Merge pull request #282 from guru4elephant/lac_example

add lac example and benchmark scripts

python/examples/lac/benchmark.py

+# 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.
+# pylint: disable=doc-string-missing
+
+import sys
+import time
+import requests
+from lac_reader import LACReader
+from paddle_serving_client import Client
+from paddle_serving_client.utils import MultiThreadRunner
+from paddle_serving_client.utils import benchmark_args
+
+args = benchmark_args()
+
+
+def single_func(idx, resource):
+    reader = LACReader("lac_dict")
+    start = time.time()
+    if args.request == "rpc":
+        client = Client()
+        client.load_client_config(args.model)
+        client.connect([args.endpoint])
+        fin = open("jieba_test.txt")
+        for line in fin:
+            feed_data = reader.process(line)
+            fetch_map = client.predict(
+                feed={"words": feed_data}, fetch=["crf_decode"])
+    elif args.request == "http":
+        fin = open("jieba_test.txt")
+        for line in fin:
+            req_data = {"words": line.strip(), "fetch": ["crf_decode"]}
+            r = requests.post(
+                "http://{}/lac/prediction".format(args.endpoint),
+                data={"words": line.strip(),
+                      "fetch": ["crf_decode"]})
+    end = time.time()
+    return [[end - start]]
+
+
+multi_thread_runner = MultiThreadRunner()
+result = multi_thread_runner.run(single_func, args.thread, {})
+print(result)

python/examples/lac/get_data.sh

+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/lac/lac_model.tar.gz
+tar -zxvf lac_model.tar.gz

python/examples/lac/lac_client.py

+# encoding=utf-8
+# 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.
+# pylint: disable=doc-string-missing
+
+from paddle_serving_client import Client
+from lac_reader import LACReader
+import sys
+import os
+import io
+
+client = Client()
+client.load_client_config(sys.argv[1])
+client.connect(["127.0.0.1:9280"])
+
+reader = LACReader(sys.argv[2])
+for line in sys.stdin:
+    if len(line) <= 0:
+        continue
+    feed_data = reader.process(line)
+    if len(feed_data) <= 0:
+        continue
+    fetch_map = client.predict(feed={"words": feed_data}, fetch=["crf_decode"])
+    print(fetch_map)

python/examples/lac/lac_http_client.py

+# 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.
+#coding=utf-8
+import requests
+import json
+import time
+
+if __name__ == "__main__":
+    server = "http://127.0.0.1:9280/lac/prediction"
+    fin = open("jieba_test.txt", "r")
+    start = time.time()
+    for line in fin:
+        req_data = {"words": line.strip(), "fetch": ["crf_decode"]}
+        r = requests.post(server, json=req_data)
+    end = time.time()
+    print(end - start)

python/examples/lac/lac_reader.py

+# 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.
+
+from paddle_serving_client import Client
+import sys
+reload(sys)
+sys.setdefaultencoding('utf-8')
+import os
+import io
+
+
+def load_kv_dict(dict_path,
+                 reverse=False,
+                 delimiter="\t",
+                 key_func=None,
+                 value_func=None):
+    result_dict = {}
+    for line in io.open(dict_path, "r", encoding="utf8"):
+        terms = line.strip("\n").split(delimiter)
+        if len(terms) != 2:
+            continue
+        if reverse:
+            value, key = terms
+        else:
+            key, value = terms
+        if key in result_dict:
+            raise KeyError("key duplicated with [%s]" % (key))
+        if key_func:
+            key = key_func(key)
+        if value_func:
+            value = value_func(value)
+        result_dict[key] = value
+    return result_dict
+
+
+class LACReader(object):
+    """data reader"""
+
+    def __init__(self, dict_folder):
+        # read dict
+        #basepath = os.path.abspath(__file__)
+        #folder = os.path.dirname(basepath)
+        word_dict_path = os.path.join(dict_folder, "word.dic")
+        label_dict_path = os.path.join(dict_folder, "tag.dic")
+        self.word2id_dict = load_kv_dict(
+            word_dict_path, reverse=True, value_func=int)
+        self.id2word_dict = load_kv_dict(word_dict_path)
+        self.label2id_dict = load_kv_dict(
+            label_dict_path, reverse=True, value_func=int)
+        self.id2label_dict = load_kv_dict(label_dict_path)
+
+    @property
+    def vocab_size(self):
+        """vocabulary size"""
+        return max(self.word2id_dict.values()) + 1
+
+    @property
+    def num_labels(self):
+        """num_labels"""
+        return max(self.label2id_dict.values()) + 1
+
+    def word_to_ids(self, words):
+        """convert word to word index"""
+        word_ids = []
+        idx = 0
+        try:
+            words = unicode(words, 'utf-8')
+        except:
+            pass
+        for word in words:
+            if word not in self.word2id_dict:
+                word = "OOV"
+            word_id = self.word2id_dict[word]
+            word_ids.append(word_id)
+        return word_ids
+
+    def label_to_ids(self, labels):
+        """convert label to label index"""
+        label_ids = []
+        for label in labels:
+            if label not in self.label2id_dict:
+                label = "O"
+            label_id = self.label2id_dict[label]
+            label_ids.append(label_id)
+        return label_ids
+
+    def process(self, sent):
+        words = sent.strip()
+        word_ids = self.word_to_ids(words)
+        return word_ids

python/examples/lac/lac_web_service.py

+# 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.
+
+from paddle_serving_server.web_service import WebService
+import sys
+from lac_reader import LACReader
+
+
+class LACService(WebService):
+    def load_reader(self):
+        self.reader = LACReader("lac_dict")
+
+    def preprocess(self, feed={}, fetch=[]):
+        if "words" not in feed:
+            raise ("feed data error!")
+        feed_data = self.reader.process(feed["words"])
+        return {"words": feed_data}, fetch
+
+
+lac_service = LACService(name="lac")
+lac_service.load_model_config(sys.argv[1])
+lac_service.load_reader()
+lac_service.prepare_server(
+    workdir=sys.argv[2], port=int(sys.argv[3]), device="cpu")
+lac_service.run_server()

python/examples/lac/utils.py

+#   Copyright (c) 2019 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.
+"""
+util tools
+"""
+from __future__ import print_function
+import os
+import sys
+import numpy as np
+import paddle.fluid as fluid
+import io
+
+
+def str2bool(v):
+    """
+    argparse does not support True or False in python
+    """
+    return v.lower() in ("true", "t", "1")
+
+
+def parse_result(words, crf_decode, dataset):
+    """ parse result """
+    offset_list = (crf_decode.lod())[0]
+    words = np.array(words)
+    crf_decode = np.array(crf_decode)
+    batch_size = len(offset_list) - 1
+
+    for sent_index in range(batch_size):
+        begin, end = offset_list[sent_index], offset_list[sent_index + 1]
+        sent = []
+        for id in words[begin:end]:
+            if dataset.id2word_dict[str(id[0])] == 'OOV':
+                sent.append(' ')
+            else:
+                sent.append(dataset.id2word_dict[str(id[0])])
+        tags = [
+            dataset.id2label_dict[str(id[0])] for id in crf_decode[begin:end]
+        ]
+
+        sent_out = []
+        tags_out = []
+        parital_word = ""
+        for ind, tag in enumerate(tags):
+            # for the first word
+            if parital_word == "":
+                parital_word = sent[ind]
+                tags_out.append(tag.split('-')[0])
+                continue
+
+            # for the beginning of word
+            if tag.endswith("-B") or (tag == "O" and tags[ind - 1] != "O"):
+                sent_out.append(parital_word)
+                tags_out.append(tag.split('-')[0])
+                parital_word = sent[ind]
+                continue
+
+            parital_word += sent[ind]
+
+        # append the last word, except for len(tags)=0
+        if len(sent_out) < len(tags_out):
+            sent_out.append(parital_word)
+    return sent_out, tags_out
+
+
+def parse_padding_result(words, crf_decode, seq_lens, dataset):
+    """ parse padding result """
+    words = np.squeeze(words)
+    batch_size = len(seq_lens)
+
+    batch_out = []
+    for sent_index in range(batch_size):
+
+        sent = []
+        for id in words[begin:end]:
+            if dataset.id2word_dict[str(id[0])] == 'OOV':
+                sent.append(' ')
+            else:
+                sent.append(dataset.id2word_dict[str(id[0])])
+        tags = [
+            dataset.id2label_dict[str(id)]
+            for id in crf_decode[sent_index][1:seq_lens[sent_index] - 1]
+        ]
+
+        sent_out = []
+        tags_out = []
+        parital_word = ""
+        for ind, tag in enumerate(tags):
+            # for the first word
+            if parital_word == "":
+                parital_word = sent[ind]
+                tags_out.append(tag.split('-')[0])
+                continue
+
+            # for the beginning of word
+            if tag.endswith("-B") or (tag == "O" and tags[ind - 1] != "O"):
+                sent_out.append(parital_word)
+                tags_out.append(tag.split('-')[0])
+                parital_word = sent[ind]
+                continue
+
+            parital_word += sent[ind]
+
+        # append the last word, except for len(tags)=0
+        if len(sent_out) < len(tags_out):
+            sent_out.append(parital_word)
+
+        batch_out.append([sent_out, tags_out])
+    return batch_out
+
+
+def init_checkpoint(exe, init_checkpoint_path, main_program):
+    """
+    Init CheckPoint
+    """
+    assert os.path.exists(
+        init_checkpoint_path), "[%s] cann't be found." % init_checkpoint_path
+
+    def existed_persitables(var):
+        """
+        If existed presitabels
+        """
+        if not fluid.io.is_persistable(var):
+            return False
+        return os.path.exists(os.path.join(init_checkpoint_path, var.name))
+
+    fluid.io.load_vars(
+        exe,
+        init_checkpoint_path,
+        main_program=main_program,
+        predicate=existed_persitables)