转载出处

以下报错主要是由于TensorFlow升级1.0后与以前代码不兼容所致。

 

1.AttributeError: 'module' object has noattribute 'random_crop'

解决方案:

将distorted_image= tf.image.random_crop(reshaped_image, [height, width])改为:

distorted_image = tf.random_crop(reshaped_image,[height, width,3])

 

2.  AttributeError: 'module'object has no attribute 'SummaryWriter'

解决方案:

tf.train.SummaryWriter改为:tf.summary.FileWriter

 

3.  AttributeError: 'module'object has no attribute 'summaries'

解决方案:

 tf.merge_all_summaries()改为:summary_op =tf.summaries.merge_all()

 


4. AttributeError: 'module' object hasno attribute 'histogram_summary'

tf.histogram_summary(var.op.name,var)改为:  tf.summaries.histogram()

 


5. AttributeError: 'module' object hasno attribute 'scalar_summary'

tf.scalar_summary(l.op.name+ ' (raw)', l)

解决方案:

tf.scalar_summary('images',images)改为:tf.summary.scalar('images', images)

tf.image_summary('images',images)改为:tf.summary.image('images', images)

 

6. ValueError: Only call `softmax_cross_entropy_with_logits` withnamed arguments (labels=..., logits=..., ...)

解决方案:

   cifar10.loss(labels, logits) 改为:cifar10.loss(logits=logits,labels=labels)

 cross_entropy= tf.nn.softmax_cross_entropy_with_logits(
        logits, dense_labels,name='cross_entropy_per_example')

改为:

  cross_entropy = tf.nn.softmax_cross_entropy_with_logits(
        logits=logits, labels=dense_labels,name='cross_entropy_per_example')

 

7. TypeError: Using a `tf.Tensor` as a Python `bool` isnot allowed. Use `if t is not None:` instead of `if t:` to test if a tensor isdefined, and use TensorFlow ops such as tf.cond to execute subgraphsconditioned on the value of a tensor.

解决方案:

if grad: 改为  if grad is not None:

 

8. ValueError: Shapes (2, 128, 1) and () are incompatible

解决方案:

concated = tf.concat(1, [indices, sparse_labels])改为:

concated= tf.concat([indices, sparse_labels], 1)

 

9. 报错:

File"/home/lily/work/Tensorflow/CIRFAR-10/tensorflow.cifar10-master/cifar10_input.py",line 83, in read_cifar10

    result.key, value =reader.read(filename_queue)

  File"/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/io_ops.py",line 326, in read

queue_ref = queue.queue_ref

AttributeError: 'str' object hasno attribute 'queue_ref'

 

解决方案:

由于训练样本的路径需要修改,给cifar10_input.py中data_dir赋值为本地数据所在的文件夹

 

 

AttributeError: 'module' object has no attribute 'SummaryWriter'

tf.train.SummaryWriter改为:tf.summary.FileWriter

 

AttributeError: 'module' object has no attribute 'summaries'

 tf.merge_all_summaries()改为:summary_op = tf.summaries.merge_all()

 

tf.histogram_summary(var.op.name, var)
AttributeError: 'module' object has no attribute 'histogram_summary'

改为:  tf.summaries.histogram()

 

tf.scalar_summary(l.op.name + ' (raw)', l)
AttributeError: 'module' object has no attribute 'scalar_summary'

 

tf.scalar_summary('images', images)改为:tf.summary.scalar('images', images)

tf.image_summary('images', images)改为:tf.summary.image('images', images)

 

ValueError: Only call `softmax_cross_entropy_with_logits` with named arguments (labels=..., logits=..., ...)

    cifar10.loss(labels, logits) 改为:cifar10.loss(logits=logits, labels=labels)

 cross_entropy = tf.nn.softmax_cross_entropy_with_logits(
        logits, dense_labels, name='cross_entropy_per_example')

改为:

   cross_entropy = tf.nn.softmax_cross_entropy_with_logits(
        logits=logits, labels=dense_labels, name='cross_entropy_per_example')

 

TypeError: Using a `tf.Tensor` as a Python `bool` is not allowed. Use `if t is not None:` instead of `if t:` to test if a tensor is defined, and use TensorFlow ops such as tf.cond to execute subgraphs conditioned on the value of a tensor.

if grad: 改为  if grad is not None:

 

ValueError: Shapes (2, 128, 1) and () are incompatible

concated = tf.concat(1, [indices, sparse_labels])改为:

concated = tf.concat([indices, sparse_labels], 1)

 

tensorflow1.0

 

主要 API 改进

BusAdjacency 枚举被协议缓冲 DeviceLocality 代替。总线索引现在从 1 而不是 0 开始,同时,使用 bus_id==0,之前为 BUS_ANY。

Env::FileExists 和 FileSystem::FileExists 现在返回 tensorflow::Status 而不是一个 bool。任何此函数的调用者都可以通过向调用添加.ok()将返回转换为 bool。

C API:TF_SessionWithGraph 类型更名为 TF_Session,其在 TensorFlow 的绑定语言中成为首选。原来的 TF_Session 已更名为 TF_DeprecatedSession。

C API: TF_Port 被更名为 TF_Output。

C API: 调用者保留提供给 TF_Run、 TF_SessionRun、TF_SetAttrTensor 等的 TF_Tensor 对象的所有权。

将 tf.image.per_image_whitening() 更名为 tf.image.per_image_standardization()。

将 Summary protobuf 构造函数移动到了 tf.summary 子模块。

不再使用 histogram_summary、audio_summary、 scalar_summary,image_summary、merge_summary 和 merge_all_summaries。

组合 batch_ *和常规版本的线性代数和 FFT 运算。常规运算现在也处理批处理。所有 batch_ * Python 接口已删除。

tf.all_variables,tf.VARIABLES 和 tf.initialize_all_variables 更名为 tf.global_variables,tf.GLOBAL_VARIABLES 和 tf.global_variable_initializers respectively。