Turn on F401: Unused import warning. (#18598)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18598
ghimport-source-id: c74597e5e7437e94a43c163cee0639b20d0d0c6a

Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18598 Turn on F401: Unused import warning.**

This was requested by someone at Facebook; this lint is turned
on for Facebook by default.  "Sure, why not."

I had to noqa a number of imports in __init__.  Hypothetically
we're supposed to use __all__ in this case, but I was too lazy
to fix it.  Left for future work.

Be careful!  flake8-2 and flake8-3 behave differently with
respect to import resolution for # type: comments.  flake8-3 will
report an import unused; flake8-2 will not.  For now, I just
noqa'd all these sites.

All the changes were done by hand.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Differential Revision: D14687478

fbshipit-source-id: 30d532381e914091aadfa0d2a5a89404819663e3

.circleci/cimodel/lib/visualization.py

@@ -22,7 +22,7 @@ def handle_missing_graphviz(f):
     calls to the draw() method of the returned object to do nothing.
     """
     try:
-        import pygraphviz
+        import pygraphviz  # noqa: F401
         return f
 
     except ModuleNotFoundError:

.flake8

@@ -7,7 +7,7 @@ max-line-length = 120
 # C408 ignored because we like the dict keyword argument syntax
 # E501 is not flexible enough, we're using B950 instead
 ignore =
-    E203,E305,E402,E501,E721,E741,F401,F403,F405,F821,F841,F999,W503,W504,C408,
+    E203,E305,E402,E501,E721,E741,F403,F405,F821,F841,F999,W503,W504,C408,
     # these ignores are from flake8-bugbear; please fix!
     B007,B008,
     # these ignores are from flake8-comprehensions; please fix!

.jenkins/pytorch/perf_test/compare_with_baseline.py

@@ -1,7 +1,6 @@
 import sys
 import json
 import math
-import numpy
 import argparse
 
 parser = argparse.ArgumentParser()

benchmarks/fastrnns/__init__.py

@@ -1,5 +1,5 @@
-from .cells import *
-from .factory import *
+from .cells import *  # noqa: F401
+from .factory import *  # noqa: F401
 
 # (output, next_state) = cell(input, state)
 seqLength = 100

benchmarks/fastrnns/profile.py

@@ -1,5 +1,4 @@
 import argparse
-import os
 import subprocess
 import sys
 import time

benchmarks/fastrnns/test.py

@@ -2,7 +2,6 @@ import argparse
 import torch
 import torch.nn as nn
 
-from .cells import lstm_cell
 from .factory import pytorch_lstm_creator, varlen_pytorch_lstm_creator
 from .runner import get_nn_runners
 

docs/cpp/source/conf.py

@@ -20,11 +20,8 @@
 import os
 # sys.path.insert(0, os.path.abspath('.'))
 
-import sys
 import textwrap
 
-import pytorch_sphinx_theme
-
 # -- General configuration ------------------------------------------------
 
 # If your documentation needs a minimal Sphinx version, state it here.

docs/source/conf.py

@@ -25,7 +25,7 @@ import os
 
 import torch
 try:
-    import torchvision
+    import torchvision  # noqa: F401
 except ImportError:
     import warnings
     warnings.warn('unable to load "torchvision" package')

setup.py

@@ -142,7 +142,7 @@
 #     we will search for libraries in these paths
 
 from __future__ import print_function
-from setuptools import setup, Extension, distutils, Command, find_packages
+from setuptools import setup, Extension, distutils, find_packages
 from distutils import core, dir_util
 from distutils.core import Distribution
 from distutils.errors import DistutilsArgError
@@ -151,7 +151,6 @@ import setuptools.command.install
 import distutils.command.clean
 import distutils.sysconfig
 import filecmp
-import platform
 import subprocess
 import shutil
 import sys

test/common_methods_invocations.py

@@ -1,9 +1,9 @@
 import torch
-from torch._six import inf, nan, istuple
-from functools import reduce, wraps
+from torch._six import inf, istuple
+from functools import reduce
 from operator import mul, itemgetter
 import collections
-from torch.autograd import Variable, Function, detect_anomaly
+from torch.autograd import Variable
 from torch.testing import make_non_contiguous
 from common_utils import (skipIfNoLapack,
                           prod_single_zero, random_square_matrix_of_rank,

test/common_nn.py

@@ -13,7 +13,7 @@ import torch.nn as nn
 import torch.nn.functional as F
 from torch.nn.functional import _Reduction
 from common_utils import TestCase, to_gpu, freeze_rng_state, is_iterable, \
-    TEST_WITH_ROCM, skipIfRocm
+    TEST_WITH_ROCM
 from common_cuda import TEST_CUDA
 from torch.autograd.gradcheck import get_numerical_jacobian, iter_tensors
 from torch.autograd import Variable

test/custom_operator/test_custom_ops.py

@@ -1,4 +1,3 @@
-import argparse
 import os.path
 import tempfile
 import unittest

test/onnx/debug_embed_params.py

@@ -4,12 +4,10 @@ from __future__ import print_function
 from __future__ import unicode_literals
 
 import sys
-import itertools
 
 import torch
 import torch.jit
 from torch.autograd import Variable
-import torch.autograd.function as function
 
 import onnx
 import caffe2.python.onnx.backend as c2

test/onnx/export_onnx_tests_filter.py

@@ -5,12 +5,9 @@ from __future__ import unicode_literals
 
 import argparse
 import glob
-import numpy as np
 import onnx.backend.test
-import caffe2.python.onnx.backend as c2
 import os
 import shutil
-from onnx import numpy_helper
 from test_caffe2_common import run_generated_test
 import google.protobuf.text_format
 import test_onnx_common

test/onnx/export_onnx_tests_generator.py

@@ -13,7 +13,6 @@ import shutil
 import torch
 import traceback
 
-import test_pytorch_common
 import test_onnx_common
 from common_nn import module_tests
 from test_nn import new_module_tests

test/onnx/model_defs/__init__.py

@@ -1,4 +1,4 @@
-from .squeezenet import *
-from .super_resolution import *
-from .op_test import *
-from .srresnet import *
+from .squeezenet import *  # noqa: F401
+from .super_resolution import *  # noqa: F401
+from .op_test import *  # noqa: F401
+from .srresnet import *  # noqa: F401

test/onnx/model_defs/squeezenet.py

@@ -1,4 +1,3 @@
-import math
 import torch
 import torch.nn as nn
 import torch.nn.init as init

test/onnx/model_defs/super_resolution.py

@@ -1,4 +1,3 @@
-import torch
 import torch.nn as nn
 import torch.nn.init as init
 

test/onnx/model_defs/word_language_model.py

@@ -3,7 +3,6 @@
 
 import torch
 import torch.nn as nn
-from torch.autograd import Variable
 
 
 class RNNModel(nn.Module):

test/onnx/test_models.py

@@ -5,7 +5,6 @@ from torchvision.models.resnet import resnet50
 from torchvision.models.vgg import vgg16, vgg16_bn, vgg19, vgg19_bn
 
 from model_defs.mnist import MNIST
-from model_defs.word_language_model import RNNModel
 from model_defs.squeezenet import SqueezeNet
 from model_defs.super_resolution import SuperResolutionNet
 from model_defs.srresnet import SRResNet
@@ -17,17 +16,9 @@ from test_pytorch_common import TestCase, run_tests, skipIfNoLapack
 import torch
 import torch.onnx
 import torch.onnx.utils
-from torch.autograd import Variable, Function
-from torch.nn import Module
+from torch.autograd import Variable
 from torch.onnx import OperatorExportTypes
 
-import onnx
-import onnx.checker
-import onnx.helper
-
-import google.protobuf.text_format
-
-import io
 import unittest
 
 import caffe2.python.onnx.backend as backend

test/onnx/test_operators.py

@@ -1,4 +1,4 @@
-from test_pytorch_common import TestCase, run_tests, skipIfNoLapack, flatten
+from test_pytorch_common import TestCase, run_tests, flatten
 
 import torch
 import torch.onnx
@@ -10,11 +10,9 @@ import itertools
 import io
 import unittest
 import inspect
-import argparse
 import glob
 import os
 import shutil
-import sys
 import common_utils as common
 
 

test/onnx/test_pytorch_common.py

@@ -13,7 +13,7 @@ import torch.autograd.function as function
 pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
 sys.path.insert(-1, pytorch_test_dir)
 
-from common_utils import *
+from common_utils import *  # noqa: F401
 
 torch.set_default_tensor_type('torch.FloatTensor')
 

test/onnx/test_pytorch_helper.py

@@ -1,7 +1,6 @@
 # Some standard imports
 import numpy as np
 from torch import nn
-from torch.autograd import Variable
 import torch.onnx
 import torch.nn.init as init
 from caffe2.python.model_helper import ModelHelper

test/onnx/test_pytorch_onnx_caffe2.py

@@ -3,7 +3,6 @@ from __future__ import division
 from __future__ import print_function
 from __future__ import unicode_literals
 
-from functools import wraps
 import numpy as np
 import sys
 import unittest

test/optim/test.py

@@ -1,7 +1,6 @@
 import json
 import torch
 import torch.legacy.optim as optim
-from pprint import pprint
 
 
 def rosenbrock(tensor):

test/test_autograd.py

@@ -8,8 +8,8 @@ import warnings
 from copy import deepcopy
 from collections import OrderedDict
 from itertools import product
-from operator import mul, itemgetter
-from functools import reduce, wraps
+from operator import mul
+from functools import reduce
 from torch._six import inf, nan, istuple
 from torch.autograd.gradcheck import gradgradcheck, gradcheck
 from torch.autograd.function import once_differentiable
@@ -17,14 +17,11 @@ from torch.autograd.profiler import profile
 from torch.utils.checkpoint import checkpoint
 from common_utils import (TEST_MKL, TestCase, run_tests, skipIfNoLapack,
                           suppress_warnings, skipIfRocm,
-                          prod_single_zero, random_square_matrix_of_rank,
-                          random_symmetric_matrix, random_symmetric_psd_matrix,
-                          random_symmetric_pd_matrix, make_nonzero_det,
-                          random_fullrank_matrix_distinct_singular_value, load_tests)
+                          load_tests)
 from common_cuda import TEST_CUDA
 from torch.autograd import Variable, Function, detect_anomaly
 from torch.autograd.function import InplaceFunction
-from torch.testing import make_non_contiguous, randn_like
+from torch.testing import randn_like
 from common_methods_invocations import (method_tests,
                                         create_input, unpack_variables,
                                         EXCLUDE_FUNCTIONAL, EXCLUDE_GRADCHECK,
@@ -32,7 +29,7 @@ from common_methods_invocations import (method_tests,
                                         EXCLUDE_GRADGRADCHECK_BY_TEST_NAME,
                                         exclude_tensor_method,
                                         mask_not_all_zeros,
-                                        L, S)
+                                        S)
 
 # load_tests from common_utils is used to automatically filter tests for
 # sharding on sandcastle. This line silences flake warnings

test/test_cuda.py

@@ -1,7 +1,5 @@
 import io
-import math
 import tempfile
-import re
 import unittest
 import sys
 from itertools import repeat
@@ -19,9 +17,9 @@ from torch._six import inf, nan
 from test_torch import _TestTorchMixin
 
 from common_methods_invocations import tri_tests_args, tri_large_tests_args, \
-    run_additional_tri_tests, _compare_trilu_indices, _compare_large_trilu_indices
+    _compare_trilu_indices, _compare_large_trilu_indices
 from common_utils import TestCase, get_gpu_type, to_gpu, freeze_rng_state, run_tests, \
-    PY3, IS_WINDOWS, NO_MULTIPROCESSING_SPAWN, skipIfRocm, TEST_NUMPY, TEST_WITH_ROCM, load_tests, iter_indices
+    PY3, IS_WINDOWS, NO_MULTIPROCESSING_SPAWN, skipIfRocm, TEST_NUMPY, TEST_WITH_ROCM, load_tests
 
 # load_tests from common_utils is used to automatically filter tests for
 # sharding on sandcastle. This line silences flake warnings

test/test_dataloader.py

@@ -3,13 +3,10 @@ import sys
 import errno
 import os
 import ctypes
-import signal
 import torch
 import gc
 import time
-import traceback
 import unittest
-import subprocess
 import itertools
 import warnings
 from torch import multiprocessing as mp

test/test_distributed.py

@@ -16,11 +16,9 @@ import torch.cuda
 import torch.distributed as dist
 import torch.nn as nn
 import torch.nn.functional as F
-import torch.optim as optim
 from common_utils import TestCase, run_tests
 from torch._utils_internal import TEST_MASTER_ADDR as MASTER_ADDR
 from torch._utils_internal import TEST_MASTER_PORT as MASTER_PORT
-import common_utils as common
 
 BACKEND = os.environ["BACKEND"]
 TEMP_DIR = os.environ["TEMP_DIR"]

test/test_docs_coverage.py

@@ -2,8 +2,6 @@ import torch
 import unittest
 import os
 import re
-import ast
-import _ast
 import textwrap
 
 

test/test_indexing.py

@@ -1,6 +1,5 @@
 from common_utils import TestCase, run_tests
 import torch
-import warnings
 from torch import tensor
 import unittest
 

test/test_jit.py

@@ -12,9 +12,6 @@ from contextlib import contextmanager
 from itertools import product, chain
 import torch.jit.frontend
 from torch.autograd import Variable, Function
-from torch.nn import Module
-from torch.autograd.function import traceable
-from torch.testing import assert_allclose
 from torch.onnx import OperatorExportTypes
 from torch._six import inf, PY2, builtins, StringIO
 from common_utils import TestCase, run_tests, IS_WINDOWS, TEST_WITH_UBSAN, \
@@ -25,7 +22,6 @@ from textwrap import dedent
 from functools import wraps
 import os
 import io
-import itertools
 import sys
 import unittest
 import inspect
@@ -46,14 +42,13 @@ from common_methods_invocations import method_tests as autograd_method_tests
 from common_methods_invocations import create_input, unpack_variables, \
     exclude_tensor_method, non_differentiable, EXCLUDE_GRADCHECK, EXCLUDE_FUNCTIONAL
 from torch.testing import FileCheck
-from torch._C import TensorType, TupleType, FloatType, IntType, \
-    ListType, StringType, DictType
+from torch._C import TensorType
 from copy import deepcopy
 import random
 from typing import List, Dict, Optional, Tuple
 from torch.jit.frontend import NotSupportedError
 from torch import Tensor
-from torch.jit.annotations import BroadcastingList2, BroadcastingList3
+from torch.jit.annotations import BroadcastingList2, BroadcastingList3  # noqa: F401
 
 # For testing truediv in python 2
 from test_module.future_div import div_int_future, div_float_future
@@ -6727,8 +6722,6 @@ a")
 
     @unittest.skipIf(not PY35, "Python 3.5 needed")
     def test_type_annotation_py3(self):
-        import importlib.util
-
         code = dedent("""
         import torch
         from torch import Tensor
@@ -9349,8 +9342,6 @@ a")
             foo(torch.ones([123]))  # wrong size
 
     def test_builtin_error_messsage(self):
-        from torch.nn.modules.utils import _single, _pair, _triple, _quadruple
-
         with self.assertRaisesRegex(RuntimeError, "arguments for call are not valid"):
             @torch.jit.script
             def close_match(x):
@@ -11020,8 +11011,6 @@ class TestEndToEndHybridFrontendModels(JitTestCase):
 
     @staticmethod
     def _test_super_resolution(self, device, check_export_import=True):
-        import torch.nn.init as init
-
         class Net(nn.Module):
 
             def __init__(self, upscale_factor):

test/test_jit_fuser.py

@@ -3,17 +3,12 @@ from __future__ import division
 from __future__ import print_function
 from __future__ import unicode_literals
 
-import functools
-import os
 import unittest
-import sys
 import torch
-import torch.autograd.function as function
 from torch import Tensor
 
-from common_utils import TestCase, run_tests, IS_WINDOWS, \
+from common_utils import IS_WINDOWS, \
     skipIfRocm, IS_SANDCASTLE
-from typing import List, Dict, Optional, Tuple
 
 from test_jit import JitTestCase, enable_cpu_fuser, RUN_CUDA, RUN_CUDA_HALF, RUN_CUDA_MULTI_GPU, \
     backward_graph

test/test_module/future_div.py

@@ -1,5 +1,5 @@
 from __future__ import division
-import torch
+import torch  # noqa: F401
 
 
 def div_int_future():

test/test_module/no_future_div.py

@@ -1,4 +1,4 @@
-import torch
+import torch  # noqa: F401
 
 
 def div_int_nofuture():

test/test_multiprocessing.py

@@ -13,7 +13,6 @@ import torch.utils.hooks
 from torch.nn import Parameter
 from common_utils import (TestCase, run_tests, IS_WINDOWS, NO_MULTIPROCESSING_SPAWN, TEST_WITH_ASAN,
                           load_tests, slowTest)
-from multiprocessing.reduction import ForkingPickler
 
 # load_tests from common_utils is used to automatically filter tests for
 # sharding on sandcastle. This line silences flake warnings

test/test_nn.py

@@ -11,8 +11,6 @@ from itertools import repeat, product
 from functools import wraps, reduce
 from operator import mul
 from collections import OrderedDict
-import hashlib
-import os
 import threading
 
 import torch
@@ -29,9 +27,9 @@ from torch.autograd import Variable, gradcheck
 from torch.autograd.gradcheck import gradgradcheck
 from torch.nn import Parameter
 from torch.nn.parallel._functions import Broadcast
-from common_utils import freeze_rng_state, run_tests, TestCase, skipIfNoLapack, skipIfRocm, TEST_WITH_ROCM, \
-    TEST_NUMPY, TEST_SCIPY, IS_WINDOWS, download_file, PY3, PY34, to_gpu, \
-    get_function_arglist, skipCUDAMemoryLeakCheckIf, load_tests
+from common_utils import freeze_rng_state, run_tests, TestCase, skipIfNoLapack, skipIfRocm, \
+    TEST_NUMPY, TEST_SCIPY, download_file, PY3, PY34, to_gpu, \
+    get_function_arglist, load_tests
 from common_cuda import TEST_CUDA, TEST_MULTIGPU, TEST_CUDNN, \
     TEST_CUDNN_VERSION
 from common_nn import NNTestCase, ModuleTest, CriterionTest, TestBase, \

test/test_quantized.py

@@ -1,13 +1,9 @@
 import torch
 import torch.jit
-import torch.nn as nn
-import torch.nn.functional as F
 import numpy as np
 import unittest
 from caffe2.python import core
-from common_utils import TestCase, run_tests, IS_WINDOWS, TEST_WITH_UBSAN, \
-    skipIfRocm, skipIfNoLapack, suppress_warnings, load_tests, IS_SANDCASTLE, \
-    freeze_rng_state, set_rng_seed
+from common_utils import TestCase, run_tests
 
 
 def canonical(graph):

test/test_sparse.py

@@ -1,5 +1,4 @@
 import torch
-from torch import sparse
 
 import itertools
 import functools

test/test_thd_distributed.py

@@ -15,7 +15,6 @@ import torch.cuda
 import torch.distributed.deprecated as dist
 import torch.nn as nn
 import torch.nn.functional as F
-import torch.optim as optim
 from common_utils import TestCase, run_tests
 from torch._utils_internal import TEST_MASTER_ADDR as MASTER_ADDR
 

test/test_torch.py

@@ -3,7 +3,6 @@ import io
 import os
 import math
 import random
-import operator
 import copy
 import shutil
 import torch
@@ -17,7 +16,7 @@ import gzip
 import types
 import textwrap
 import re
-from torch._utils_internal import get_file_path, get_file_path_2
+from torch._utils_internal import get_file_path_2
 from torch.utils.dlpack import from_dlpack, to_dlpack
 from torch._utils import _rebuild_tensor
 from torch._six import inf, nan, string_classes, istuple
@@ -2032,7 +2031,6 @@ class _TestTorchMixin(object):
     def _test_int_pow(self, cast):
         if not TEST_NUMPY:
             return
-        import numpy as np
 
         def check_against_np(tensor, exp):
             tensor_np = tensor.cpu().numpy()
@@ -4669,7 +4667,6 @@ class _TestTorchMixin(object):
         # Test non-contiguous inputs.
         if not TEST_NUMPY:
             return
-        import numpy
         from numpy.linalg import solve
         A = cast(random_fullrank_matrix_distinct_singular_value(2, 2)).permute(1, 0, 2)
         b = cast(torch.randn(2, 2, 2)).permute(2, 1, 0)
@@ -6218,7 +6215,6 @@ class _TestTorchMixin(object):
             # Test non-contiguous inputs.
             if not TEST_NUMPY:
                 return
-            import numpy
             from numpy.linalg import solve
             A = random_symmetric_pd_matrix(2, 2)
             b = torch.randn(2, 2, 2)

test/test_type_hints.py

@@ -1,6 +1,6 @@
 from __future__ import print_function
 import unittest
-from common_utils import TestCase, run_tests, download_file
+from common_utils import TestCase, run_tests
 import tempfile
 import torch
 import re
@@ -10,7 +10,7 @@ import subprocess
 import inspect
 
 try:
-    import mypy
+    import mypy  # noqa: F401
     HAVE_MYPY = True
 except ImportError:
     HAVE_MYPY = False

test/test_utils.py

@@ -2,22 +2,19 @@ from __future__ import print_function
 import sys
 import os
 import re
-import math
 import shutil
 import random
 import tempfile
 import unittest
-import traceback
 import torch
 import torch.nn as nn
 import torch.utils.data
 import torch.cuda
-import warnings
 from torch.utils.checkpoint import checkpoint, checkpoint_sequential
 import torch.hub as hub
 from torch.autograd._functions.utils import prepare_onnx_paddings
 from torch.autograd._functions.utils import check_onnx_broadcast
-from common_utils import IS_WINDOWS, IS_PPC, skipIfRocm, load_tests
+from common_utils import skipIfRocm, load_tests
 
 # load_tests from common_utils is used to automatically filter tests for
 # sharding on sandcastle. This line silences flake warnings
@@ -34,7 +31,7 @@ skipIfNoTorchVision = unittest.skipIf(not HAS_TORCHVISION, "no torchvision")
 
 HAS_CUDA = torch.cuda.is_available()
 
-from common_utils import TestCase, run_tests, download_file
+from common_utils import TestCase, run_tests
 
 
 class RandomDatasetMock(object):
@@ -326,7 +323,7 @@ test_dir = os.path.abspath(os.path.dirname(str(__file__)))
 class TestFFI(TestCase):
     def test_deprecated(self):
         with self.assertRaisesRegex(ImportError, "torch.utils.ffi is deprecated. Please use cpp extensions instead."):
-            from torch.utils.ffi import create_extension
+            from torch.utils.ffi import create_extension  # noqa: F401
 
 
 @unittest.skipIf('SKIP_TEST_BOTTLENECK' in os.environ.keys(), 'SKIP_TEST_BOTTLENECK is set')

tools/amd_build/build_amd.py

@@ -2,7 +2,6 @@
 
 from __future__ import absolute_import, division, print_function
 import os
-import sys
 import subprocess
 import argparse
 from functools import reduce

tools/autograd/gen_variable_type.py

@@ -23,7 +23,6 @@
 #     differentiable subcomponents.
 #
 from __future__ import print_function
-import os
 import sys
 from .utils import CodeTemplate, nested_dict, write, uninplace_api_name
 from .gen_autograd import VIEW_FUNCTIONS

tools/build_libtorch.py

@@ -1,8 +1,5 @@
 import argparse
-import os
 from os.path import dirname, abspath
-import shlex
-import subprocess
 import sys
 
 # By appending pytorch_root to sys.path, this module can import other torch

tools/build_pytorch_libs.py

@@ -1,22 +1,20 @@
-from .setup_helpers.env import (IS_64BIT, IS_ARM, IS_DARWIN, IS_LINUX, IS_PPC, IS_WINDOWS,
+from .setup_helpers.env import (IS_64BIT, IS_DARWIN, IS_WINDOWS,
                                 DEBUG, REL_WITH_DEB_INFO, USE_MKLDNN,
-                                check_env_flag, check_negative_env_flag, hotpatch_build_env_vars)
+                                check_env_flag, check_negative_env_flag)
 
 import os
 import sys
 import distutils
 import distutils.sysconfig
-from distutils.file_util import copy_file
-from distutils.dir_util import copy_tree
-from subprocess import check_call, call, check_output
+from subprocess import check_call, check_output
 from distutils.version import LooseVersion
 from .setup_helpers.cuda import USE_CUDA, CUDA_HOME
 from .setup_helpers.dist_check import USE_DISTRIBUTED, USE_GLOO_IBVERBS
 from .setup_helpers.nccl import USE_SYSTEM_NCCL, NCCL_INCLUDE_DIR, NCCL_ROOT_DIR, NCCL_SYSTEM_LIB, USE_NCCL
-from .setup_helpers.rocm import ROCM_HOME, ROCM_VERSION, USE_ROCM
+from .setup_helpers.rocm import USE_ROCM
 from .setup_helpers.nnpack import USE_NNPACK
 from .setup_helpers.qnnpack import USE_QNNPACK
-from .setup_helpers.cudnn import CUDNN_INCLUDE_DIR, CUDNN_LIB_DIR, CUDNN_LIBRARY, USE_CUDNN
+from .setup_helpers.cudnn import CUDNN_INCLUDE_DIR, CUDNN_LIBRARY, USE_CUDNN
 
 
 from pprint import pprint

tools/clang_format.py

@@ -12,9 +12,7 @@ Only files that are in CLANG_FORMAT_WHITELIST are checked.
 import subprocess
 import os
 import argparse
-import fnmatch
 import difflib
-import sys
 import re
 
 

tools/cwrap/__init__.py

@@ -1 +1 @@
-from .cwrap import cwrap
+from .cwrap import cwrap  # noqa: F401

tools/cwrap/plugins/ArgumentReferences.py

@@ -1,5 +1,4 @@
 from . import CWrapPlugin
-from string import Template
 
 
 class ArgumentReferences(CWrapPlugin):

tools/cwrap/plugins/CuDNNPlugin.py

@@ -1,8 +1,6 @@
 from string import Template
 import copy
-from copy import deepcopy
 from . import CWrapPlugin
-from itertools import product
 
 
 class CuDNNPlugin(CWrapPlugin):

tools/cwrap/plugins/GILRelease.py

@@ -1,5 +1,4 @@
 from . import CWrapPlugin
-from string import Template
 
 
 class GILRelease(CWrapPlugin):

tools/cwrap/plugins/OptionalArguments.py

@@ -1,7 +1,4 @@
-import os
-from copy import deepcopy
 from . import CWrapPlugin
-from itertools import product
 from ...shared import cwrap_common
 
 

tools/cwrap/plugins/__init__.py

@@ -420,15 +420,15 @@ class CWrapPlugin(object):
         return template
 
 
-from .NNExtension import NNExtension
-from .NullableArguments import NullableArguments
-from .OptionalArguments import OptionalArguments
-from .ArgcountChecker import ArgcountChecker
-from .ArgumentReferences import ArgumentReferences
-from .BeforeAfterCall import BeforeAfterCall
-from .ConstantArguments import ConstantArguments
-from .ReturnArguments import ReturnArguments
-from .GILRelease import GILRelease
-from .AutoGPU import AutoGPU
-from .CuDNNPlugin import CuDNNPlugin
-from .WrapDim import WrapDim
+from .NNExtension import NNExtension  # noqa: F401
+from .NullableArguments import NullableArguments  # noqa: F401
+from .OptionalArguments import OptionalArguments  # noqa: F401
+from .ArgcountChecker import ArgcountChecker  # noqa: F401
+from .ArgumentReferences import ArgumentReferences  # noqa: F401
+from .BeforeAfterCall import BeforeAfterCall  # noqa: F401
+from .ConstantArguments import ConstantArguments  # noqa: F401
+from .ReturnArguments import ReturnArguments  # noqa: F401
+from .GILRelease import GILRelease  # noqa: F401
+from .AutoGPU import AutoGPU  # noqa: F401
+from .CuDNNPlugin import CuDNNPlugin  # noqa: F401
+from .WrapDim import WrapDim  # noqa: F401

tools/download_mnist.py

@@ -5,7 +5,6 @@ import argparse
 import gzip
 import os
 import sys
-import urllib
 
 try:
     from urllib.error import URLError

tools/jit/gen_jit_dispatch.py

@@ -12,14 +12,11 @@ generated.  In the full build system, OUTPUT_DIR is
 torch/csrc/jit/generated/
 """
 
-import os
 import argparse
-import re
 import copy
-from itertools import count, combinations, groupby
-from ..autograd.utils import CodeTemplate, write, uninplace_api_name
+from itertools import groupby
+from ..autograd.utils import CodeTemplate, write
 from ..autograd.gen_autograd import load_aten_declarations
-from collections import OrderedDict
 from ..autograd.gen_autograd import RETURNS_VIEWS_OF_INPUT
 
 # JIT has a type system of

tools/nnwrap/__init__.py

@@ -1 +1 @@
-from .generate_wrappers import generate_wrappers, wrap_function, import_module
+from .generate_wrappers import generate_wrappers, wrap_function, import_module  # noqa: F401

tools/nnwrap/generate_wrappers.py

@@ -1,6 +1,5 @@
 import os
-import sys
-from string import Template, ascii_lowercase
+from string import Template
 from ..cwrap import cwrap
 from ..cwrap.plugins import NNExtension, NullableArguments, AutoGPU
 from ..shared import import_module

tools/pyi/gen_pyi.py

@@ -1,11 +1,7 @@
 from __future__ import print_function
-import multiprocessing
-import sys
 import os
-import inspect
 import collections
 import yaml
-import types
 import re
 import argparse
 

tools/setup_helpers/dist_check.py

@@ -2,8 +2,7 @@ import os
 import subprocess
 import glob
 
-from .env import IS_CONDA, IS_LINUX, IS_WINDOWS, CONDA_DIR, check_env_flag, check_negative_env_flag, gather_paths
-from .cuda import USE_CUDA
+from .env import IS_CONDA, IS_WINDOWS, CONDA_DIR, check_env_flag, check_negative_env_flag, gather_paths
 
 # On ROCm, RCCL development isn't complete. https://github.com/ROCmSoftwarePlatform/rccl
 USE_DISTRIBUTED = not check_negative_env_flag("USE_DISTRIBUTED") and not IS_WINDOWS and not check_env_flag("USE_ROCM")

tools/setup_helpers/miopen.py

@@ -1,7 +1,4 @@
-import os
-import glob
-
-from .env import IS_WINDOWS, IS_CONDA, CONDA_DIR, check_env_flag, gather_paths
+from .env import check_env_flag
 from .rocm import USE_ROCM, ROCM_HOME
 
 

tools/setup_helpers/nccl.py

@@ -1,7 +1,5 @@
 import os
 import glob
-import warnings
-from itertools import chain
 
 from .env import IS_WINDOWS, IS_DARWIN, IS_CONDA, CONDA_DIR, check_negative_env_flag, \
     gather_paths

tools/setup_helpers/nvtoolext.py

@@ -1,7 +1,6 @@
 import os
 import platform
 import ctypes.util
-from subprocess import Popen, PIPE
 
 from .cuda import USE_CUDA
 

tools/shared/__init__.py

@@ -1,3 +1,2 @@
-from .module_loader import import_module
-from .cwrap_common import set_declaration_defaults, \
-    sort_by_number_of_options, enumerate_options_due_to_default
+from .module_loader import import_module  # noqa: F401
+from .cwrap_common import set_declaration_defaults, sort_by_number_of_options, enumerate_options_due_to_default  # noqa: F401

torch/__init__.py

@@ -13,7 +13,7 @@ import sys
 import platform
 from ._utils import _import_dotted_name
 from ._utils_internal import get_file_path, prepare_multiprocessing_environment
-from .version import __version__
+from .version import __version__  # noqa: F401
 from ._six import string_classes as _string_classes
 
 __all__ = [
@@ -39,7 +39,7 @@ import os as _dl_flags
 # if we have numpy, it *must* be imported before the call to setdlopenflags()
 # or there is risk that later c modules will segfault when importing numpy
 try:
-    import numpy as _np
+    import numpy as _np  # noqa: F401
 except ImportError:
     pass
 
@@ -281,7 +281,7 @@ del BoolStorageBase
 
 import torch.cuda
 import torch.autograd
-from torch.autograd import no_grad, enable_grad, set_grad_enabled
+from torch.autograd import no_grad, enable_grad, set_grad_enabled  # noqa: F401
 import torch.nn
 import torch.optim
 import torch.multiprocessing
@@ -309,7 +309,7 @@ def compiled_with_cxx11_abi():
 
 
 # Import the ops "namespace"
-from torch._ops import ops
+from torch._ops import ops  # noqa: F401
 
 # Import the quasi random sampler
 import torch.quasirandom

torch/_six.py

@@ -53,9 +53,9 @@ else:
 
 
 if PY2:
-    import Queue as queue
+    import Queue as queue  # noqa: F401
 else:
-    import queue
+    import queue  # noqa: F401
 
 
 def with_metaclass(meta, *bases):

torch/_tensor_str.py

@@ -1,8 +1,6 @@
 import math
 import torch
-from functools import reduce
-from sys import float_info
-from torch._six import inf, nan
+from torch._six import inf
 
 
 class __PrinterOptions(object):

torch/_thnn/utils.py

@@ -1,7 +1,3 @@
-import os
-import itertools
-import importlib
-
 try:
     # when compiling a cffi extension, this works. When compiling
     # torch itself, it doesn't work because the parent module can't

torch/autograd/__init__.py

@@ -8,11 +8,11 @@ import torch
 import warnings
 
 from .variable import Variable
-from .function import Function, NestedIOFunction
-from .gradcheck import gradcheck, gradgradcheck
-from .grad_mode import no_grad, enable_grad, set_grad_enabled
-from .anomaly_mode import detect_anomaly, set_detect_anomaly
-from . import profiler
+from .function import Function, NestedIOFunction  # noqa: F401
+from .gradcheck import gradcheck, gradgradcheck  # noqa: F401
+from .grad_mode import no_grad, enable_grad, set_grad_enabled  # noqa: F401
+from .anomaly_mode import detect_anomaly, set_detect_anomaly  # noqa: F401
+from . import profiler  # noqa: F401
 
 __all__ = ['Variable', 'Function', 'backward', 'grad_mode']
 

torch/autograd/_functions/__init__.py

@@ -1 +1 @@
-from .tensor import *
+from .tensor import *  # noqa: F401

torch/autograd/_functions/utils.py

@@ -1,4 +1,3 @@
-import torch
 from functools import reduce
 
 

torch/autograd/gradcheck.py

@@ -1,7 +1,6 @@
 import torch
 from torch._six import container_abcs, istuple
 import torch.testing
-import sys
 from itertools import product
 import warnings
 

torch/autograd/profiler.py

@@ -1,12 +1,7 @@
-import subprocess
-import re
-import os
-import sys
 import itertools
 from collections import defaultdict, namedtuple
 
 import torch
-from torch._six import FileNotFoundError
 
 
 class range(object):

torch/cuda/__init__.py

@@ -648,7 +648,7 @@ torch._storage_classes.add(ByteStorage)
 torch._storage_classes.add(HalfStorage)
 torch._storage_classes.add(BoolStorage)
 
-from . import sparse
-from . import profiler
-from . import nvtx
-from .streams import Stream, Event
+from . import sparse  # noqa: F401
+from . import profiler  # noqa: F401
+from . import nvtx  # noqa: F401
+from .streams import Stream, Event  # noqa: F401

torch/cuda/comm.py

@@ -1,8 +1,7 @@
 import torch
 from . import nccl
-from torch._utils import _accumulate, _take_tensors, _flatten_dense_tensors, \
-    _flatten_sparse_tensors, _unflatten_dense_tensors, \
-    _unflatten_sparse_tensors, _reorder_tensors_as
+from torch._utils import _take_tensors, _flatten_dense_tensors, \
+    _unflatten_dense_tensors, _reorder_tensors_as
 
 
 def broadcast(tensor, devices):

torch/distributed/__init__.py

@@ -10,8 +10,8 @@ if is_available() and not torch._C._c10d_init():
 
 
 if is_available():
-    from .distributed_c10d import *
+    from .distributed_c10d import *  # noqa: F401
     # Variables prefixed with underscore are not auto imported
     # See the comment in `distributed_c10d.py` above `_backend` on why we expose
     # this.
-    from .distributed_c10d import _backend
+    from .distributed_c10d import _backend  # noqa: F401

torch/distributed/distributed_c10d.py

@@ -3,7 +3,10 @@ import warnings
 from torch._six import string_classes
 from datetime import timedelta
 
-from .rendezvous import rendezvous, register_rendezvous_handler
+# This module is wildcard imported from torch.distributed.
+# TODO: specify __all__
+
+from .rendezvous import rendezvous, register_rendezvous_handler  # noqa: F401
 from . import BroadcastOptions, AllreduceOptions, ReduceOptions, \
     ScatterOptions, GatherOptions
 from . import ReduceOp

torch/distributed/launch.py

@@ -140,11 +140,8 @@ will not pass ``--local_rank`` when you specify this flag.
 import sys
 import subprocess
 import os
-import socket
 from argparse import ArgumentParser, REMAINDER
 
-import torch
-
 
 def parse_args():
     """

torch/distributions/__init__.py

@@ -124,6 +124,8 @@ __all__ = [
     'Gamma',
     'Geometric',
     'Gumbel',
+    'HalfCauchy',
+    'HalfNormal',
     'Independent',
     'Laplace',
     'LogNormal',

torch/distributions/categorical.py

@@ -2,7 +2,7 @@ import torch
 from torch._six import nan
 from torch.distributions import constraints
 from torch.distributions.distribution import Distribution
-from torch.distributions.utils import probs_to_logits, logits_to_probs, lazy_property, broadcast_all
+from torch.distributions.utils import probs_to_logits, logits_to_probs, lazy_property
 
 
 class Categorical(Distribution):

torch/distributions/chi2.py

@@ -1,4 +1,3 @@
-import torch
 from torch.distributions import constraints
 from torch.distributions.gamma import Gamma
 

torch/distributions/fishersnedecor.py

@@ -1,6 +1,5 @@
 from numbers import Number
 import torch
-import math
 from torch._six import nan
 from torch.distributions import constraints
 from torch.distributions.distribution import Distribution

torch/distributions/gamma.py

@@ -3,7 +3,7 @@ from numbers import Number
 import torch
 from torch.distributions import constraints
 from torch.distributions.exp_family import ExponentialFamily
-from torch.distributions.utils import broadcast_all, lazy_property
+from torch.distributions.utils import broadcast_all
 
 
 def _standard_gamma(concentration):

torch/distributions/half_cauchy.py

@@ -1,6 +1,5 @@
 import math
 
-import torch
 from torch._six import inf
 from torch.distributions import constraints
 from torch.distributions.transforms import AbsTransform

torch/distributions/half_normal.py

@@ -1,6 +1,5 @@
 import math
 
-import torch
 from torch._six import inf
 from torch.distributions import constraints
 from torch.distributions.transforms import AbsTransform

torch/distributions/kl.py

@@ -19,7 +19,6 @@ from .gumbel import Gumbel
 from .half_normal import HalfNormal
 from .independent import Independent
 from .laplace import Laplace
-from .logistic_normal import LogisticNormal
 from .lowrank_multivariate_normal import (LowRankMultivariateNormal, _batch_lowrank_logdet,
                                           _batch_lowrank_mahalanobis)
 from .multivariate_normal import (MultivariateNormal, _batch_mahalanobis)

torch/distributions/log_normal.py

@@ -1,4 +1,3 @@
-import torch
 from torch.distributions import constraints
 from torch.distributions.transforms import ExpTransform
 from torch.distributions.normal import Normal

torch/distributions/logistic_normal.py

@@ -2,7 +2,7 @@ import torch
 from torch.distributions import constraints
 from torch.distributions.normal import Normal
 from torch.distributions.transformed_distribution import TransformedDistribution
-from torch.distributions.transforms import ComposeTransform, ExpTransform, StickBreakingTransform
+from torch.distributions.transforms import StickBreakingTransform
 
 
 class LogisticNormal(TransformedDistribution):

torch/distributions/pareto.py

@@ -1,4 +1,3 @@
-import torch
 from torch.distributions import constraints
 from torch.distributions.exponential import Exponential
 from torch.distributions.transformed_distribution import TransformedDistribution

torch/distributions/studentT.py

@@ -1,5 +1,4 @@
 import math
-from numbers import Number
 
 import torch
 from torch._six import inf, nan

torch/distributions/utils.py

@@ -1,6 +1,5 @@
 from functools import update_wrapper
 from numbers import Number
-import math
 import torch
 import torch.nn.functional as F
 

torch/for_onnx/__init__.py

@@ -1 +1 @@
-from .onnx import *
+from .onnx import *  # noqa: F401

torch/hub.py

@@ -2,7 +2,6 @@ import importlib
 import os
 import shutil
 import sys
-import tempfile
 import zipfile
 
 if sys.version_info[0] == 2:
@@ -10,10 +9,7 @@ if sys.version_info[0] == 2:
     from urllib2 import urlopen  # noqa f811
 else:
     from urllib.request import urlopen
-    from urllib.parse import urlparse
-
-import torch
-import torch.utils.model_zoo as model_zoo
+    from urllib.parse import urlparse  # noqa: F401
 
 MASTER_BRANCH = 'master'
 ENV_TORCH_HUB_DIR = 'TORCH_HUB_DIR'

torch/jit/__init__.py

@@ -1,35 +1,31 @@
 import torch._C
-from torch import Tensor
 from torch.autograd import Variable, function
 from torch.serialization import validate_cuda_device
-from torch.nn import Module, ModuleList, ParameterList, Parameter, Sequential
+from torch.nn import Module, ModuleList, Parameter, Sequential
 from torch.jit.frontend import get_jit_class_def, get_jit_def, get_default_args
 import torch.backends.cudnn as cudnn
 import torch.jit.annotations
 import torch._jit_internal as _jit_internal
-from torch._six import raise_from, with_metaclass, get_function_from_type, \
+from torch._six import with_metaclass, get_function_from_type, \
     string_classes
-from torch._jit_internal import ignore
-from torch.jit._pickle import Unpickler
+from torch._jit_internal import ignore  # noqa: F401
+from torch.jit._pickle import Unpickler  # noqa: F401
 from ..nn.modules.utils import _single, _pair, _triple, _quadruple, \
     _list_with_default
 import torch.testing
 
 import math
-from collections import defaultdict, OrderedDict, namedtuple
+from collections import OrderedDict, namedtuple
 import textwrap
 import sys
 import warnings
-import itertools
 import weakref
 import types
 import contextlib
 import os
 import functools
 import copy
-import numbers
 import collections
-import re
 import inspect
 import pickle
 if sys.version_info[0] > 2:

torch/jit/_pickle.py

@@ -1,5 +1,3 @@
-import torch
-import functools
 import pickle
 
 

torch/jit/annotations.py

@@ -1,4 +1,3 @@
-import re
 import sys
 import ast
 import inspect
@@ -181,3 +180,33 @@ def ann_to_type(ann):
     elif ann is str:
         return StringType.get()
     raise ValueError("Unknown type annotation: '{}'".format(ann.__name__))
+
+
+__all__ = [
+    'List',
+    'BroadcastingList1',
+    'BroadcastingList2',
+    'BroadcastingList3',
+    'Tuple',
+    'is_tuple',
+    'is_list',
+    'Dict',
+    'is_dict',
+    'TensorType',
+    'TupleType',
+    'FloatType',
+    'IntType',
+    'ListType',
+    'StringType',
+    'DictType',
+    'Module',
+    # TODO: Consider not exporting these during wildcard import (reserve
+    # that for the types; for idiomatic typing code.)
+    'get_signature',
+    'get_num_params',
+    'parse_type_line',
+    'get_type_line',
+    'split_type_line',
+    'try_real_annotations',
+    'ann_to_type',
+]

torch/jit/frontend.py

@@ -5,8 +5,6 @@ import ast
 import inspect
 import string
 from textwrap import dedent
-from functools import partial
-from collections import namedtuple
 from torch._six import PY2
 from torch._C._jit_tree_views import *
 

torch/jit/quantized.py

@@ -1,11 +1,7 @@
 import torch
-import copy
-import numbers
-from typing import Tuple, Optional
+from typing import Tuple, Optional  # noqa: F401
 from torch import Tensor
-from torch.jit import ScriptModule
 
-from torch.nn.utils.rnn import PackedSequence
 from torch.nn import _VF
 
 

torch/multiprocessing/__init__.py

@@ -22,7 +22,7 @@ __all__ = ['set_sharing_strategy', 'get_sharing_strategy',
            'get_all_sharing_strategies']
 
 
-from multiprocessing import *
+from multiprocessing import *  # noqa: F401
 
 
 __all__ += multiprocessing.__all__
@@ -36,13 +36,13 @@ torch._C._multiprocessing_init()
 if sys.version_info < (3, 3):
     """Override basic classes in Python 2.7 and Python 3.3 to use ForkingPickler
     for serialization. Later versions of Python already use ForkingPickler."""
-    from .queue import Queue, SimpleQueue
-    from .pool import Pool
+    from .queue import Queue, SimpleQueue  # noqa: F401
+    from .pool import Pool  # noqa: F401
 
 
 """Add helper function to spawn N processes and wait for completion of any of
 them. This depends `mp.get_context` which was added in Python 3.4."""
-from .spawn import spawn, SpawnContext
+from .spawn import spawn, SpawnContext  # noqa: F401
 
 
 if sys.platform == 'darwin' or sys.platform == 'win32':

torch/multiprocessing/reductions.py

@@ -1,7 +1,6 @@
 import torch
 import torch.utils.hooks
 import os
-import weakref
 import threading
 import multiprocessing
 from multiprocessing.reduction import ForkingPickler