add imdb code

core/configure/CMakeLists.txt

@@ -29,22 +29,24 @@ FILE(GLOB inc ${CMAKE_CURRENT_BINARY_DIR}/*.pb.h)
 install(FILES ${inc}
         DESTINATION ${PADDLE_SERVING_INSTALL_DIR}/include/configure)
 
+if (CLIENT_ONLY)
 py_proto_compile(sdk_configure_py_proto SRCS proto/sdk_configure.proto)
 add_custom_target(sdk_configure_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
 add_dependencies(sdk_configure_py_proto sdk_configure_py_proto_init)
 add_custom_command(TARGET sdk_configure_py_proto POST_BUILD
-		COMMAND ${CMAKE_COMMAND} -E make_directory ${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving/proto
-		COMMAND cp *.py ${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving/proto
-		COMMENT "Copy generated python proto into directory paddle_serving/proto."
+		COMMAND ${CMAKE_COMMAND} -E make_directory ${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_client/proto
+		COMMAND cp *.py ${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_client/proto
+		COMMENT "Copy generated python proto into directory paddle_serving_client/proto."
 		WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR})
+endif()
 
 if (NOT CLIENT_ONLY)
 py_proto_compile(server_config_py_proto SRCS proto/server_configure.proto)
 add_custom_target(server_config_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
 add_dependencies(server_config_py_proto server_config_py_proto_init)
 add_custom_command(TARGET server_config_py_proto POST_BUILD
-		COMMAND ${CMAKE_COMMAND} -E make_directory ${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving/proto
-		COMMAND cp *.py ${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving/proto
-		COMMENT "Copy generated python proto into directory paddle_serving/proto."
+		COMMAND ${CMAKE_COMMAND} -E make_directory ${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_server/proto
+		COMMAND cp *.py ${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_server/proto
+		COMMENT "Copy generated python proto into directory paddle_serving_server/proto."
 		WORKING_DIRECTORY ${CMAKE_CURRENT_BINRARY_DIR})
 endif()

python/examples/imdb/get_data.sh

-wget https://fleet.bj.bcebos.com/text_classification_data.tar.gz
+wget --no-check-certificate https://fleet.bj.bcebos.com/text_classification_data.tar.gz
 tar -zxvf text_classification_data.tar.gz
+#wget --no-check-certificate https://paddle-serving.bj.bcebos.com/imdb-demo%2Fimdb.tar.gz
+#tar -xzf imdb-demo%2Fimdb.tar.gz

python/examples/imdb/local_train.py

@@ -16,7 +16,6 @@ import sys
 import paddle
 import logging
 import paddle.fluid as fluid
-import paddle_serving as serving
 
 logging.basicConfig(format='%(asctime)s - %(levelname)s - %(message)s')
 logger = logging.getLogger("fluid")
@@ -42,7 +41,7 @@ if __name__ == "__main__":
     dataset = fluid.DatasetFactory().create_dataset()
     filelist = ["train_data/%s" % x for x in os.listdir("train_data")]
     dataset.set_use_var([data, label])
-    pipe_command = "python imdb_reader.py"
+    pipe_command = "/home/users/dongdaxiang/paddle_whls/custom_op/paddle_release_home/python/bin/python imdb_reader.py"
     dataset.set_pipe_command(pipe_command)
     dataset.set_batch_size(4)
     dataset.set_filelist(filelist)
@@ -57,12 +56,19 @@ if __name__ == "__main__":
     epochs = 30
     save_dirname = "cnn_model"
 
+    import paddle_serving_client.io as serving_io
+
     for i in range(epochs):
         exe.train_from_dataset(program=fluid.default_main_program(),
                                dataset=dataset, debug=False)
         logger.info("TRAIN --> pass: {}".format(i))
-        fluid.io.save_inference_model("%s/epoch%d.model" % (save_dirname, i),
-                                      [data.name, label.name], [acc], exe)
-        serving.save_model("%s/epoch%d.model" % (save_dirname, i), "client_config{}".format(i),
-                           {"words": data, "label": label},
-                           {"acc": acc, "cost": avg_cost, "prediction": prediction})
+        if i == 20:
+            serving_io.save_model("serving_server_model",
+                                  "serving_client_conf",
+                                  {"words": data, "label": label},
+                                  {"cost": avg_cost, "acc": acc,
+                                   "prediction": prediction},
+                                  fluid.default_main_program())
+
+
+

python/examples/imdb/test_client.py

-from paddle_serving.serving_client import Client
+from paddle_serving_client import Client
 import sys
 
 client = Client()
@@ -7,10 +7,11 @@ client.connect(["127.0.0.1:9292"])
 
 for line in sys.stdin:
     group = line.strip().split()
-    words = [int(x) for x in group[1:int(group[0])]]
+    words = [int(x) for x in group[1:int(group[0]) + 1]]
     label = [int(group[-1])]
     feed = {"words": words, "label": label}
-    fetch = ["acc", "cost", "prediction"]
+    fetch = ["cost", "acc", "prediction"]
     fetch_map = client.predict(feed=feed, fetch=fetch)
-    print("{} {}".format(fetch_map["prediction"][1], label[0]))
+    print(fetch_map)
+    #print("{} {}".format(fetch_map["prediction"][1], label[0]))
     

python/examples/imdb/test_client_batch.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from paddle_serving.serving_client import Client
+from paddle_serving_client import Client
 import sys
 import subprocess
 from multiprocessing import Pool

python/examples/imdb/test_client_multithread.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from paddle_serving import Client
+from paddle_serving_client import Client
 import sys
 import subprocess
 from multiprocessing import Pool

python/examples/imdb/test_server.py

+import os
+import sys
+from paddle_serving_server import OpMaker
+from paddle_serving_server import OpSeqMaker
+from paddle_serving_server import Server
+
+op_maker = OpMaker()
+read_op = op_maker.create('general_reader')
+general_infer_op = op_maker.create('general_infer')
+
+op_seq_maker = OpSeqMaker()
+op_seq_maker.add_op(read_op)
+op_seq_maker.add_op(general_infer_op)
+
+server = Server()
+server.set_op_sequence(op_seq_maker.get_op_sequence())
+server.load_model_config(sys.argv[1])
+server.prepare_server(workdir="work_dir1", port=9292, device="cpu")
+server.run_server()