我正在学习张量流并得到一个奇怪的错误。当我在文本编辑器中键入代码并将其作为.py文件运行时，它不起作用，但如果我在python交互式命令行中逐行键入它，它运行良好并给出预期的结果。此代码来自官方教程：
import tensorflow as tf
import numpy as np
features = [tf.contrib.layers.real_valued_column("x", dimension=1)]
estimator = tf.contrib.learn.LinearRegressor(feature_columns=features)
x = np.array([1., 2., 3., 4.])
y = np.array([0., -1., -2., -3.])
input_fn = tf.contrib.learn.io.numpy_input_fn({"x":x}, y, batch_size=4,num_epochs=1000)
estimator.fit(input_fn=input_fn, steps=1000)
estimator.evaluate(input_fn=input_fn)
使用python tf_contrib_learn_basic_usage.py，结果是：
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfu
lly opened CUDA library cublas64_80.dll locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfu
lly opened CUDA library cudnn64_5.dll locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfu
lly opened CUDA library cufft64_80.dll locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfu
lly opened CUDA library nvcuda.dll locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfu
lly opened CUDA library curand64_80.dll locally
WARNING:tensorflow:Using temporary folder as model directory: C:\Users\ljxfo\AppData\Local\Temp\tmpvx8ucski
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "BestSplits" device_type: "CPU"') for unknown op: BestSplits
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "CountExtremelyRandomStats" device_type: "CPU"') for unknown op: CountExtremelyRandomStats
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "FinishedNodes" device_type: "CPU"') for unknown op: FinishedNodes
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "GrowTree" device_type: "CPU"') for unknown op: GrowTree
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "ReinterpretStringToFloat" device_type: "CPU"') for unknown op: ReinterpretStringToFloat
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "SampleInputs" device_type: "CPU"') for unknown op: SampleInputs
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "ScatterAddNdim" device_type: "CPU"') for unknown op: ScatterAddNdim
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "TopNInsert" device_type: "CPU"') for unknown op: TopNInsert
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "TopNRemove" device_type: "CPU"') for unknown op: TopNRemove
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "TreePredictions" device_type: "CPU"') for unknown op: TreePredictions
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('
op: "UpdateFertileSlots" device_type: "CPU"') for unknown op: UpdateFertileSlots
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dim
s. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:From C:\Users\ljxfo\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\contrib\le
arn\python\learn\estimators\head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will
be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that T
ensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor o
r list of tags to a scalar summary op is no longer supported.
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:885] F
ound device 0 with properties:
name: GeForce GT 635M
major: 2 minor: 1 memoryClockRate (GHz) 0.95
pciBusID 0000:01:00.0
Total memory: 2.00GiB
Free memory: 1.65GiB
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:906] D
MA: 0
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:916] 0
: Y
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:948] I
gnoring visible gpu device (device: 0, name: GeForce GT 635M, pci bus id: 0000:01:00.0) with Cuda compute capability 2.1
. The minimum required Cuda capability is 3.0.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dim
s. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:From C:\Users\ljxfo\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\contrib\le
arn\python\learn\estimators\head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will
be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that T
ensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor o
r list of tags to a scalar summary op is no longer supported.
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:948] I
gnoring visible gpu device (device: 0, name: GeForce GT 635M, pci bus id: 0000:01:00.0) with Cuda compute capability 2.1
. The minimum required Cuda capability is 3.0.
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
据我所知，使用gtx635m的笔记本电脑并不完全支持cuda，但是在逐行输入时代码效果很好。那有什么不对呢？