From f7d58cc4f950f507257957ee563eba770b19182d Mon Sep 17 00:00:00 2001
From: Liufang Sang <slf12thuss@163.com>
Date: Tue, 22 Oct 2019 11:02:07 +0800
Subject: [PATCH] [PaddleSlim] add infer time  (#3688)

* add infer time test=release/1.6

* fix model name in doc  test=release/1.6
---
 PaddleCV/PaddleDetection/slim/infer.py        | 22 +++++++++++++++++++
 .../slim/quantization/README.md               |  4 +---
 PaddleSlim/classification/infer.py            | 22 +++++++++++++++++--
 3 files changed, 43 insertions(+), 5 deletions(-)

diff --git a/PaddleCV/PaddleDetection/slim/infer.py b/PaddleCV/PaddleDetection/slim/infer.py
index 4a212ad6..96a527f2 100644
--- a/PaddleCV/PaddleDetection/slim/infer.py
+++ b/PaddleCV/PaddleDetection/slim/infer.py
@@ -19,6 +19,7 @@ from __future__ import print_function
 import os
 import sys
 import glob
+import time
 
 import numpy as np
 from PIL import Image
@@ -166,8 +167,29 @@ def main():
 
     imid2path = reader.imid2path
     keys = ['bbox']
+    infer_time = True
     for iter_id, data in enumerate(reader()):
         feed_data = [[d[0], d[1]] for d in data]
+        # for infer time
+        if infer_time:
+            warmup_times = 10
+            repeats_time = 30
+            feed_data_dict = feeder.feed(feed_data);
+            for i in range(warmup_times):
+                exe.run(infer_prog,
+                        feed=feed_data_dict,
+                        fetch_list=fetch_list,
+                        return_numpy=False)
+            start_time = time.time()
+            for i in range(repeats_time):
+                exe.run(infer_prog,
+                        feed=feed_data_dict,
+                        fetch_list=fetch_list,
+                        return_numpy=False)
+
+            print("infer time: {} ms/sample".format((time.time()-start_time) * 1000 / repeats_time))
+            infer_time = False
+
         outs = exe.run(infer_prog,
                        feed=feeder.feed(feed_data),
                        fetch_list=fetch_list,
diff --git a/PaddleCV/PaddleDetection/slim/quantization/README.md b/PaddleCV/PaddleDetection/slim/quantization/README.md
index f8378776..c151678b 100644
--- a/PaddleCV/PaddleDetection/slim/quantization/README.md
+++ b/PaddleCV/PaddleDetection/slim/quantization/README.md
@@ -228,7 +228,7 @@ FP32模型可使用PaddleLite进行加载预测，可参见教程[Paddle-Lite如
 
 >当前release的结果并非超参调优后的最好结果，仅做示例参考，后续我们会优化当前结果。
 
-### MobileNetV1
+### MobileNetV1-YOLO-V3
 
 | weight量化方式 | activation量化方式| Box ap |Paddle Fluid inference time(ms)| Paddle Lite inference time(ms)|
 |---|---|---|---|---|
@@ -237,8 +237,6 @@ FP32模型可使用PaddleLite进行加载预测，可参见教程[Paddle-Lite如
 |abs_max|moving_average_abs_max|- |- |-|
 |channel_wise_abs_max|abs_max|- |- |-|
 
->训练超参：
-
 
 ## FAQ
 
diff --git a/PaddleSlim/classification/infer.py b/PaddleSlim/classification/infer.py
index 9f872301..9d5680f3 100644
--- a/PaddleSlim/classification/infer.py
+++ b/PaddleSlim/classification/infer.py
@@ -17,6 +17,7 @@ import sys
 import numpy as np
 import argparse
 import functools
+import time
 
 import paddle
 import paddle.fluid as fluid
@@ -46,9 +47,26 @@ def infer(args):
     test_reader = paddle.batch(reader.test(), batch_size=1)
     feeder = fluid.DataFeeder(place=place, feed_list=feed_target_names, program=test_program)
 
-    results=[] 
+    results=[]
+    #for infer time, if you don't need, please change infer_time to False
+    infer_time = True
     for batch_id, data in enumerate(test_reader()):
-
+        # for infer time
+        if infer_time:
+            warmup_times = 10
+            repeats_time = 30
+            feed_data = feeder.feed(data)
+            for i in range(warmup_times):
+                exe.run(test_program,
+                        feed=feed_data,
+                        fetch_list=fetch_targets)
+            start_time = time.time()
+            for i in range(repeats_time):
+                exe.run(test_program,
+                        feed=feed_data,
+                        fetch_list=fetch_targets)
+            print("infer time: {} ms/sample".format((time.time()-start_time) * 1000 / repeats_time))
+            infer_time = False
         # top1_acc, top5_acc
         result = exe.run(test_program,
                           feed=feeder.feed(data),
-- 
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