Remove unused six code for Python 2/3 compatibility (pytorch#48077)

Summary:
This is basically a reborn version of pytorch#45254 .

Ref: pytorch#42919

Pull Request resolved: pytorch#48077

Reviewed By: ngimel

Differential Revision: D25687042

Pulled By: bugra

fbshipit-source-id: 05f20a6f3c5212f73d0b1505b493b720e6cf74e5

Author: skyline75489

benchmarks/distributed/ddp/benchmark.py

@@ -26,10 +26,6 @@
 import torchvision
 
 
-if not torch._six.PY3:
-    raise RuntimeError("DDP benchmark requires Python 3")
-
-
 def allgather_object(obj):
     buffer = io.BytesIO()
     torch.save(obj, buffer)

benchmarks/distributed/ddp/diff.py

@@ -9,10 +9,6 @@
 import numpy as np
 
 
-if not torch._six.PY3:
-    raise RuntimeError("DDP benchmark requires Python 3")
-
-
 def load(path):
     with open(path, 'r') as f:
         return json.load(f)

caffe2/contrib/tensorboard/tensorboard_exporter.py

@@ -7,7 +7,6 @@
 import copy
 import logging
 import os
-import six
 
 from caffe2.proto import caffe2_pb2
 from caffe2.python import core, workspace
@@ -93,7 +92,7 @@ def _get_blob_names(ops):
 
 
 def _remap_keys(m, f):
-    m2 = {f(key): value for key, value in six.iteritems(m)}
+    m2 = {f(key): value for key, value in m.items()}
     m.clear()
     m.update(m2)
 

caffe2/python/context.py

@@ -3,7 +3,7 @@
 
 import inspect
 import threading
-import six
+import functools
 
 
 class _ContextInfo(object):
@@ -91,7 +91,7 @@ def __exit__(self, *args):
             _context_registry().get(cls).exit(self)
 
     def __call__(self, func):
-        @six.wraps(func)
+        @functools.wraps(func)
         def wrapper(*args, **kwargs):
             with self:
                 return func(*args, **kwargs)

caffe2/python/experiment_util.py

@@ -10,7 +10,6 @@
 import logging
 import socket
 import abc
-import six
 
 from collections import OrderedDict
 from future.utils import viewkeys, viewvalues
@@ -26,7 +25,7 @@
 
 
 class ExternalLogger(object):
-    six.add_metaclass(abc.ABCMeta)
+    __metaclass__ = abc.ABCMeta
 
     @abc.abstractmethod
     def set_runtime_args(self, runtime_args):

caffe2/python/hypothesis_test_util.py

@@ -50,7 +50,6 @@
 import logging
 import numpy as np
 import os
-import six
 import struct
 
 
@@ -748,5 +747,5 @@ def assertRunOpRaises(
             if regexp is None:
                 self.assertRaises(exception, workspace.RunOperatorOnce, op)
             else:
-                six.assertRaisesRegex(
-                    self, exception, regexp, workspace.RunOperatorOnce, op)
+                self.assertRaisesRegex(
+                    exception, regexp, workspace.RunOperatorOnce, op)

caffe2/python/layer_model_helper.py

@@ -22,7 +22,6 @@
 
 import logging
 import numpy as np
-import six
 import copy
 logger = logging.getLogger(__name__)
 
@@ -125,7 +124,7 @@ def filter_metrics_schema(self, white_set):
 
     def add_ad_hoc_plot_blob(self, blob, dtype=None):
         assert isinstance(
-            blob, (six.string_types, core.BlobReference)
+            blob, (str, core.BlobReference)
         ), "expect type str or BlobReference, but got {}".format(type(blob))
         dtype = dtype or (np.float, (1, ))
         self.add_metric_field(str(blob), schema.Scalar(dtype, blob))
@@ -173,7 +172,7 @@ def initializer(blob_name):
     def add_global_constant(
         self, name, array=None, dtype=None, initializer=None
     ):
-        assert isinstance(name, six.string_types), (
+        assert isinstance(name, str), (
             'name should be a string as we are using it as map key')
         # This is global namescope for constants. They will be created in all
         # init_nets and there should be very few of them.
@@ -310,7 +309,7 @@ def create_param(self, param_name, shape, initializer, optimizer=None,
                      ps_param=None, regularizer=None):
         if isinstance(param_name, core.BlobReference):
             param_name = str(param_name)
-        elif isinstance(param_name, six.string_types):
+        elif isinstance(param_name, str):
             # Parameter name will be equal to current Namescope that got
             # resolved with the respect of parameter sharing of the scopes.
             param_name = parameter_sharing_context.get_parameter_name(
@@ -750,6 +749,6 @@ def breakdown_map(self, breakdown_map):
         # TODO(xlwang): provide more rich feature information in breakdown_map;
         # and change the assertion accordingly
         assert isinstance(breakdown_map, dict)
-        assert all(isinstance(k, six.string_types) for k in breakdown_map)
+        assert all(isinstance(k, str) for k in breakdown_map)
         assert sorted(breakdown_map.values()) == list(range(len(breakdown_map)))
         self._breakdown_map = breakdown_map

caffe2/python/layer_parameter_sharing_test.py

@@ -9,7 +9,6 @@
 )
 from caffe2.python.optimizer import AdagradOptimizer, AdamOptimizer
 from caffe2.python.layer_test_util import LayersTestCase
-import six
 
 
 class ParameterSharingTest(LayersTestCase):
@@ -116,7 +115,7 @@ def test_layer_shared_parameter_name_different_shapes(self):
                 self.assertEquals(self.model.layers[-1].w,
                                   'global_scope/fc/w')
 
-                with six.assertRaisesRegex(self, ValueError, 'Got inconsistent shapes .*'):
+                with self.assertRaisesRegex(ValueError, 'Got inconsistent shapes .*'):
                     self.model.FC(
                         self.model.input_feature_schema.float_features,
                         output_dims + 1

caffe2/python/layers/functional.py

@@ -11,7 +11,6 @@
 )
 import caffe2.proto.caffe2_pb2 as caffe2_pb2
 import numpy as np
-import six
 import logging
 
 logger = logging.getLogger(__name__)
@@ -31,7 +30,7 @@ def __init__(self, model, input_record, output_names_or_num, function,
         self._kwargs = kwargs
         return_struct = (
             isinstance(output_names_or_num, list) or
-            (isinstance(output_names_or_num, six.integer_types) and
+            (isinstance(output_names_or_num, int) and
              output_names_or_num != 1)
         )
 

caffe2/python/layers/sampling_trainable_mixin.py

@@ -6,10 +6,9 @@
 
 
 import abc
-import six
 
 
-class SamplingTrainableMixin(six.with_metaclass(abc.ABCMeta, object)):
+class SamplingTrainableMixin(metaclass=abc.ABCMeta):
 
     def __init__(self, *args, **kwargs):
         super(SamplingTrainableMixin, self).__init__(*args, **kwargs)

caffe2/python/layers/tags.py

@@ -5,7 +5,7 @@
 
 
 
-import six
+import functools
 
 from caffe2.python import context
 
@@ -104,7 +104,7 @@ def __exit__(self, type, value, traceback):
         TagContext.current().remove_tags(self.tags)
 
     def __call__(self, func):
-        @six.wraps(func)
+        @functools.wraps(func)
         def wrapper(*args, **kwargs):
             with self:
                 return func(*args, **kwargs)

caffe2/python/model_helper.py

@@ -21,7 +21,6 @@
 from itertools import chain
 
 import logging
-import six
 
 
 # _known_working_ops are operators that do not need special care.
@@ -199,7 +198,7 @@ def create_param(self, param_name, shape, initializer, tags=None):
         # ParameterSharing will be applied.
         if isinstance(param_name, core.BlobReference):
             param_name = str(param_name)
-        elif isinstance(param_name, six.string_types):
+        elif isinstance(param_name, str):
             # Parameter name will be equal to current Namescope that got
             # resolved with the respect of parameter sharing of the scopes.
             param_name = parameter_sharing_context.get_parameter_name(

caffe2/python/modeling/initializers.py

@@ -6,8 +6,6 @@
 from caffe2.python.core import DataType, BlobReference, ScopedBlobReference
 from caffe2.python.modeling.parameter_info import ParameterInfo
 
-import six
-
 
 class Initializer(object):
     '''
@@ -47,7 +45,7 @@ class ExternalInitializer(object):
     def create_param(self, param_name, init_net, shape):
         if isinstance(param_name, BlobReference):
             param = BlobReference(str(param_name), init_net)
-        elif isinstance(param_name, six.string_types):
+        elif isinstance(param_name, str):
             param = ScopedBlobReference(param_name, init_net)
         else:
             raise TypeError("Unsupported type for param_name")

caffe2/python/modeling/net_modifier.py

@@ -4,10 +4,9 @@
 
 
 import abc
-import six
 
 
-class NetModifier(six.with_metaclass(abc.ABCMeta, object)):
+class NetModifier(metaclass=abc.ABCMeta):
     """
     An abstraction class for supporting modifying a generated net.
     Inherited classes should implement the modify_net method where

caffe2/python/onnx/tests/c2_ref_test.py

@@ -8,7 +8,6 @@
 
 import json
 import os
-import six
 import unittest
 
 from caffe2.python import core
@@ -44,9 +43,8 @@ def test_check_arguments(self):
         b2.convert_node(node_def.SerializeToString())
 
         bad_node_def = make_node("Add", inputs=["X", "Y"], outputs=["Z"], foo=42, bar=56)
-        with six.assertRaisesRegex(self,
-                                   RuntimeError,
-                                   "Don't know how to map unexpected argument (foo|bar)"):
+        with self.assertRaisesRegex(RuntimeError,
+                                    "Don't know how to map unexpected argument (foo|bar)"):
             b2.convert_node(bad_node_def.SerializeToString())
 
     def test_dynamicslice_3inputs_graph(self):

caffe2/python/onnx/tests/conversion_test.py

@@ -6,7 +6,6 @@
 
 
 import json
-import six
 import tempfile
 import textwrap
 import traceback
@@ -82,9 +81,9 @@ def test_caffe2_to_onnx_value_info(self):
         caffe2_net.flush()
 
         args = [caffe2_net.name, '--output', output.name]
-        six.assertRaisesRegex(self, Exception,
-                              'value info',
-                              self._run_command, caffe2_to_onnx, args)
+        self.assertRaisesRegex(Exception,
+                               'value info',
+                               self._run_command, caffe2_to_onnx, args)
 
         args.extend([
             '--value-info',

caffe2/python/operator_test/image_input_op_test.py

@@ -13,7 +13,7 @@
 from PIL import Image
 import numpy as np
 import shutil
-import six
+import io
 import sys
 import tempfile
 
@@ -134,7 +134,7 @@ def create_test(output_dir, width, height, default_bound, minsize, crop, means,
             img_array = np.random.random_integers(
                 0, 255, [height, width, 3]).astype(np.uint8)
             img_obj = Image.fromarray(img_array)
-            img_str = six.BytesIO()
+            img_str = io.BytesIO()
             img_obj.save(img_str, 'PNG')
 
             # Create a random bounding box for every other image

caffe2/python/operator_test/reshape_ops_test.py

@@ -3,7 +3,6 @@
 
 
 import numpy as np
-import six
 from numpy.testing import assert_array_equal
 
 from caffe2.python import core, workspace

caffe2/python/operator_test/utility_ops_test.py

@@ -11,7 +11,6 @@
 import hypothesis.strategies as st
 import numpy as np
 import random
-import six
 
 
 class TestUtilityOps(serial.SerializedTestCase):
@@ -474,7 +473,7 @@ def test_range(self, gc, dc):
             names[len(inputs) - 1],
             ["Y"]
         )
-        with six.assertRaisesRegex(self, RuntimeError, 'Step size cannot be 0'):
+        with self.assertRaisesRegex(RuntimeError, 'Step size cannot be 0'):
             self.assertReferenceChecks(
                 device_option=gc,
                 op=op,

caffe2/python/parallel_workers.py

@@ -38,7 +38,6 @@
 import atexit
 import time
 import collections
-import six
 import traceback
 
 from abc import ABCMeta, abstractmethod
@@ -110,7 +109,7 @@ def put_metric(self, key, value, count=True):
 
 
 class State():
-    six.add_metaclass(ABCMeta)
+    __metaclass__ = ABCMeta
 
     @abstractmethod
     def start(self):

caffe2/python/python_op_test.py

@@ -8,7 +8,6 @@
 from hypothesis import given, settings
 import hypothesis.strategies as st
 import numpy as np
-import six
 
 
 class CustomError(Exception):
@@ -55,12 +54,12 @@ def f(inputs, _):
 
     def test_exception(self):
         op = CreatePythonOperator(MainOpFunctionThatThrowsCustomError, [], [])
-        with six.assertRaisesRegex(self, CustomError, "This is an intentional exception."):
+        with self.assertRaisesRegex(CustomError, "This is an intentional exception."):
             workspace.RunOperatorOnce(op)
 
     def test_exception_builder(self):
         op = CreatePythonOperator(MainOpFunctionThatThrowsCustomErrorInBuilder, [], [])
-        with six.assertRaisesRegex(self, CustomError, "This is an intentional exception in builder."):
+        with self.assertRaisesRegex(CustomError, "This is an intentional exception in builder."):
             workspace.RunOperatorOnce(op)
 
     @given(x=hu.tensor())

caffe2/python/rnn_cell.py

@@ -11,7 +11,6 @@
 import logging
 import numpy as np
 import random
-import six
 from future.utils import viewkeys
 
 from caffe2.proto import caffe2_pb2
@@ -32,7 +31,7 @@
 def _RectifyName(blob_reference_or_name):
     if blob_reference_or_name is None:
         return None
-    if isinstance(blob_reference_or_name, six.string_types):
+    if isinstance(blob_reference_or_name, str):
         return core.ScopedBlobReference(blob_reference_or_name)
     if not isinstance(blob_reference_or_name, core.BlobReference):
         raise Exception("Unknown blob reference type")