add auc metric for client

python/paddle_serving_client/metric/__init__.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.

python/paddle_serving_client/metric/auc.py

+def tied_rank(x):
+    """
+    Computes the tied rank of elements in x.
+    This function computes the tied rank of elements in x.
+    Parameters
+    ----------
+    x : list of numbers, numpy array
+    Returns
+    -------
+    score : list of numbers
+            The tied rank f each element in x
+    """
+    sorted_x = sorted(zip(x,range(len(x))))
+    r = [0 for k in x]
+    cur_val = sorted_x[0][0]
+    last_rank = 0
+    for i in range(len(sorted_x)):
+        if cur_val != sorted_x[i][0]:
+            cur_val = sorted_x[i][0]
+            for j in range(last_rank, i): 
+                r[sorted_x[j][1]] = float(last_rank+1+i)/2.0
+            last_rank = i
+        if i==len(sorted_x)-1:
+            for j in range(last_rank, i+1): 
+                r[sorted_x[j][1]] = float(last_rank+i+2)/2.0
+    return r
+
+def auc(actual, posterior):
+    """
+    Computes the area under the receiver-operater characteristic (AUC)
+    This function computes the AUC error metric for binary classification.
+    Parameters
+    ----------
+    actual : list of binary numbers, numpy array
+             The ground truth value
+    posterior : same type as actual
+                Defines a ranking on the binary numbers, from most likely to
+                be positive to least likely to be positive.
+    Returns
+    -------
+    score : double
+            The mean squared error between actual and posterior
+    """
+    r = tied_rank(posterior)
+    num_positive = len([0 for x in actual if x==1])
+    num_negative = len(actual)-num_positive
+    sum_positive = sum([r[i] for i in range(len(r)) if actual[i]==1])
+    auc = ((sum_positive - num_positive*(num_positive+1)/2.0) /
+           (num_negative*num_positive))
+    return auc
+

python/setup.py.client.in

@@ -34,14 +34,17 @@ REQUIRED_PACKAGES = [
 
 packages=['paddle_serving_client',
           'paddle_serving_client.proto',
-          'paddle_serving_client.io']
+          'paddle_serving_client.io',
+	  'paddle_serving_client.metric']
 package_data={'paddle_serving_client': ['serving_client.so']}
 package_dir={'paddle_serving_client':
              '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_client',
              'paddle_serving_client.proto':
              '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_client/proto',
              'paddle_serving_client.io':
-             '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_client/io'}
+             '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_client/io',
+	     'paddle_serving_client.metric':
+	     '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_client/metric'}
 
 setup(
     name='paddle-serving-client',