提交 62a7a986 编写于 作者: M MRXLT

add gpu whl

上级 2ee7eb44
if (CLIENT_ONLY)
file(GLOB_RECURSE SERVING_CLIENT_PY_FILES paddle_serving_client/*.py)
set(PY_FILES ${SERVING_CLIENT_PY_FILES})
SET(PACKAGE_NAME "serving_client")
set(SETUP_LOG_FILE "setup.py.client.log")
file(GLOB_RECURSE SERVING_CLIENT_PY_FILES paddle_serving_client/*.py)
set(PY_FILES ${SERVING_CLIENT_PY_FILES})
SET(PACKAGE_NAME "serving_client")
set(SETUP_LOG_FILE "setup.py.client.log")
endif()
if (NOT CLIENT_ONLY)
file(GLOB_RECURSE SERVING_SERVER_PY_FILES paddle_serving_server/*.py)
set(PY_FILES ${SERVING_SERVER_PY_FILES})
SET(PACKAGE_NAME "serving_server")
set(SETUP_LOG_FILE "setup.py.server.log")
if (NOT WITH_GPU)
file(GLOB_RECURSE SERVING_SERVER_PY_FILES paddle_serving_server/*.py)
else()
file(GLOB_RECURSE SERVING_SERVER_PY_FILES paddle_serving_server_gpu/*.py)
endif()
set(PY_FILES ${SERVING_SERVER_PY_FILES})
SET(PACKAGE_NAME "serving_server")
set(SETUP_LOG_FILE "setup.py.server.log")
endif()
if (CLIENT_ONLY)
......@@ -18,8 +22,13 @@ configure_file(${CMAKE_CURRENT_SOURCE_DIR}/setup.py.client.in
endif()
if (NOT CLIENT_ONLY)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/setup.py.server.in
if (NOT WITH_GPU)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/setup.py.server.in
${CMAKE_CURRENT_BINARY_DIR}/setup.py)
else()
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/setup.py.server_gpu.in
${CMAKE_CURRENT_BINARY_DIR}/setup.py)
endif()
endif()
set(SERVING_CLIENT_CORE ${PADDLE_SERVING_BINARY_DIR}/core/general-client/serving_client.so)
......@@ -37,12 +46,22 @@ add_custom_target(paddle_python ALL DEPENDS serving_client ${PADDLE_SERVING_BINA
endif()
if (NOT CLIENT_ONLY)
add_custom_command(
if(NOT WITH_GPU)
add_custom_command(
OUTPUT ${PADDLE_SERVING_BINARY_DIR}/.timestamp
COMMAND cp -r ${CMAKE_CURRENT_SOURCE_DIR}/paddle_serving_server/ ${PADDLE_SERVING_BINARY_DIR}/python/
COMMAND env ${py_env} ${PYTHON_EXECUTABLE} setup.py bdist_wheel
DEPENDS ${SERVING_SERVER_CORE} server_config_py_proto ${PY_FILES})
add_custom_target(paddle_python ALL DEPENDS ${PADDLE_SERVING_BINARY_DIR}/.timestamp)
add_custom_target(paddle_python ALL DEPENDS ${PADDLE_SERVING_BINARY_DIR}/.timestamp)
else()
add_custom_command(
OUTPUT ${PADDLE_SERVING_BINARY_DIR}/.timestamp
COMMAND cp -r
${CMAKE_CURRENT_SOURCE_DIR}/paddle_serving_server_gpu/ ${PADDLE_SERVING_BINARY_DIR}/python/
COMMAND env ${py_env} ${PYTHON_EXECUTABLE} setup.py bdist_wheel
DEPENDS ${SERVING_SERVER_CORE} server_config_py_proto ${PY_FILES})
add_custom_target(paddle_python ALL DEPENDS ${PADDLE_SERVING_BINARY_DIR}/.timestamp)
endif()
endif()
set(SERVING_CLIENT_PYTHON_PACKAGE_DIR ${CMAKE_CURRENT_BINARY_DIR}/dist/)
......
# Copyright (c) 2020 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
from .proto import server_configure_pb2 as server_sdk
from .proto import general_model_config_pb2 as m_config
import google.protobuf.text_format
import tarfile
import paddle_serving_server as paddle_serving_server
from version import serving_server_version
class OpMaker(object):
def __init__(self):
self.op_dict = {
"general_infer": "GeneralInferOp",
"general_reader": "GeneralReaderOp",
"general_single_kv": "GeneralSingleKVOp",
"general_dist_kv": "GeneralDistKVOp"
}
# currently, inputs and outputs are not used
# when we have OpGraphMaker, inputs and outputs are necessary
def create(self, name, inputs=[], outputs=[]):
if name not in self.op_dict:
raise Exception("Op name {} is not supported right now".format(
name))
node = server_sdk.DAGNode()
node.name = "{}_op".format(name)
node.type = self.op_dict[name]
return node
class OpSeqMaker(object):
def __init__(self):
self.workflow = server_sdk.Workflow()
self.workflow.name = "workflow1"
self.workflow.workflow_type = "Sequence"
def add_op(self, node):
if len(self.workflow.nodes) >= 1:
dep = server_sdk.DAGNodeDependency()
dep.name = self.workflow.nodes[-1].name
dep.mode = "RO"
node.dependencies.extend([dep])
self.workflow.nodes.extend([node])
def get_op_sequence(self):
workflow_conf = server_sdk.WorkflowConf()
workflow_conf.workflows.extend([self.workflow])
return workflow_conf
class Server(object):
def __init__(self):
self.server_handle_ = None
self.infer_service_conf = None
self.model_toolkit_conf = None
self.resource_conf = None
self.engine = None
self.memory_optimization = False
self.model_conf = None
self.workflow_fn = "workflow.prototxt"
self.resource_fn = "resource.prototxt"
self.infer_service_fn = "infer_service.prototxt"
self.model_toolkit_fn = "model_toolkit.prototxt"
self.general_model_config_fn = "general_model.prototxt"
self.workdir = ""
self.max_concurrency = 0
self.num_threads = 0
self.port = 8080
self.reload_interval_s = 10
self.module_path = os.path.dirname(paddle_serving_server.__file__)
self.cur_path = os.getcwd()
def set_max_concurrency(self, concurrency):
self.max_concurrency = concurrency
def set_num_threads(self, threads):
self.num_threads = threads
def set_port(self, port):
self.port = port
def set_reload_interval(self, interval):
self.reload_interval_s = interval
def set_op_sequence(self, op_seq):
self.workflow_conf = op_seq
def set_memory_optimize(self, flag=False):
self.memory_optimization = flag
def _prepare_engine(self, model_config_path, device):
if self.model_toolkit_conf == None:
self.model_toolkit_conf = server_sdk.ModelToolkitConf()
if self.engine == None:
self.engine = server_sdk.EngineDesc()
self.model_config_path = model_config_path
self.engine.name = "general_model"
self.engine.reloadable_meta = model_config_path + "/fluid_time_file"
os.system("touch {}".format(self.engine.reloadable_meta))
self.engine.reloadable_type = "timestamp_ne"
self.engine.runtime_thread_num = 0
self.engine.batch_infer_size = 0
self.engine.enable_batch_align = 0
self.engine.model_data_path = model_config_path
self.engine.enable_memory_optimization = self.memory_optimization
self.engine.static_optimization = False
self.engine.force_update_static_cache = False
if device == "cpu":
self.engine.type = "FLUID_CPU_ANALYSIS_DIR"
elif device == "gpu":
self.engine.type = "FLUID_GPU_ANALYSIS_DIR"
self.model_toolkit_conf.engines.extend([self.engine])
def _prepare_infer_service(self, port):
if self.infer_service_conf == None:
self.infer_service_conf = server_sdk.InferServiceConf()
self.infer_service_conf.port = port
infer_service = server_sdk.InferService()
infer_service.name = "GeneralModelService"
infer_service.workflows.extend(["workflow1"])
self.infer_service_conf.services.extend([infer_service])
def _prepare_resource(self, workdir):
if self.resource_conf == None:
with open("{}/{}".format(workdir, self.general_model_config_fn),
"w") as fout:
fout.write(str(self.model_conf))
self.resource_conf = server_sdk.ResourceConf()
self.resource_conf.model_toolkit_path = workdir
self.resource_conf.model_toolkit_file = self.model_toolkit_fn
self.resource_conf.general_model_path = workdir
self.resource_conf.general_model_file = self.general_model_config_fn
def _write_pb_str(self, filepath, pb_obj):
with open(filepath, "w") as fout:
fout.write(str(pb_obj))
def load_model_config(self, path):
self.model_config_path = path
self.model_conf = m_config.GeneralModelConfig()
f = open("{}/serving_server_conf.prototxt".format(path), 'r')
self.model_conf = google.protobuf.text_format.Merge(
str(f.read()), self.model_conf)
# check config here
# print config here
def download_bin(self):
os.chdir(self.module_path)
need_download = False
device_version = "serving-gpu-"
floder_name = device_version + serving_server_version
tar_name = floder_name + ".tar.gz"
bin_url = "https://paddle-serving.bj.bcebos.com/bin/" + tar_name
self.server_path = os.path.join(self.module_path, floder_name)
if not os.path.exists(self.server_path):
print('Frist time run, downloading PaddleServing components ...')
r = os.system('wget ' + bin_url + ' --no-check-certificate')
if r != 0:
print('Download failed')
if os.path.exists(tar_name):
os.remove(tar_name)
else:
try:
print('Decompressing files ..')
tar = tarfile.open(tar_name)
tar.extractall()
tar.close()
except:
if os.path.exists(exe_path):
os.remove(exe_path)
finally:
os.remove(tar_name)
os.chdir(self.cur_path)
self.bin_path = self.server_path + "/serving"
def prepare_server(self, workdir=None, port=9292, device="cpu"):
if workdir == None:
workdir = "./tmp"
os.system("mkdir {}".format(workdir))
else:
os.system("mkdir {}".format(workdir))
os.system("touch {}/fluid_time_file".format(workdir))
self._prepare_resource(workdir)
self._prepare_engine(self.model_config_path, device)
self._prepare_infer_service(port)
self.workdir = workdir
infer_service_fn = "{}/{}".format(workdir, self.infer_service_fn)
workflow_fn = "{}/{}".format(workdir, self.workflow_fn)
resource_fn = "{}/{}".format(workdir, self.resource_fn)
model_toolkit_fn = "{}/{}".format(workdir, self.model_toolkit_fn)
self._write_pb_str(infer_service_fn, self.infer_service_conf)
self._write_pb_str(workflow_fn, self.workflow_conf)
self._write_pb_str(resource_fn, self.resource_conf)
self._write_pb_str(model_toolkit_fn, self.model_toolkit_conf)
def run_server(self):
# just run server with system command
# currently we do not load cube
self.download_bin()
command = "{} " \
"-enable_model_toolkit " \
"-inferservice_path {} " \
"-inferservice_file {} " \
"-max_concurrency {} " \
"-num_threads {} " \
"-port {} " \
"-reload_interval_s {} " \
"-resource_path {} " \
"-resource_file {} " \
"-workflow_path {} " \
"-workflow_file {} ".format(
self.bin_path,
self.workdir,
self.infer_service_fn,
self.max_concurrency,
self.num_threads,
self.port,
self.reload_interval_s,
self.workdir,
self.resource_fn,
self.workdir,
self.workflow_fn)
os.system(command)
# Copyright (c) 2020 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.
""" Paddle Serving Client version string """
serving_client_version = "0.1.0"
serving_server_version = "0.1.0"
module_proto_version = "0.1.0"
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