我正在研究TensorFlow上的项目,并且正在尝试使用线性回归器训练模型.要将数据添加到估算器上,我正在使用函数tf.estimator.inputs.pandas_input_fn(),但由于存在一些问题,因此无法启动训练.我收到此错误：
TypeError: Failed to convert object of type <class 'dict'> to Tensor. Contents: {'DispositionSoldAmount': <tf.Tensor 'random_shuffle_queue_DequeueMany:4' shape=(128,) dtype=float64>}. Consider casting elements to a supported type.
我试图将yData更改为pandas.core.series.Series,但这并没有改变结果.
有人有解决我问题的解决方案吗？
另外,我使用sklearn.linear_regression用相同的DataSet训练了另一个模型,并且该模型可以正常工作.
这是我的代码：
FEATURES = ["DispositionMileage","PurchasePrice","Age"] # X
feature_cols = [tf.feature_column.numeric_column(k) for k in FEATURES]
estimator = tf.estimator.LinearRegressor(feature_columns=feature_cols,model_dir="train")
def get_input_fn( num_epochs=None,n_batch = 128,shuffle=True):
return tf.estimator.inputs.pandas_input_fn(
x=Xdata,y=ydata,batch_size=n_batch,num_epochs=num_epochs,shuffle=shuffle)
estimator.train(input_fn=get_input_fn(num_epochs=None,shuffle=True),steps=1000)
使用的数据：
Xdata type is pandas.core.frame.DataFrame:
DispositionMileage PurchasePrice Age
9741 3849 16472.0 0
9744 3849 16472.0 0
9745 3849 16472.0 0
9748 3849 16472.0 0
...
[18105 rows x 3 columns]
ydata type is pandas.core.frame.DataFrame:
DispositionSoldAmount
9741 1650.0
9744 1650.0
9745 1650.0
9748 1650.0
13465 7750.0
...
[18105 rows x 1 columns]
完整的回溯：
WARNING:tensorflow:From /home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/inputs/queues/feeding_queue_runner.py:62: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines,use the `tf.data` module.
WARNING:tensorflow:From /home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/inputs/queues/feeding_functions.py:500: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines,use the `tf.data` module.
Traceback (most recent call last):
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py",line 527,in make_tensor_proto
str_values = [compat.as_bytes(x) for x in proto_values]
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py",in <listcomp>
str_values = [compat.as_bytes(x) for x in proto_values]
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/util/compat.py",line 61,in as_bytes
(bytes_or_text,))
TypeError: Expected binary or unicode string,got {'DispositionSoldAmount': <tf.Tensor 'random_shuffle_queue_DequeueMany:4' shape=(128,) dtype=float64>}
During handling of the above exception,another exception occurred:
Traceback (most recent call last):
File "tuto.py",line 85,in <module>
estimator.train(input_fn=get_input_fn(num_epochs=None,steps=1000)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py",line 354,in train
loss = self._train_model(input_fn,hooks,saving_listeners)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py",line 1207,in _train_model
return self._train_model_default(input_fn,line 1237,in _train_model_default
features,labels,model_fn_lib.ModeKeys.TRAIN,self.config)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py",line 1195,in _call_model_fn
model_fn_results = self._model_fn(features=features,**kwargs)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/linear.py",line 537,in _model_fn
sparse_combiner=sparse_combiner)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/linear.py",line 215,in _linear_model_fn
logits=logits)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/head.py",line 239,in create_estimator_spec
regularization_losses))
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/head.py",line 1482,in _create_tpu_estimator_spec
features=features,mode=mode,logits=logits,labels=labels)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/head.py",line 1381,in create_loss
expected_labels_dimension=self._logits_dimension)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/head.py",line 305,in _check_dense_labels_match_logits_and_reshape
labels = sparse_tensor.convert_to_tensor_or_sparse_tensor(labels)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/framework/sparse_tensor.py",line 279,in convert_to_tensor_or_sparse_tensor
value,dtype=dtype,name=name)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py",line 1146,in internal_convert_to_tensor
ret = conversion_func(value,name=name,as_ref=as_ref)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py",line 229,in _constant_tensor_conversion_function
return constant(v,name=name)
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py",line 208,in constant
value,shape=shape,verify_shape=verify_shape))
File "/home/USER/.local/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py",line 531,in make_tensor_proto
"supported type." % (type(values),values))
TypeError: Failed to convert object of type <class 'dict'> to Tensor. Contents: {'DispositionSoldAmount': <tf.Tensor 'random_shuffle_queue_DequeueMany:4' shape=(128,) dtype=float64>}. Consider casting elements to a supported type.
最佳答案
您需要将ydata数据框转换为pandas.Series
ydata = pd.Series(ydata[column_name])
检查了随机数据,它正在工作.我实际上感到很惊讶,看起来在新的TF版本中tf.estimator.inputs.pandas_input_fn不接受数据框作为标签.
版权声明：本文内容由互联网用户自发贡献，该文观点与技术仅代表作者本人。本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容， 请发送邮件至 dio@foxmail.com 举报，一经查实，本站将立刻删除。