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提交 caa6b596 编写于 作者: H heqiaozhi
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add hdfs_utils & helper & node doc

上级 37596000
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Showing with 238 addition and 72 deletion
python/paddle/fluid/contrib/utils/hdfs_utils.py
浏览文件 @ caa6b596
......@@ -32,6 +32,28 @@ _logger.setLevel(logging.INFO)
class HDFSClient(object):
"""
A tool of HDFS
Args:
hadoop_home (string): hadoop_home
configs (dict): hadoop config, it is a dict, please contain \
key "fs.default.name" and "hadoop.job.ugi"
Can be a float value
Examples:
hadoop_home = "/home/client/hadoop-client/hadoop/"
configs = {
"fs.default.name": "hdfs://xxx.hadoop.com:54310",
"hadoop.job.ugi": "hello,hello123"
}
client = HDFSClient(hadoop_home, configs)
client.ls("/user/com/train-25")
files = client.lsr("/user/com/train-25/models")
"""
def __init__(self, hadoop_home, configs):
self.pre_commands = []
hadoop_bin = '%s/bin/hadoop' % hadoop_home
......@@ -55,7 +77,10 @@ class HDFSClient(object):
whole_commands = " ".join(whole_commands)
for x in range(retry_times + 1):
proc = subprocess.Popen(
whole_commands, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
whole_commands,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
shell=True)
(output, errors) = proc.communicate()
ret_code, ret_out, ret_err = proc.returncode, output, errors
if ret_code:
......@@ -69,10 +94,12 @@ class HDFSClient(object):
def upload(self, hdfs_path, local_path, overwrite=False, retry_times=5):
"""
upload the local file to hdfs
args:
local_file_path: the local file path
remote_file_path: default value(${OUTPUT_PATH}/${SYS_USER_ID}/${SYS_JOB_ID}/tmp)
return:
Args:
hdfs_path: hdfs path, target path
local_path: local file path, source path
overwrite: will overwrite the original file
retry_times: max times retry to upload
Returns:
True or False
"""
assert hdfs_path is not None
......@@ -115,10 +142,12 @@ class HDFSClient(object):
def download(self, hdfs_path, local_path, overwrite=False, unzip=False):
"""
download from hdfs
args:
local_file_path: the local file path
remote_file_path: remote dir on hdfs
return:
Args:
hdfs_path: hdfs path, target path
local_path: local file path, source path
overwrite: will remove original file and overwrite it.
unzip: ignore this param
Returns
True or False
"""
_logger.info('Downloading %r to %r.', hdfs_path, local_path)
......@@ -160,11 +189,11 @@ class HDFSClient(object):
def is_exist(self, hdfs_path=None):
"""
whether the remote hdfs path exists?
args:
remote_file_path: default value(${OUTPUT_PATH}/${SYS_USER_ID}/${SYS_JOB_ID}/tmp)
Args:
hdfs_path: default value(${OUTPUT_PATH}/${SYS_USER_ID}/${SYS_JOB_ID}/tmp)
fs_name: The default values are the same as in the job configuration
fs_ugi: The default values are the same as in the job configuration
return:
Returns:
True or False
"""
exist_cmd = ['-test', '-e', hdfs_path]
......@@ -183,11 +212,11 @@ class HDFSClient(object):
def is_dir(self, hdfs_path=None):
"""
whether the remote hdfs path exists?
args:
Args:
remote_file_path: default value(${OUTPUT_PATH}/${SYS_USER_ID}/${SYS_JOB_ID}/tmp)
fs_name: The default values are the same as in the job configuration
fs_ugi: The default values are the same as in the job configuration
return:
Returns:
True or False
"""
......@@ -207,15 +236,17 @@ class HDFSClient(object):
return True
def delete(self, hdfs_path):
"""Remove a file or directory from HDFS.
:param hdfs_path: HDFS path.
:param recursive: Recursively delete files and directories. By default,
this method will raise an :class:`HdfsError` if trying to delete a
non-empty directory.
"""
Remove a file or directory from HDFS.
This function returns `True` if the deletion was successful and `False` if
no file or directory previously existed at `hdfs_path`.
Args:
param hdfs_path: HDFS path.
param recursive: Recursively delete files and directories. By default,
this method will raise an :class:`HdfsError` if trying to delete a
non-empty directory.
Returns:
This function returns `True` if the deletion was successful and `False` if
no file or directory previously existed at `hdfs_path`.
"""
_logger.info('Deleting %r.', hdfs_path)
......@@ -241,14 +272,17 @@ class HDFSClient(object):
return True
def rename(self, hdfs_src_path, hdfs_dst_path, overwrite=False):
"""Move a file or folder.
:param hdfs_src_path: Source path.
:param hdfs_dst_path: Destination path. If the path already exists and is
a directory, the source will be moved into it. If the path exists and is
a file, or if a parent destination directory is missing, this method will
raise an :class:`HdfsError`.
"""
Rename a file or folder.
Args:
:param hdfs_src_path: Source path.
:param hdfs_dst_path: Destination path. If the path already exists and is
a directory, the source will be moved into it. If the path exists and is
a file, or if a parent destination directory is missing, this method will
raise an :class:`HdfsError`.
Returns:
This function returns `True` if the rename was successful and `False` if
rename was faild.
"""
assert hdfs_src_path is not None
assert hdfs_dst_path is not None
......@@ -274,6 +308,11 @@ class HDFSClient(object):
@staticmethod
def make_local_dirs(local_path):
"""
create a directiory local, is same to mkdir
Args:
local_path: local path that wants to create a directiory.
"""
try:
os.makedirs(local_path)
except OSError as e:
......@@ -282,9 +321,11 @@ class HDFSClient(object):
def makedirs(self, hdfs_path):
"""Create a remote directory, recursively if necessary.
:param hdfs_path: Remote path. Intermediate directories will be created
appropriately.
Args:
:param hdfs_path: Remote path. Intermediate directories will be created
appropriately.
Returns:
True if make a directories was successful, False when make a directiries was failed.
"""
_logger.info('Creating directories to %r.', hdfs_path)
assert hdfs_path is not None
......@@ -304,6 +345,13 @@ class HDFSClient(object):
return True
def ls(self, hdfs_path):
"""
ls a hdfs_path.
Args:
:param hdfs_path: hdfs_path will be ls.
Returns:
This function returns a `list` that contaion all files in the hdfs_path.
"""
assert hdfs_path is not None
if not self.is_exist(hdfs_path):
......@@ -329,6 +377,14 @@ class HDFSClient(object):
return ret_lines
def lsr(self, hdfs_path, only_file=True, sort=True):
"""
ls a hdfs_path sort by time.
Args:
:param hdfs_path: hdfs_path will be ls.
Returns:
This function returns a `list` that contaion all files sorted by time in the hdfs_path.
"""
def sort_by_time(v1, v2):
v1_time = datetime.strptime(v1[1], '%Y-%m-%d %H:%M')
v2_time = datetime.strptime(v2[1], '%Y-%m-%d %H:%M')
......@@ -372,12 +428,15 @@ def multi_upload(client,
multi_processes=5,
overwrite=False):
"""
:param overwrite: will overwrite hdfs file or not
:param multi_processes: the upload data process at the same time, default=5
:param client: instance of HDFSClient
:param hdfs_path: path on hdfs
:param local_path: path on local
:return:
Upload file to hdfs.
Args:
:param overwrite: will overwrite hdfs file or not
:param multi_processes: the upload data process at the same time, default=5
:param client: instance of HDFSClient
:param hdfs_path: path on hdfs
:param local_path: path on local
Returns:
"""
def __subprocess_upload(datas):
......@@ -387,6 +446,13 @@ def multi_upload(client,
client.upload(hdfs_re_path, data, overwrite, retry_times=5)
def get_local_files(path):
"""
Get all local files
Args:
path: local file path
Returns:
A list that contation all files in the path.
"""
rlist = []
if not os.path.isdir(path):
......@@ -431,14 +497,17 @@ def multi_download(client,
multi_processes=5):
"""
multi_download
:param client: instance of HDFSClient
:param hdfs_path: path on hdfs
:param local_path: path on local
:param trainer_id: current trainer id
:param trainers: all trainers number
:param file_cnt: all file number
:param multi_processes: the download data process at the same time, default=5
:return: None
Args:
:param client: instance of HDFSClient
:param hdfs_path: path on hdfs
:param local_path: path on local
:param trainer_id: current trainer id
:param trainers: all trainers number
:param file_cnt: all file number
:param multi_processes: the download data process at the same time, default=5
:return: None
Returns:
A list that be downloaded.
"""
def __subprocess_download(datas):
......
python/paddle/fluid/distributed/helper.py
浏览文件 @ caa6b596
......@@ -15,13 +15,26 @@
from mpi4py import MPI
import ps_pb2 as pslib
class FileSystem(object):
def __init__(self, fs_type="afs",
"""
A file system that support async_executor hadoop client desc.
Args:
fs_type (string): fs_type, for example is "afs"
user (string): hadoop param
passwd (string): hadoop param
hadoop bin (string): hadoop param
Examples:
fs = FileSystm()
"""
def __init__(self,
fs_type="afs",
uri="afs://tianqi.afs.baidu.com:9902",
user=None,
passwd=None,
hadoop_bin="",
afs_conf=None):
hadoop_bin=""):
assert user != None
assert passwd != None
assert hadoop_bin != None
......@@ -38,9 +51,22 @@ class FileSystem(object):
#self.fs_client.afs_conf = afs_conf if not afs_conf else ""
def get_desc(self):
"""
get hadoop desc.
"""
return self.fs_client
class MPIHelper(object):
"""
MPIHelper is a wrapper of mpi4py, supprot get_rank get_size etc.
Args:
No params
Examples:
mh = MPIHelper()
mh.get_ip()
"""
def __init__(self):
self.comm = MPI.COMM_WORLD
......@@ -61,5 +87,3 @@ class MPIHelper(object):
def finalize(self):
MPI.Finalize()
python/paddle/fluid/distributed/node.py
浏览文件 @ caa6b596
......@@ -13,17 +13,34 @@
import ps_pb2 as pslib
class Server(object):
"""
A Server basic class.
"""
def __init__(self):
pass
class Worker(object):
"""
A Worker basic class.
"""
def __init__(self):
pass
class DownpourServer(Server):
"""
DownpourServer class is used to generate server program_desc
Args:
server: it is pslib.ServerParameter()
Examples:
server = DownpourServer()
"""
def __init__(self):
self.server_ = pslib.ServerParameter()
self.server_.downpour_server_param.service_param.start_server_port = 0
......@@ -33,8 +50,18 @@ class DownpourServer(Server):
self.server_.downpour_server_param.service_param.start_server_port = 0
self.server_.downpour_server_param.service_param.server_thread_num = 12
def add_sparse_table(self, table_id, learning_rate,
slot_key_vars, slot_value_var):
def add_sparse_table(self, table_id, learning_rate, slot_key_vars,
slot_value_var):
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
slot_key_vars(string): slot key id
slot_value_var(string): slot key value after embedding
Returns:
return None
"""
table = self.server_.downpour_server_param.downpour_table_param.add()
table.table_id = table_id
table.table_class = "DownpourSparseTable"
......@@ -44,10 +71,10 @@ class DownpourServer(Server):
table.accessor.sparse_sgd_param.initial_g2sum = 3
table.accessor.sparse_sgd_param.initial_range = 1e-4
table.accessor.sparse_sgd_param.weight_bounds.extend([-10, 10])
table.accessor.embedx_dim = 8
table.accessor.embedx_threshold = 5
table.accessor.fea_dim = 11
table.accessor.fea_dim = 11
#table.accessor.fea_dim = abs(reduce(lambda x, y: x * y,
# slot_value_var[0].shape, 1))
table.accessor.downpour_accessor_param.nonclk_coeff = 0.1
......@@ -58,53 +85,99 @@ class DownpourServer(Server):
table.accessor.downpour_accessor_param.show_click_decay_rate = 0.999
table.accessor.downpour_accessor_param.delete_threshold = 0.8
def add_dense_table(self, table_id, learning_rate,
param_var, grad_var):
def add_dense_table(self, table_id, learning_rate, param_var, grad_var):
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
param_var(list): all dense param. it is a list.
grad_var(list): all dense grad parm it is a list.
Returns:
return None
"""
table = self.server_.downpour_server_param.downpour_table_param.add()
table.table_id = table_id
table.table_class = "DownpourDenseTable"
table.type = pslib.PS_DENSE_TABLE
table.accessor.accessor_class = "DownpourDenseValueAccessor"
table.accessor.dense_sgd_param.name = "adam"
table.accessor.dense_sgd_param.name = "adam"
table.accessor.dense_sgd_param.adam.learning_rate = learning_rate
table.accessor.dense_sgd_param.adam.avg_decay_rate = 0.999993
table.accessor.dense_sgd_param.adam.ada_decay_rate = 0.9999
table.accessor.dense_sgd_param.adam.avg_decay_rate = 0.999993
table.accessor.dense_sgd_param.adam.ada_decay_rate = 0.9999
table.accessor.dense_sgd_param.adam.ada_epsilon = 1e-8
table.accessor.dense_sgd_param.adam.mom_decay_rate = 0.99
table.accessor.dense_sgd_param.naive.learning_rate = 0.0002
fea_dim = 0
for param in filter(lambda x: x.name.find("embedding") == -1, param_var):
for param in filter(lambda x: x.name.find("embedding") == -1,
param_var):
fea_dim += reduce(lambda x, y: x * y, param.shape, 1)
table.accessor.fea_dim = fea_dim
def get_desc(self):
"""
Return downpour server program_desc
"""
return self.server_
class DownpourWorker(Worker):
"""
DownpourWorker class is used to generate worker program_desc
Args:
window (int): push params frequency
worker: it is pslib.DownpourTrainerParameter
Examples:
worker = DownpourWorker(1)
"""
def __init__(self, window):
self.window = window
self.worker_ = pslib.DownpourTrainerParameter()
#self.worker_.pull_dense_per_batch = window
#self.worker_.push_dense_per_batch = window
def add_sparse_table(self, table_id, learning_rate,
slot_key_vars, slot_value_vars):
def add_sparse_table(self, table_id, learning_rate, slot_key_vars,
slot_value_vars):
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
slot_key_vars(string): slot key id
slot_value_var(string): slot key value after embedding
Returns:
return None
"""
table = self.worker_.sparse_table.add()
table.table_id = table_id
table.slot_key.extend(
[var.name for var in slot_key_vars])
table.slot_value.extend(
[var.name for var in slot_value_vars])
table.slot_key.extend([var.name for var in slot_key_vars])
table.slot_value.extend([var.name for var in slot_value_vars])
table.slot_gradient.extend(
[var.name + "@GRAD" for var in slot_value_vars])
def add_dense_table(self, table_id, learning_rate,
param_vars, grad_vars):
def add_dense_table(self, table_id, learning_rate, param_vars, grad_vars):
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
param_var(list): all dense param. it is a list.
grad_var(list): all dense grad parm it is a list.
Returns:
return None
"""
table = self.worker_.dense_table.add()
table.table_id = table_id
table.dense_variable_name.extend(filter(lambda x: x.find("embedding") == -1, [p.name for p in param_vars]))
table.dense_gradient_variable_name.extend(filter(lambda x: x.find("embedding") == -1, [g.name for g in grad_vars]))
table.dense_variable_name.extend(
filter(lambda x: x.find("embedding") == -1,
[p.name for p in param_vars]))
table.dense_gradient_variable_name.extend(
filter(lambda x: x.find("embedding") == -1,
[g.name for g in grad_vars]))
def get_desc(self):
"""
Return downpour worker program_desc
"""
return self.worker_
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