tensorflow-datasets>=1.3.2',\n        'tensorflow-text==1.15.0rc0',\n    ],\n    extras_require={\n        'tensorflow': ['tensorflow==1.15'],\n        'gcp': ['gevent', 'google-api-python-client', 'google-compute-engine',\n                'google-cloud-storage', 'oauth2client'],\n    },\n    entry_points={\n        'console_scripts': [\n            't5_mesh_transformer = '\n            't5.models.mesh_transformer_main:console_entry_point',\n        ],\n    },\n    classifiers=[\n        'Development Status :: 4 - Beta',\n        'Intended Audience :: Developers',\n        'Intended Audience :: Science/Research',\n        'License :: OSI Approved :: Apache Software License',\n        'Topic :: Scientific/Engineering :: Artificial Intelligence',\n    ],\n    keywords='text nlp machinelearning',\n)\n", "path": "setup.py"}]}