tensorflow函数API变更列表

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)

 

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.summary.merge_all()

 

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

tf.histogram_summary()

改为：tf.summary.histogram()

 

tf.scalar_summary()

改为：tf.summary.scalar()

 

tf.image_summary()

改为：tf.summary.image()

self.summary_writer = tf.train.SummaryWriter(summary_dir)
改为：summary.FileWriter(name)

self.summaries = tf.merge_summary([
    tf.scalar_summary("loss", self.loss)
])
改为：summary.merge().      summary.scalar()

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