Add support for Python 2 (#11)

* Add missing __init__.py files

* Add packages

* Rename logging.py to logger.py

Import rules from Python2 makes this a bad idea

* Make import_file py2 compatible

* list does not have .copy() in py2

* math.log2 does not exist in py2

* Miscellaneous fixes for py2

* Address comments

.gitignore

@@ -3,7 +3,7 @@ __pycache__
 _ext
 *.pyc
 *.so
-maskrcnn-benchmark.egg-info/
+maskrcnn_benchmark.egg-info/
 build/
 dist/
 

maskrcnn_benchmark/__init__.py

@@ -0,0 +1 @@
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.

maskrcnn_benchmark/data/build.py

@@ -1,5 +1,6 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
 import bisect
+import copy
 import logging
 
 import torch.utils.data
@@ -63,7 +64,8 @@ def make_data_sampler(dataset, shuffle, distributed):
 
 
 def _quantize(x, bins):
-    bins = sorted(bins.copy())
+    bins = copy.copy(bins)
+    bins = sorted(bins)
     quantized = list(map(lambda y: bisect.bisect_right(bins, y), x))
     return quantized
 

maskrcnn_benchmark/engine/__init__.py

@@ -0,0 +1 @@
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.

maskrcnn_benchmark/modeling/poolers.py

@@ -1,5 +1,4 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
-import math
 import torch
 import torch.nn.functional as F
 from torch import nn
@@ -57,7 +56,7 @@ def __init__(self, output_size, scales, sampling_ratio):
         """
         Arguments:
             output_size (list[tuple[int]] or list[int]): output size for the pooled region
-            scales (list[flaot]): scales for each Pooler
+            scales (list[float]): scales for each Pooler
             sampling_ratio (int): sampling ratio for ROIAlign
         """
         super(Pooler, self).__init__()
@@ -72,8 +71,8 @@ def __init__(self, output_size, scales, sampling_ratio):
         self.output_size = output_size
         # get the levels in the feature map by leveraging the fact that the network always
         # downsamples by a factor of 2 at each level.
-        lvl_min = -math.log2(scales[0])
-        lvl_max = -math.log2(scales[-1])
+        lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item()
+        lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item()
         self.map_levels = LevelMapper(lvl_min, lvl_max)
 
     def convert_to_roi_format(self, boxes):

maskrcnn_benchmark/structures/image_list.py

@@ -1,4 +1,6 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
+from __future__ import division
+
 import torch
 
 

maskrcnn_benchmark/utils/c2_model_loading.py

@@ -119,7 +119,10 @@ def _rename_weights_for_resnet(weights, stage_names):
 
 def _load_c2_pickled_weights(file_path):
     with open(file_path, "rb") as f:
-        data = pickle.load(f, encoding="latin1")
+        if torch._six.PY3:
+            data = pickle.load(f, encoding="latin1")
+        else:
+            data = pickle.load(f)
     if "blobs" in data:
         weights = data["blobs"]
     else:

maskrcnn_benchmark/utils/imports.py

@@ -1,14 +1,23 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
-import importlib
-import importlib.util
-import sys
-
-
-# from https://stackoverflow.com/questions/67631/how-to-import-a-module-given-the-full-path?utm_medium=organic&utm_source=google_rich_qa&utm_campaign=google_rich_qa
-def import_file(module_name, file_path, make_importable=False):
-    spec = importlib.util.spec_from_file_location(module_name, file_path)
-    module = importlib.util.module_from_spec(spec)
-    spec.loader.exec_module(module)
-    if make_importable:
-        sys.modules[module_name] = module
-    return module
+import torch
+
+if torch._six.PY3:
+    import importlib
+    import importlib.util
+    import sys
+
+
+    # from https://stackoverflow.com/questions/67631/how-to-import-a-module-given-the-full-path?utm_medium=organic&utm_source=google_rich_qa&utm_campaign=google_rich_qa
+    def import_file(module_name, file_path, make_importable=False):
+        spec = importlib.util.spec_from_file_location(module_name, file_path)
+        module = importlib.util.module_from_spec(spec)
+        spec.loader.exec_module(module)
+        if make_importable:
+            sys.modules[module_name] = module
+        return module
+else:
+    import imp
+
+    def import_file(module_name, file_path, make_importable=None):
+        module = imp.load_source(module_name, file_path)
+        return module

setup.py

@@ -62,7 +62,7 @@ def get_extensions():
     author="fmassa",
     url="https://github.com/facebookresearch/maskrnn-benchmark",
     description="object detection in pytorch",
-    # packages=find_packages(exclude=("configs", "examples", "test",)),
+    packages=find_packages(exclude=("configs", "tests",)),
     # install_requires=requirements,
     ext_modules=get_extensions(),
     cmdclass={"build_ext": torch.utils.cpp_extension.BuildExtension},

tools/test_net.py

@@ -14,7 +14,7 @@
 from maskrcnn_benchmark.utils.checkpoint import DetectronCheckpointer
 from maskrcnn_benchmark.utils.collect_env import collect_env_info
 from maskrcnn_benchmark.utils.comm import synchronize
-from maskrcnn_benchmark.utils.logging import setup_logger
+from maskrcnn_benchmark.utils.logger import setup_logger
 from maskrcnn_benchmark.utils.miscellaneous import mkdir
 
 

tools/train_net.py

@@ -22,7 +22,7 @@
 from maskrcnn_benchmark.utils.collect_env import collect_env_info
 from maskrcnn_benchmark.utils.comm import synchronize
 from maskrcnn_benchmark.utils.imports import import_file
-from maskrcnn_benchmark.utils.logging import setup_logger
+from maskrcnn_benchmark.utils.logger import setup_logger
 from maskrcnn_benchmark.utils.miscellaneous import mkdir