Tensorflow1.0版本与以前函数不同之处
Posted wangliman
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大部分是Api版本问题:
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)
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