From dee13436a6fcfa5c9a61be3a4bef5ce92af94e4c Mon Sep 17 00:00:00 2001 From: Steffy-zxf <48793257+Steffy-zxf@users.noreply.github.com> Date: Tue, 21 Apr 2020 17:20:39 +0800 Subject: [PATCH] Update docs (#531) * update docs --- .../finetuned_model_to_module/module.py | 22 +++-- docs/tutorial/finetuned_model_to_module.md | 93 +++++++++++++------ 2 files changed, 75 insertions(+), 40 deletions(-) diff --git a/demo/text_classification/finetuned_model_to_module/module.py b/demo/text_classification/finetuned_model_to_module/module.py index f79be3a2..d00b3b84 100644 --- a/demo/text_classification/finetuned_model_to_module/module.py +++ b/demo/text_classification/finetuned_model_to_module/module.py @@ -94,6 +94,7 @@ class ERNIETinyFinetuned(hub.Module): config=config, metrics_choices=metrics_choices) + @serving def predict(self, data, return_result=False, accelerate_mode=True): """ Get prediction results @@ -102,7 +103,14 @@ class ERNIETinyFinetuned(hub.Module): data=data, return_result=return_result, accelerate_mode=accelerate_mode) - return run_states + results = [run_state.run_results for run_state in run_states] + prediction = [] + for batch_result in results: + # get predict index + batch_result = np.argmax(batch_result, axis=2)[0] + batch_result = batch_result.tolist() + prediction += batch_result + return prediction if __name__ == "__main__": @@ -113,12 +121,6 @@ if __name__ == "__main__": data = [["这个宾馆比较陈旧了，特价的房间也很一般。总体来说一般"], ["交通方便；环境很好；服务态度很好 房间较小"], ["19天硬盘就罢工了~~~算上运来的一周都没用上15天~~~可就是不能换了~~~唉~~~~你说这算什么事呀~~~"]] - index = 0 - run_states = ernie_tiny.predict(data=data) - results = [run_state.run_results for run_state in run_states] - for batch_result in results: - # get predict index - batch_result = np.argmax(batch_result, axis=2)[0] - for result in batch_result: - print("%s\tpredict=%s" % (data[index][0], result)) - index += 1 + predictions = ernie_tiny.predict(data=data) + for index, text in enumerate(data): + print("%s\tpredict=%s" % (data[index][0], predictions[index])) diff --git a/docs/tutorial/finetuned_model_to_module.md b/docs/tutorial/finetuned_model_to_module.md index ddc9d8d8..853501e6 100644 --- a/docs/tutorial/finetuned_model_to_module.md +++ b/docs/tutorial/finetuned_model_to_module.md @@ -148,7 +148,9 @@ def _initialize(self, 初始化过程即为Fine-tune时创建Task的过程。 -**NOTE:** 执行类的初始化不能使用默认的__init__接口，而是应该重载实现_initialize接口。对象默认内置了directory属性，可以直接获取到Module所在路径 +**NOTE:** +1. 执行类的初始化不能使用默认的__init__接口，而是应该重载实现_initialize接口。对象默认内置了directory属性，可以直接获取到Module所在路径。 +2. 使用Fine-tune保存的模型预测时，无需加载数据集Dataset，即Reader中的dataset参数可为None。 #### step 3_4. 完善预测逻辑 ```python @@ -160,7 +162,14 @@ def predict(self, data, return_result=False, accelerate_mode=True): data=data, return_result=return_result, accelerate_mode=accelerate_mode) - return run_states + results = [run_state.run_results for run_state in run_states] + prediction = [] + for batch_result in results: + # get predict index + batch_result = np.argmax(batch_result, axis=2)[0] + batch_result = batch_result.tolist() + prediction += batch_result + return prediction ``` #### step 3_5. 支持serving调用 @@ -179,7 +188,14 @@ def predict(self, data, return_result=False, accelerate_mode=True): data=data, return_result=return_result, accelerate_mode=accelerate_mode) - return run_states + results = [run_state.run_results for run_state in run_states] + prediction = [] + for batch_result in results: + # get predict index + batch_result = np.argmax(batch_result, axis=2)[0] + batch_result = batch_result.tolist() + prediction += batch_result + return prediction ``` ### 完整代码 @@ -214,15 +230,9 @@ ernie_tiny = hub.Module(name="ernie_tiny_finetuned") data = [["这个宾馆比较陈旧了，特价的房间也很一般。总体来说一般"], ["交通方便；环境很好；服务态度很好 房间较小"], ["19天硬盘就罢工了~~~算上运来的一周都没用上15天~~~可就是不能换了~~~唉~~~~你说这算什么事呀~~~"]] -index = 0 -run_states = ernie_tiny.predict(data=data) -results = [run_state.run_results for run_state in run_states] -for batch_result in results: - # get predict index - batch_result = np.argmax(batch_result, axis=2)[0] - for result in batch_result: - print("%s\tpredict=%s" % (data[index][0], result)) - index += 1 +predictions = ernie_tiny.predict(data=data) +for index, text in enumerate(data): + print("%s\tpredict=%s" % (data[index][0], predictions[index])) ``` ### 调用方法2 @@ -238,15 +248,9 @@ ernie_tiny_finetuned = hub.Module(directory="finetuned_model_to_module/") data = [["这个宾馆比较陈旧了，特价的房间也很一般。总体来说一般"], ["交通方便；环境很好；服务态度很好 房间较小"], ["19天硬盘就罢工了~~~算上运来的一周都没用上15天~~~可就是不能换了~~~唉~~~~你说这算什么事呀~~~"]] -index = 0 -run_states = ernie_tiny.predict(data=data) -results = [run_state.run_results for run_state in run_states] -for batch_result in results: - # get predict index - batch_result = np.argmax(batch_result, axis=2)[0] - for result in batch_result: - print("%s\tpredict=%s" % (data[index][0], result)) - index += 1 +predictions = ernie_tiny.predict(data=data) +for index, text in enumerate(data): + print("%s\tpredict=%s" % (data[index][0], predictions[index])) ``` ### 调用方法3 @@ -263,13 +267,42 @@ import numpy as np data = [["这个宾馆比较陈旧了，特价的房间也很一般。总体来说一般"], ["交通方便；环境很好；服务态度很好 房间较小"], ["19天硬盘就罢工了~~~算上运来的一周都没用上15天~~~可就是不能换了~~~唉~~~~你说这算什么事呀~~~"]] -run_states = ERNIETinyFinetuned.predict(data=data) -index = 0 -results = [run_state.run_results for run_state in run_states] -for batch_result in results: - # get predict index - batch_result = np.argmax(batch_result, axis=2)[0] - for result in batch_result: - print("%s\tpredict=%s" % (data[index][0], result)) - index += 1 +predictions = ERNIETinyFinetuned.predict(data=data) +for index, text in enumerate(data): + print("%s\tpredict=%s" % (data[index][0], predictions[index])) ``` + + +### PaddleHub Serving调用方法 + +**第一步:启动预测服务** + +```shell +hub serving start -m ernie_tiny_finetuned +``` + +**第二步:发送请求，获取预测结果** + +通过如下脚本既可以发送请求： +```python +# coding: utf8 +import requests +import json + + +# 待预测文本 +texts = [["这个宾馆比较陈旧了，特价的房间也很一般。总体来说一般"], ["交通方便；环境很好；服务态度很好 房间较小"], + ["19天硬盘就罢工了~~~算上运来的一周都没用上15天~~~可就是不能换了~~~唉~~~~你说这算什么事呀~~~"]] +# key为'data', 对应着预测接口predict的参数data +data = {'data': texts} + +# 指定模型为ernie_tiny_finetuned并发送post请求，且请求的headers为application/json方式 +url = "http://127.0.0.1:8866/predict/ernie_tiny_finetuned" +headers = {"Content-Type": "application/json"} +r = requests.post(url=url, headers=headers, data=json.dumps(data)) + +# 打印预测结果 +print(json.dumps(r.json(), indent=4, ensure_ascii=False)) +``` + +关与PaddleHub Serving更多信息参见[Hub Serving教程](../../docs/tutorial/serving.md)以及[Demo](../../demo/serving) -- GitLab