X_test.head()
Alarm_First_Notify_Delay
Duration_Difference
Customer_Same
Site_Same
SameDevice
100746
701 631 1 0 0
87012
0 35 1 1 1
167585
0 0 1 1 1
178924
0 35 1 1 1
76793
0 0 1 1 1
feature_spec2 = {
'Alarm_First_Notify_Delay': tf.FixedLenFeature([X_test.Alarm_First_Notify_Delay.count()],tf.float32),
'Customer_Same':tf.FixedLenFeature([X_test.Customer_Same.count()],tf.float32),
'Duration_Difference':tf.FixedLenFeature([X_test.Duration_Difference.count()],tf.float32),
'SameDevice':tf.FixedLenFeature([X_test.SameDevice.count()],tf.float32),
'Site_Same':tf.FixedLenFeature([X_test.Site_Same.count()],tf.float32)
}
value of feature_spec2 is as follows :-
{'Alarm_First_Notify_Delay': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None),
'Customer_Same': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None),
'Duration_Difference': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None),
'SameDevice': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None),
'Site_Same': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None)}
import tensorflow as tf
exported_path = 'D:\\dnnclassifier\\1518769534'
res_pred =[]
import time
from datetime import datetime
start = time.time()
start_time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(start))
print('start time : ',start_time)
with tf.Session() as sess:
#load the saved model
tf.saved_model.loader.load(sess, [tf.saved_model.tag_constants.SERVING], exported_path)
#Prepare model input, the model expects a float array to be passed to x
# check line 28 serving_input_receiver_fn
model_input= tf.train.Example(features= feature_spec2)
#get the predictor , refer tf.contrib.predicdtor
predictor= tf.contrib.predictor.from_saved_model(exported_path)
#get the input_tensor tensor from the model graph
# name is input_tensor defined in input_receiver function refer to tf.dnn.classifier
input_tensor=tf.get_default_graph().get_tensor_by_name("input_tensors:0")
#get the output dict
# do not forget [] around model_input or else it will complain shape() for Tensor shape(?,)
# since its of shape(?,) when we trained it
model_input=model_input.SerializeToString()
print(model)
output_dict= predictor({"inputs":[model_input]})
#print(" prediction is " , output_dict['scores'])
end = time.time()
end_time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(end))
print('end time : ',end_time)
error encountered:-
start time : 2018-02-16 14:08:05
INFO:tensorflow:Restoring parameters from b'D:\\dnnclassifier\\1518769534\\variables\\variables'
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
C:\ProgramData\Anaconda3\envs\tfdeeplearning\lib\site-packages\google\protobuf\internal\python_message.py in _GetFieldByName(message_descriptor, field_name)
544 try:
--> 545 return message_descriptor.fields_by_name[field_name]
546 except KeyError:
KeyError: 'SameDevice'
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-136-02d93ae3ed5d> in <module>()
15
16
---> 17 model_input= tf.train.Example(features= feature_spec2)
18
19 #get the predictor , refer tf.contrib.predicdtor
C:\ProgramData\Anaconda3\envs\tfdeeplearning\lib\site-packages\google\protobuf\internal\python_message.py in init(self, **kwargs)
514 new_val = field_value
515 if isinstance(field_value, dict):
--> 516 new_val = field.message_type._concrete_class(**field_value)
517 try:
518 copy.MergeFrom(new_val)
C:\ProgramData\Anaconda3\envs\tfdeeplearning\lib\site-packages\google\protobuf\internal\python_message.py in init(self, **kwargs)
482 self._listener_for_children = _Listener(self)
483 for field_name, field_value in kwargs.items():
--> 484 field = _GetFieldByName(message_descriptor, field_name)
485 if field is None:
486 raise TypeError("%s() got an unexpected keyword argument '%s'" %
C:\ProgramData\Anaconda3\envs\tfdeeplearning\lib\site-packages\google\protobuf\internal\python_message.py in _GetFieldByName(message_descriptor, field_name)
546 except KeyError:
547 raise ValueError('Protocol message %s has no "%s" field.' %
--> 548 (message_descriptor.name, field_name))
549
550
ValueError: Protocol message Features has no "SameDevice" field.
encounter the below error while trying to get predictions from a stored DNNCLASSIFIER model
Plaban · 15 minutes ago
feature_spec2 = {
'Alarm_First_Notify_Delay': tf.FixedLenFeature([X_test.Alarm_First_Notify_Delay.count()],tf.float32),
'Customer_Same':tf.FixedLenFeature([X_test.Customer_Same.count()],tf.float32),
'Duration_Difference':tf.FixedLenFeature([X_test.Duration_Difference.count()],tf.float32),
'SameDevice':tf.FixedLenFeature([X_test.SameDevice.count()],tf.float32),
'Site_Same':tf.FixedLenFeature([X_test.Site_Same.count()],tf.float32)
}
value of feature_spec2 is as follows :-
{'Alarm_First_Notify_Delay': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None),
'Customer_Same': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None),
'Duration_Difference': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None),
'SameDevice': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None),
'Site_Same': FixedLenFeature(shape=[66849], dtype=tf.float32, default_value=None)}
Code to get predictions
import tensorflow as tf
exported_path = 'D:\\dnnclassifier\\1518769534'
res_pred =[]
import time
from datetime import datetime
start = time.time()
start_time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(start))
print('start time : ',start_time)
with tf.Session() as sess:
#load the saved model
tf.saved_model.loader.load(sess, [tf.saved_model.tag_constants.SERVING], exported_path)
#Prepare model input, the model expects a float array to be passed to x
# check line 28 serving_input_receiver_fn
model_input= tf.train.Example(features= feature_spec2)
#get the predictor , refer tf.contrib.predicdtor
predictor= tf.contrib.predictor.from_saved_model(exported_path)
#get the input_tensor tensor from the model graph
# name is input_tensor defined in input_receiver function refer to tf.dnn.classifier
input_tensor=tf.get_default_graph().get_tensor_by_name("input_tensors:0")
#get the output dict
# do not forget [] around model_input or else it will complain shape() for Tensor shape(?,)
# since its of shape(?,) when we trained it
model_input=model_input.SerializeToString()
print(model)
output_dict= predictor({"inputs":[model_input]})
#print(" prediction is " , output_dict['scores'])
res_pred.append([items[0],items[1],items[2],items[3],items[4],output_dict['classes'],output_dict['scores']])
end = time.time()
end_time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(end))
print('end time : ',end_time)
error encountered:-
start time : 2018-02-16 14:08:05
INFO:tensorflow:Restoring parameters from b'D:\\dnnclassifier\\1518769534\\variables\\variables'
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
C:\ProgramData\Anaconda3\envs\tfdeeplearning\lib\site-packages\google\protobuf\internal\python_message.py in _GetFieldByName(message_descriptor, field_name)
544 try:
--> 545 return message_descriptor.fields_by_name[field_name]
546 except KeyError:
KeyError: 'SameDevice'
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-136-02d93ae3ed5d> in <module>()
15
16
---> 17 model_input= tf.train.Example(features= feature_spec2)
18
19 #get the predictor , refer tf.contrib.predicdtor
C:\ProgramData\Anaconda3\envs\tfdeeplearning\lib\site-packages\google\protobuf\internal\python_message.py in init(self, **kwargs)
514 new_val = field_value
515 if isinstance(field_value, dict):
--> 516 new_val = field.message_type._concrete_class(**field_value)
517 try:
518 copy.MergeFrom(new_val)
C:\ProgramData\Anaconda3\envs\tfdeeplearning\lib\site-packages\google\protobuf\internal\python_message.py in init(self, **kwargs)
482 self._listener_for_children = _Listener(self)
483 for field_name, field_value in kwargs.items():
--> 484 field = _GetFieldByName(message_descriptor, field_name)
485 if field is None:
486 raise TypeError("%s() got an unexpected keyword argument '%s'" %
C:\ProgramData\Anaconda3\envs\tfdeeplearning\lib\site-packages\google\protobuf\internal\python_message.py in _GetFieldByName(message_descriptor, field_name)
546 except KeyError:
547 raise ValueError('Protocol message %s has no "%s" field.' %
--> 548 (message_descriptor.name, field_name))
549
550
ValueError: Protocol message Features has no "SameDevice" field.
Could you please advise what is wrong over here, the model was exported with same input features.
答案 0 :(得分：0)
似乎您的CASE（和X_test）是协议缓冲区消息。您的代码尝试获取名为feature_spec2的字段，但此协议缓冲区消息没有这样的字段。检查定义消息的.proto文件。