Question

我用

导出了保存的模型

tf.estimator.export.ServingInputReceiver(
      features, {'examples': example_bytestring})

但是无法用序列化的字符串提供输入。

已保存的模型cli信息

MetaGraphDef with tag-set: 'serve' contains the following SignatureDefs:

signature_def['classification']:
  The given SavedModel SignatureDef contains the following input(s):
    inputs['inputs'] tensor_info:
        dtype: DT_STRING
        shape: (-1)
        name: Placeholder:0
  The given SavedModel SignatureDef contains the following output(s):
    outputs['classes'] tensor_info:
        dtype: DT_STRING
        shape: (-1, 2)
        name: dnn/head/Tile:0
    outputs['scores'] tensor_info:
        dtype: DT_FLOAT
        shape: (-1, 2)
        name: dnn/head/predictions/probabilities:0
  Method name is: tensorflow/serving/classify

signature_def['predict']:
  The given SavedModel SignatureDef contains the following input(s):
    inputs['examples'] tensor_info:
        dtype: DT_STRING
        shape: (-1)
        name: Placeholder:0
  The given SavedModel SignatureDef contains the following output(s):
    outputs['class_ids'] tensor_info:
        dtype: DT_INT64
        shape: (-1, 1)
        name: dnn/head/predictions/ExpandDims:0
    outputs['classes'] tensor_info:
        dtype: DT_STRING
        shape: (-1, 1)
        name: dnn/head/predictions/str_classes:0
    outputs['logistic'] tensor_info:
        dtype: DT_FLOAT
        shape: (-1, 1)
        name: dnn/head/predictions/logistic:0
    outputs['logits'] tensor_info:
        dtype: DT_FLOAT
        shape: (-1, 1)
        name: dnn/logits/BiasAdd:0
    outputs['probabilities'] tensor_info:
        dtype: DT_FLOAT
        shape: (-1, 2)
        name: dnn/head/predictions/probabilities:0
  Method name is: tensorflow/serving/predict

signature_def['regression']:
  The given SavedModel SignatureDef contains the following input(s):
    inputs['inputs'] tensor_info:
        dtype: DT_STRING
        shape: (-1)
        name: Placeholder:0
  The given SavedModel SignatureDef contains the following output(s):
    outputs['outputs'] tensor_info:
        dtype: DT_FLOAT
        shape: (-1, 1)
        name: dnn/head/predictions/logistic:0
  Method name is: tensorflow/serving/regress

signature_def['serving_default']:
  The given SavedModel SignatureDef contains the following input(s):
    inputs['inputs'] tensor_info:
        dtype: DT_STRING
        shape: (-1)
        name: Placeholder:0
  The given SavedModel SignatureDef contains the following output(s):
    outputs['classes'] tensor_info:
        dtype: DT_STRING
        shape: (-1, 2)
        name: dnn/head/Tile:0
    outputs['scores'] tensor_info:
        dtype: DT_FLOAT
        shape: (-1, 2)
        name: dnn/head/predictions/probabilities:0
  Method name is: tensorflow/serving/classify

def serialize_example_string(strings):

  serialized_examples = []
  for s in strings:
    try:
  value = [bytes(s, "utf-8")]
except TypeError:  # python 2
  value = [bytes(s)]

example = tf.train.Example(
            features=tf.train.Features(
              feature={
                "sentence": tf.train.Feature(bytes_list=tf.train.BytesList(value=value))
              }
            )
          )
serialized_examples.append(example.SerializeToString())

对于Prediciton

预测= sess.run（ 'dnn / head / predictions / str_classes：0'， feed_dict = { “占位符：0”：serialize_example_string（[“ test”]） } ）

结束“此无法为Tensor u'Placeholder：0'输入形状（）的值，它的形状'（？，）'错误”

TF Estimator-从保存的模型进行预测无法正常工作

0 个答案: