更换文档检测模型

paddle_detection/ppdet/data/shm_utils.py

@@ -0,0 +1,70 @@
+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+SIZE_UNIT = ['K', 'M', 'G', 'T']
+SHM_QUERY_CMD = 'df -h'
+SHM_KEY = 'shm'
+SHM_DEFAULT_MOUNT = '/dev/shm'
+
+# [ shared memory size check ]
+# In detection models, image/target data occupies a lot of memory, and
+# will occupy lots of shared memory in multi-process DataLoader, we use
+# following code to get shared memory size and perform a size check to
+# disable shared memory use if shared memory size is not enough.
+# Shared memory getting process as follows:
+# 1. use `df -h` get all mount info
+# 2. pick up spaces whose mount info contains 'shm'
+# 3. if 'shm' space number is only 1, return its size
+# 4. if there are multiple 'shm' space, try to find the default mount
+#    directory '/dev/shm' is Linux-like system, otherwise return the
+#    biggest space size.
+
+
+def _parse_size_in_M(size_str):
+    if size_str[-1] == 'B':
+        num, unit = size_str[:-2], size_str[-2]
+    else:
+        num, unit = size_str[:-1], size_str[-1]
+    assert unit in SIZE_UNIT, \
+            "unknown shm size unit {}".format(unit)
+    return float(num) * \
+            (1024 ** (SIZE_UNIT.index(unit) - 1))
+
+
+def _get_shared_memory_size_in_M():
+    try:
+        df_infos = os.popen(SHM_QUERY_CMD).readlines()
+    except:
+        return None
+    else:
+        shm_infos = []
+        for df_info in df_infos:
+            info = df_info.strip()
+            if info.find(SHM_KEY) >= 0:
+                shm_infos.append(info.split())
+
+        if len(shm_infos) == 0:
+            return None
+        elif len(shm_infos) == 1:
+            return _parse_size_in_M(shm_infos[0][3])
+        else:
+            default_mount_infos = [
+                si for si in shm_infos if si[-1] == SHM_DEFAULT_MOUNT
+            ]
+            if default_mount_infos:
+                return _parse_size_in_M(default_mount_infos[0][3])
+            else:
+                return max([_parse_size_in_M(si[3]) for si in shm_infos])