update logging

examples/FasterRCNN/data.py

@@ -52,7 +52,7 @@ def print_class_histogram(roidbs):
     data = list(itertools.chain(*[[class_names[i + 1], v] for i, v in enumerate(gt_hist[1:])]))
     COL = min(6, len(data))
     total_instances = sum(data[1::2])
-    data.extend([None] * (COL - len(data) % COL))
+    data.extend([None] * ((COL - len(data) % COL) % COL))
     data.extend(["total", total_instances])
     data = itertools.zip_longest(*[data[i::COL] for i in range(COL)])
     # the first line is BG

tensorpack/models/batch_norm.py

@@ -11,7 +11,7 @@ from ..tfutils.collection import backup_collection, restore_collection
 from ..tfutils.common import get_tf_version_tuple
 from ..tfutils.tower import get_current_tower_context
 from ..utils import logger
-from ..utils.argtools import get_data_format
+from ..utils.argtools import get_data_format, log_once
 from ..utils.develop import log_deprecated
 from .common import VariableHolder, layer_register
 from .tflayer import convert_to_tflayer_args, rename_get_variable
@@ -216,7 +216,7 @@ def BatchNorm(inputs, axis=None, training=None, momentum=0.9, epsilon=1e-5,
         assert TF_version >= (1, 4), \
             "Fine tuning a BatchNorm model with fixed statistics needs TF>=1.4!"
         if ctx.is_main_training_tower:  # only warn in first tower
-            logger.warn("[BatchNorm] Using moving_mean/moving_variance in training.")
+            log_once("Some BatchNorm layer uses moving_mean/moving_variance in training.", func='warn')
         # Using moving_mean/moving_variance in training, which means we
         # loaded a pre-trained BN and only fine-tuning the affine part.
 

tensorpack/utils/utils.py

@@ -261,7 +261,7 @@ def find_library_full_path(name):
                     if 'lib' + name + '.so' in basename:
                         if os.path.isfile(sofile):
                             return os.path.realpath(sofile)
-        except PermissionError:
+        except (OSError, IOError):
             # can fail in certain environment (e.g. chroot)
             # if the pids are incorrectly mapped
             pass