TensorFlow 1.0后与以前代码不兼容解决-CIFAR-10报错解决

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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。主要转载自CIFAR-10训练例子报错解决,并添加了一些报错解决方法。

  • 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])

  • AttributeError: ‘module’object has no attribute ‘SummaryWriter’

    解决方案:

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

  • AttributeError: ‘module’object has no attribute ‘summaries’

    解决方案:

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

  • AttributeError: ‘module’ object hasno attribute ‘histogram_summary’

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

  • 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)

  • 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’)

  • 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:

  • 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)

  • 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

  • AttributeError: ‘module’ object has no attribute ‘mul’

    解决方法:tf.mul, tf.sub and tf.neg are deprecated in favor of tf.multiply, tf.subtract and tf.negative.

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。

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