Nigel
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

!16426 Change the permission of cache shared memory to 600 for security 

From: @lixiachen
Reviewed-by: @robingrosman,@pandoublefeng
Signed-off-by: @robingrosman
This commit is contained in:
mindspore-ci-bot 2021-05-20 02:36:26 +08:00 committed by Gitee
parent 24db2c20ae 8812111f94
commit 05bbd1d8fa
18 changed files with 104 additions and 28 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
mindspore/ccsrc/minddata/dataset/engine/cache/cache_admin_arg.cc vendored
View File

@ -529,7 +529,8 @@ Status CacheAdminArgHandler::StopServer(CommandId command_id) {
if (rc.IsError()) {
msg.RemoveResourcesOnExit();
if (rc == StatusCode::kMDNetWorkError) {
std::string errMsg = "Server on port " + std::to_string(port_) + " is not up or has been shutdown already.";
std::string errMsg =
"Server on port " + std::to_string(port_) + " is not reachable or has been shutdown already.";
return Status(StatusCode::kMDNetWorkError, errMsg);
}
return rc;

16
mindspore/ccsrc/minddata/dataset/engine/cache/cache_client.cc vendored
View File

@ -41,15 +41,15 @@ Status CacheClient::Builder::Build(std::shared_ptr<CacheClient> *out) {
}
Status CacheClient::Builder::SanityCheck() {
CHECK_FAIL_RETURN_SYNTAX_ERROR(session_id_ > 0, "session id must be positive");
CHECK_FAIL_RETURN_SYNTAX_ERROR(cache_mem_sz_ >= 0, "cache memory size must not be negative. (0 implies unlimited");
CHECK_FAIL_RETURN_SYNTAX_ERROR(num_connections_ > 0, "rpc connections must be positive");
CHECK_FAIL_RETURN_SYNTAX_ERROR(prefetch_size_ > 0, "prefetch size must be positive");
CHECK_FAIL_RETURN_SYNTAX_ERROR(!hostname_.empty(), "hostname must not be empty");
CHECK_FAIL_RETURN_SYNTAX_ERROR(port_ > 1024, "Port must be in range (1025..65535)");
CHECK_FAIL_RETURN_SYNTAX_ERROR(port_ <= 65535, "Port must be in range (1025..65535)");
CHECK_FAIL_RETURN_SYNTAX_ERROR(session_id_ > 0, "session id must be positive.");
CHECK_FAIL_RETURN_SYNTAX_ERROR(cache_mem_sz_ >= 0, "cache memory size must not be negative (0 implies unlimited).");
CHECK_FAIL_RETURN_SYNTAX_ERROR(num_connections_ > 0, "number of tcp/ip connections must be positive.");
CHECK_FAIL_RETURN_SYNTAX_ERROR(prefetch_size_ > 0, "prefetch size must be positive.");
CHECK_FAIL_RETURN_SYNTAX_ERROR(!hostname_.empty(), "hostname must not be empty.");
CHECK_FAIL_RETURN_SYNTAX_ERROR(port_ > 1024, "Port must be in range (1025..65535).");
CHECK_FAIL_RETURN_SYNTAX_ERROR(port_ <= 65535, "Port must be in range (1025..65535).");
CHECK_FAIL_RETURN_SYNTAX_ERROR(hostname_ == "127.0.0.1",
"now cache client has to be on the same host with cache server");
"now cache client has to be on the same host with cache server.");
return Status::OK();
}

6
mindspore/ccsrc/minddata/dataset/engine/cache/cache_common.h vendored
View File

@ -73,7 +73,11 @@ inline void Status2CacheReply(const Status &rc, CacheReply *reply) {
/// \param port
/// \return unix socket url
inline std::string PortToUnixSocketPath(int port) {
return kDefaultCommonPath + std::string("/cache_server_p") + std::to_string(port);
#if !defined(_WIN32) && !defined(_WIN64) && !defined(__ANDROID__) && !defined(ANDROID) && !defined(__APPLE__)
return kDefaultCommonPath + Services::GetUserName() + std::string("/cache_server_p") + std::to_string(port);
#else
return kDefaultCommonPath;
#endif
}
/// \brief Round up to the next 4k

4
mindspore/ccsrc/minddata/dataset/engine/cache/cache_ipc.cc vendored
View File

@ -42,7 +42,7 @@ SharedMessage::~SharedMessage() {
Status SharedMessage::Create() {
CHECK_FAIL_RETURN_UNEXPECTED(msg_qid_ == -1, "Message queue already created");
auto access_mode = S_IRUSR | S_IWUSR | S_IROTH | S_IWOTH | S_IRGRP | S_IWGRP;
auto access_mode = S_IRUSR | S_IWUSR;
msg_qid_ = msgget(IPC_PRIVATE, IPC_CREAT | IPC_EXCL | access_mode);
if (msg_qid_ == -1) {
std::string errMsg = "Unable to create a message queue. Errno = " + std::to_string(errno);
@ -99,7 +99,7 @@ SharedMemory::~SharedMemory() {
}
Status SharedMemory::Create(int64_t sz) {
auto access_mode = S_IRUSR | S_IWUSR | S_IROTH | S_IWOTH | S_IRGRP | S_IWGRP;
auto access_mode = S_IRUSR | S_IWUSR;
shm_id_ = shmget(shm_key_, sz, IPC_CREAT | IPC_EXCL | access_mode);
if (shm_id_ == -1) {
RETURN_STATUS_UNEXPECTED("Shared memory creation failed. Errno " + std::to_string(errno));

1
mindspore/ccsrc/minddata/dataset/engine/datasetops/dataset_op.cc
View File

@ -374,6 +374,7 @@ uint32_t DatasetOp::GenerateCRC(const std::shared_ptr<DatasetOp> &op) {
std::string ss_str = ss.str();
// Filter out the Num workers field when generating the check sum
ss_str = std::regex_replace(ss_str, std::regex("Number of ShardReader workers.*\n"), "");
ss_str = std::regex_replace(ss_str, std::regex("Num workers.*\n"), "");
ss_str = std::regex_replace(ss_str, std::regex("\\[workers.*?\\]"), "");
ss_str = std::regex_replace(ss_str, std::regex("Connector queue size.*\n"), "");

5
mindspore/dataset/core/validator_helpers.py
View File

@ -129,6 +129,11 @@ def check_uint32(value, arg_name=""):
check_value(value, [UINT32_MIN, UINT32_MAX])
def check_pos_uint32(value, arg_name=""):
type_check(value, (int,), arg_name)
check_value(value, [POS_INT_MIN, UINT32_MAX])
def check_pos_int32(value, arg_name=""):
type_check(value, (int,), arg_name)
check_value(value, [POS_INT_MIN, INT32_MAX], arg_name)

9
mindspore/dataset/engine/cache_client.py
View File

@ -18,7 +18,8 @@
import copy
from mindspore._c_dataengine import CacheClient
from ..core.validator_helpers import type_check, check_uint32, check_uint64, check_positive, check_value
from ..core.validator_helpers import type_check, check_pos_int32, check_pos_uint32, check_uint64, check_positive, \
check_value
class DatasetCache:
@ -50,7 +51,7 @@ class DatasetCache:
def __init__(self, session_id, size=0, spilling=False, hostname=None, port=None, num_connections=None,
prefetch_size=None):
check_uint32(session_id, "session_id")
check_pos_uint32(session_id, "session_id")
type_check(size, (int,), "size")
if size != 0:
check_positive(size, "size")
@ -62,9 +63,9 @@ class DatasetCache:
type_check(port, (int,), "port")
check_value(port, (1025, 65535), "port")
if num_connections is not None:
check_uint32(num_connections, "num_connections")
check_pos_int32(num_connections, "num_connections")
if prefetch_size is not None:
check_uint32(prefetch_size, "prefetch_size")
check_pos_int32(prefetch_size, "prefetch_size")
self.session_id = session_id
self.size = size

6
model_zoo/official/cv/mobilenetv2/scripts/cache_util.sh
View File

@ -1,4 +1,4 @@
#!/usr/bin/env bash
#!/bin/bash
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
@ -42,8 +42,8 @@ shutdown_cache_server()
result=$(cache_admin --stop 2>&1)
rc=$?
echo "${result}"
if [ "${rc}" -ne 0 ] && [[ ! ${result} =~ "Server on port 50052 is not up or has been shutdown already" ]]; then
if [ "${rc}" -ne 0 ] && [[ ! ${result} =~ "Server on port 50052 is not reachable or has been shutdown already" ]]; then
echo "cache_admin command failure!" "${result}"
exit 1
fi
}
}

3
model_zoo/official/cv/mobilenetv2/scripts/run_train_nfs_cache.sh
View File

@ -92,6 +92,7 @@ run_ascend()
&> log$i.log &
cd ..
done
echo -e "\nWhen training run is done, remember to shut down the cache server via \"cache_admin --stop\""
}
run_gpu()
@ -149,6 +150,7 @@ run_gpu()
--enable_cache=True \
--cache_session_id=$CACHE_SESSION_ID \
&> ../train.log & # dataset train folder
echo -e "\nWhen training run is done, remember to shut down the cache server via \"cache_admin --stop\""
}
run_cpu()
@ -198,6 +200,7 @@ run_cpu()
--enable_cache=True \
--cache_session_id=$CACHE_SESSION_ID \
&> ../train.log & # dataset train folder
echo -e "\nWhen training run is done, remember to shut down the cache server via \"cache_admin --stop\""
}
if [ $1 = "Ascend" ] ; then

3
model_zoo/official/cv/mobilenetv2/train.py
View File

@ -131,3 +131,6 @@ if __name__ == '__main__':
if (epoch + 1) % config.save_checkpoint_epochs == 0:
save_checkpoint(net, os.path.join(save_ckpt_path, f"mobilenetv2_{epoch+1}.ckpt"))
print("total cost {:5.4f} s".format(time.time() - start))
if args_opt.enable_cache:
print("Remember to shut down the cache server via \"cache_admin --stop\"")

6
model_zoo/official/cv/resnet/scripts/cache_util.sh
View File

@ -1,4 +1,4 @@
#!/usr/bin/env bash
#!/bin/bash
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
@ -42,8 +42,8 @@ shutdown_cache_server()
result=$(cache_admin --stop 2>&1)
rc=$?
echo "${result}"
if [ "${rc}" -ne 0 ] && [[ ! ${result} =~ "Server on port 50052 is not up or has been shutdown already" ]]; then
if [ "${rc}" -ne 0 ] && [[ ! ${result} =~ "Server on port 50052 is not reachable or has been shutdown already" ]]; then
echo "cache_admin command failure!" "${result}"
exit 1
fi
}
}

4
model_zoo/official/cv/resnet/scripts/run_distribute_train.sh
View File

@ -134,6 +134,10 @@ do
then
python train.py --net=$1 --dataset=$2 --run_distribute=True --device_num=$DEVICE_NUM --dataset_path=$PATH2 \
--run_eval=$RUN_EVAL --eval_dataset_path=$EVAL_DATASET_PATH --enable_cache=True --cache_session_id=$CACHE_SESSION_ID &> log &
if [ "x${RUN_EVAL}" == "xTrue" ]
then
echo -e "\nWhen training run is done, remember to shut down the cache server via \"cache_admin --stop\""
fi
fi
cd ..
done

4
model_zoo/official/cv/resnet/scripts/run_distribute_train_gpu.sh
View File

@ -120,4 +120,8 @@ then
python train.py --net=$1 --dataset=$2 --run_distribute=True \
--device_num=$DEVICE_NUM --device_target="GPU" --dataset_path=$PATH1 --run_eval=$RUN_EVAL \
--eval_dataset_path=$EVAL_DATASET_PATH --enable_cache=True --cache_session_id=$CACHE_SESSION_ID &> log &
if [ "x${RUN_EVAL}" == "xTrue" ]
then
echo -e "\nWhen training run is done, remember to shut down the cache server via \"cache_admin --stop\""
fi
fi

4
model_zoo/official/cv/resnet/scripts/run_standalone_train.sh
View File

@ -123,5 +123,9 @@ if [ $# == 5 ]
then
python train.py --net=$1 --dataset=$2 --dataset_path=$PATH1 --run_eval=$RUN_EVAL \
--eval_dataset_path=$EVAL_DATASET_PATH --enable_cache=True --cache_session_id=$CACHE_SESSION_ID &> log &
if [ "x${RUN_EVAL}" == "xTrue" ]
then
echo -e "\nWhen training run is done, remember to shut down the cache server via \"cache_admin --stop\""
fi
fi
cd ..

6
model_zoo/official/cv/resnet/scripts/run_standalone_train_gpu.sh
View File

@ -17,7 +17,7 @@
CURPATH="$(dirname "$0")"
. ${CURPATH}/cache_util.sh
if [ $# != 3 ] && [ $# != 4 ]
if [ $# != 3 ] && [ $# != 4 ] && [ $# != 5 ]
then
echo "Usage: bash run_standalone_train_gpu.sh [resnet50|resnet101] [cifar10|imagenet2012] [DATASET_PATH] [PRETRAINED_CKPT_PATH](optional)"
echo " bash run_standalone_train_gpu.sh [resnet50|resnet101] [cifar10|imagenet2012] [DATASET_PATH] [RUN_EVAL](optional) [EVAL_DATASET_PATH](optional)"
@ -120,5 +120,9 @@ if [ $# == 5 ]
then
python train.py --net=$1 --dataset=$2 --device_target="GPU" --dataset_path=$PATH1 --run_eval=$RUN_EVAL \
--eval_dataset_path=$EVAL_DATASET_PATH --enable_cache=True --cache_session_id=$CACHE_SESSION_ID &> log &
if [ "x${RUN_EVAL}" == "xTrue" ]
then
echo -e "\nWhen training run is done, remember to shut down the cache server via \"cache_admin --stop\""
fi
fi
cd ..

3
model_zoo/official/cv/resnet/train.py
View File

@ -266,3 +266,6 @@ if __name__ == '__main__':
dataset_sink_mode = (not args_opt.parameter_server) and target != "CPU"
model.train(config.epoch_size - config.pretrain_epoch_size, dataset, callbacks=cb,
sink_size=dataset.get_dataset_size(), dataset_sink_mode=dataset_sink_mode)
if args_opt.run_eval and args_opt.enable_cache:
print("Remember to shut down the cache server via \"cache_admin --stop\"")

4
tests/ut/python/cachetests/cachetest_args.sh
View File

@ -55,8 +55,8 @@ cmd="${CACHE_ADMIN} --start --spilldir /path_that_does_not_exist"
CacheAdminCmd "${cmd}" 1
HandleRcExit $? 0 0
# stop cache server first to test start
StopServer
# clean up cache server first to test start
ServerCleanup
# start cache server
StartServer
HandleRcExit $? 1 1

45
tests/ut/python/dataset/test_cache_map.py
View File

@ -56,7 +56,7 @@ def test_cache_map_basic1():
if "SESSION_ID" in os.environ:
session_id = int(os.environ['SESSION_ID'])
else:
session_id = 1
raise RuntimeError("Testcase requires SESSION_ID environment variable")
some_cache = ds.DatasetCache(session_id=session_id, size=0)
@ -1970,7 +1970,7 @@ def test_cache_map_mindrecord1():
if "SESSION_ID" in os.environ:
session_id = int(os.environ['SESSION_ID'])
else:
session_id = 1
raise RuntimeError("Testcase requires SESSION_ID environment variable")
some_cache = ds.DatasetCache(session_id=session_id, size=0)
@ -2006,7 +2006,7 @@ def test_cache_map_mindrecord2():
if "SESSION_ID" in os.environ:
session_id = int(os.environ['SESSION_ID'])
else:
session_id = 1
raise RuntimeError("Testcase requires SESSION_ID environment variable")
some_cache = ds.DatasetCache(session_id=session_id, size=0)
@ -2029,6 +2029,45 @@ def test_cache_map_mindrecord2():
logger.info("test_cache_map_mindrecord2 Ended.\n")
@pytest.mark.skipif(os.environ.get('RUN_CACHE_TEST') != 'TRUE', reason="Require to bring up cache server")
def test_cache_map_mindrecord3():
"""
Test cache sharing between the following two pipelines with mindrecord leaf:
Cache Cache
| |
Map(decode) Map(decode)
| |
MindRecord(num_parallel_workers=5) MindRecord(num_parallel_workers=6)
"""
logger.info("Test cache map mindrecord3")
if "SESSION_ID" in os.environ:
session_id = int(os.environ['SESSION_ID'])
else:
raise RuntimeError("Testcase requires SESSION_ID environment variable")
some_cache = ds.DatasetCache(session_id=session_id, size=0)
# This dataset has 5 records
columns_list = ["id", "file_name", "label_name", "img_data", "label_data"]
decode_op = c_vision.Decode()
ds1 = ds.MindDataset(MIND_RECORD_DATA_DIR, columns_list=columns_list, num_parallel_workers=5, shuffle=True)
ds1 = ds1.map(input_columns=["img_data"], operations=decode_op, cache=some_cache)
ds2 = ds.MindDataset(MIND_RECORD_DATA_DIR, columns_list=columns_list, num_parallel_workers=6, shuffle=True)
ds2 = ds2.map(input_columns=["img_data"], operations=decode_op, cache=some_cache)
iter1 = ds1.create_dict_iterator(num_epochs=1, output_numpy=True)
iter2 = ds2.create_dict_iterator(num_epochs=1, output_numpy=True)
assert sum([1 for _ in iter1]) == 5
assert sum([1 for _ in iter2]) == 5
logger.info("test_cache_map_mindrecord3 Ended.\n")
@pytest.mark.skipif(os.environ.get('RUN_CACHE_TEST') != 'TRUE', reason="Require to bring up cache server")
def test_cache_map_python_sampler1():
"""