tensorflow-如何打印和书写;“预测”;归档?
我尝试了很多方法,但我无法打印或写“预测”。 我想打印模型的测试结果(“预测”)并将其写入aaa.txt,以及如何打印 代码,请参阅:tensorflow-如何打印和书写;“预测”;归档?,tensorflow,deep-learning,Tensorflow,Deep Learning,我尝试了很多方法,但我无法打印或写“预测”。 我想打印模型的测试结果(“预测”)并将其写入aaa.txt,以及如何打印 代码,请参阅: 谢谢。嗨,你找到解决办法了吗?因为我也有同样的问题。谢谢 with tf.Graph().as_default(): ............. ............. ............. image = image_preprocessing_fn(image, eval_image_size, eval_image
谢谢。嗨,你找到解决办法了吗?因为我也有同样的问题。谢谢
with tf.Graph().as_default():
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image = image_preprocessing_fn(image, eval_image_size, eval_image_size)
images, labels = tf.train.batch(
[image, label],
batch_size=FLAGS.batch_size,
num_threads=FLAGS.num_preprocessing_threads,
capacity=5 * FLAGS.batch_size)
logits, _ = network_fn(images)
predictions = tf.argmax(logits, 1) ######this predictions!!!!!!!!!!!!!!
labels = tf.squeeze(labels)
# Define the metrics:
names_to_values, names_to_updates = slim.metrics.aggregate_metric_map({
'Accuracy': slim.metrics.streaming_accuracy(predictions, labels),
'Predictions': slim.metrics.streaming_precision(predictions, labels),
'Recall@5': slim.metrics.streaming_recall_at_k(
logits, labels, 5)
})
# Print the summaries to screen.
for name, value in names_to_values.iteritems():
summary_name = 'eval/%s' % name
op = tf.summary.scalar(summary_name, value, collections=[])
op = tf.Print(op, [value], summary_name)
tf.add_to_collection(tf.GraphKeys.SUMMARIES, op)