Update min python version to 3.7 in setup.py and mypy configs (pytorc…

…h#71494)

Summary:
As Python-3.6 have reached EOL

Pull Request resolved: pytorch#71494

Reviewed By: atalman

Differential Revision: D33667509

Pulled By: malfet

fbshipit-source-id: ab1f03085cfb9161df77ba5ce373b81f5e7ef3ae
(cherry picked from commit 6034316)

mypy-strict.ini

@@ -6,7 +6,7 @@
 # files.
 
 [mypy]
-python_version = 3.6
+python_version = 3.7
 plugins = mypy_plugins/check_mypy_version.py
 
 cache_dir = .mypy_cache/strict

mypy.ini

@@ -44,8 +44,8 @@ files =
 exclude = torch/include/|torch/csrc/|torch/distributed/elastic/agent/server/api.py|torch/testing/_internal
 
 # Minimum version supported - variable annotations were introduced
-# in Python 3.6
-python_version = 3.6
+# in Python 3.7
+python_version = 3.7
 
 
 #

setup.py

@@ -206,7 +206,7 @@
     sys.exit(-1)
 
 import platform
-python_min_version = (3, 6, 2)
+python_min_version = (3, 7, 0)
 python_min_version_str = '.'.join(map(str, python_min_version))
 if sys.version_info < python_min_version:
     print("You are using Python {}. Python >={} is required.".format(platform.python_version(),
@@ -408,7 +408,6 @@ def build_deps():
 # the list of runtime dependencies required by this built package
 install_requires = [
     'typing_extensions',
-    'dataclasses; python_version < "3.7"'
 ]
 
 missing_pydep = '''

test/test_jit.py

@@ -80,7 +80,6 @@
 # Torch
 from torch import Tensor
 from torch._C import TensorType, BoolType, parse_ir, _propagate_shapes
-from torch._six import PY37
 from torch.autograd import Variable
 from torch.jit.annotations import BroadcastingList2, BroadcastingList3, Any  # noqa: F401
 from torch.nn.utils.rnn import PackedSequence
@@ -6473,8 +6472,7 @@ def func(a, b):
         checkMathWrap("ceil", ret_type="int")
         checkMathWrap("gcd", 2, is_float=False, ret_type="int")
         checkMath("isfinite", 1, ret_type="bool")
-        if PY37:
-            checkMathWrap("remainder", 2)
+        checkMathWrap("remainder", 2)
         checkMathWrap("factorial", 1, is_float=False, ret_type="int", vals=[(i, 0) for i in range(-2, 10)])
 
     def test_if_nest_while(self):

tools/fast_nvcc/fast_nvcc.py

@@ -533,7 +533,7 @@ def fast_nvcc(
     print_command_outputs(results)
     if config.table:
         write_log_csv(command_parts, results, filename=config.table)
-    return exit_code([dryrun_data] + results)
+    return exit_code([dryrun_data] + results)  # type: ignore[arg-type, operator]
 
 
 def our_arg(arg: str) -> bool:

torch/_six.py

@@ -19,12 +19,10 @@
 # SOFTWARE.
 
 import math
-import sys
 
 inf = math.inf
 nan = math.nan
 string_classes = (str, bytes)
-PY37 = sys.version_info[0] == 3 and sys.version_info[1] >= 7
 
 def with_metaclass(meta: type, *bases) -> type:
     """Create a base class with a metaclass."""

torch/futures/__init__.py

@@ -1,20 +1,12 @@
 from typing import cast, Callable, Generic, List, Optional, Type, TypeVar, Union
 
 import torch
-from torch._six import PY37
 
 T = TypeVar("T")
 S = TypeVar("S")
 
-if not PY37:
-    # Workaround for https://github.com/python/typing/issues/449 in Python 3.6
-    from typing import GenericMeta
-
-    class _PyFutureMeta(type(torch._C.Future), GenericMeta):   # type: ignore[misc]
-        pass
-else:
-    class _PyFutureMeta(type(torch._C.Future), type(Generic)):  # type: ignore[misc, no-redef]
-        pass
+class _PyFutureMeta(type(torch._C.Future), type(Generic)):  # type: ignore[misc, no-redef]
+    pass
 
 class Future(torch._C.Future, Generic[T], metaclass=_PyFutureMeta):
     r"""

torch/jit/_builtins.py

@@ -5,7 +5,6 @@
 import torch
 import torch.backends.cudnn as cudnn
 
-from torch._six import PY37
 from ..nn.modules.utils import _single, _pair, _triple, _quadruple, _list_with_default
 
 from collections import OrderedDict
@@ -142,8 +141,7 @@ def register_all(mod):
 
     _builtin_ops.append((math.gcd, "aten::gcd"))
     _builtin_ops.append((math.isfinite, "aten::isfinite"))
-    if PY37:
-        _builtin_ops.append((math.remainder, "aten::mathremainder"))  # type: ignore[attr-defined]
+    _builtin_ops.append((math.remainder, "aten::mathremainder"))  # type: ignore[attr-defined]
 
     import torch.distributed.autograd as dist_autograd
     if dist_autograd.is_available():

torch/utils/data/_typing.py

@@ -9,25 +9,17 @@
 from typing import (Any, Dict, Iterator, Generic, List, Set, Tuple, TypeVar, Union,
                     get_type_hints)
 from typing import _eval_type, _tp_cache, _type_check, _type_repr  # type: ignore[attr-defined]
-
-try:  # Python > 3.6
-    from typing import ForwardRef  # type: ignore[attr-defined]
-except ImportError:  # Python 3.6
-    from typing import _ForwardRef as ForwardRef  # type: ignore[attr-defined]
+from typing import ForwardRef
 
 # TODO: Use TypeAlias when Python 3.6 is deprecated
 # Please check [Note: TypeMeta and TypeAlias]
-try:
-    from typing import GenericMeta  # Python 3.6
-    _GenericAlias = GenericMeta
-except ImportError:  # Python > 3.6
-    # In case of metaclass conflict due to ABCMeta or _ProtocolMeta
-    # For Python 3.9, only Protocol in typing uses metaclass
-    from abc import ABCMeta
-    from typing import _ProtocolMeta, _GenericAlias  # type: ignore[attr-defined, no-redef]
-
-    class GenericMeta(_ProtocolMeta, ABCMeta):  # type: ignore[no-redef]
-        pass
+# In case of metaclass conflict due to ABCMeta or _ProtocolMeta
+# For Python 3.9, only Protocol in typing uses metaclass
+from abc import ABCMeta
+from typing import _ProtocolMeta, _GenericAlias  # type: ignore[attr-defined, no-redef]
+
+class GenericMeta(_ProtocolMeta, ABCMeta):  # type: ignore[no-redef]
+    pass
 
 import torch