Add PaddleSlim CE (#2288)

* Add PaddleSlim CE

* Add log and remove counting

* Remove environment variable LD_LIBRARY_PATH

* Reduce epoch count to save time

PaddleSlim/.run_ce.sh

+#!/bin/bash
+# This file is only used for continuous evaluation.
+
+export FLAGS_eager_delete_tensor_gb=0.0
+export CUDA_VISIBLE_DEVICES=3
+
+if [ ! -d 'pretrain' ]; then
+    ln -s ${PRETRAINED_MODEL_PATH} ./pretrain
+fi
+
+if [ ! -d 'data' ]; then
+    ln -s ${ILSVRC2012_DATA_PATH} ./data
+fi
+
+if [ -d 'checkpoints' ]; then
+    rm -rf checkpoints
+fi
+
+sed -i "s/epoch: 200/epoch: 1/g" configs/filter_pruning_uniform.yaml
+
+python compress.py \
+    --model "MobileNet" \
+    --pretrained_model ./pretrain/MobileNetV1_pretrained \
+    --compress_config ./configs/filter_pruning_uniform.yaml 2>&1 | tee run.log | python _ce.py
+
+
+

PaddleSlim/_ce.py

+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+
+import os
+import sys
+import re
+sys.path.append(os.environ['ceroot'])
+from kpi import AccKpi
+
+test_acc_top1_kpi = AccKpi(
+    'test_acc_top1', 0.02, 0, actived=True, desc='TOP1 ACC')
+test_acc_top5_kpi = AccKpi(
+    'test_acc_top5', 0.02, 0, actived=True, desc='TOP5 ACC')
+tracking_kpis = [test_acc_top1_kpi, test_acc_top5_kpi] 
+
+
+def parse_log(log):
+    '''
+    parse log
+    '''
+    pattern = r"^.*Final eval result: \['acc_top1', 'acc_top5'\]=\[(?P<test_acc_top1>0\.\d+)\s+(?P<test_acc_top5>0\.\d+)\s*\]"
+    prog = re.compile(pattern)
+    for line in log.split('\n'):
+        result = prog.match(line)
+        if not result:
+            continue
+        for kpi_name, kpi_value in result.groupdict().iteritems():
+            yield kpi_name, float(kpi_value)
+
+
+def log_to_ce(log):
+    """
+    log to ce
+    """
+    kpi_tracker = {}
+    for kpi in tracking_kpis:
+        kpi_tracker[kpi.name] = kpi
+
+    for(kpi_name, kpi_value) in parse_log(log):
+        kpi_tracker[kpi_name].add_record(kpi_value)
+        kpi_tracker[kpi_name].persist()
+
+
+if __name__ == '__main__':
+    log = sys.stdin.read()
+    log_to_ce(log)
+
+