Question

即使日志目录中有检查点文件，嵌入式投影仪也不会显示任何内容。

我的代码是文件的修改版本：mnist_t-sine.py来自：https://github.com/normanheckscher/mnist-tensorboard-embeddings。它已被修改为绘制嵌入的直方图（没有多大意义，但只是为了检查张量板是否有效）。

这是我的代码：https://drive.google.com/open?id=0B8ZdOStUW_DCb3Uwbm9VTnQ5SzA

# Copyright 2016 Norman Heckscher. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the 'License');
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an 'AS IS' BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""MNIST dimensionality reduction with TensorFlow and TensorBoard.

This demonstrates the functionality of the TensorBoard Embedding Visualization dashboard using MNIST.

https://www.tensorflow.org/versions/r0.12/how_tos/embedding_viz/index.html#tensorboard-embedding-visualization
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import argparse
import sys

import os
import numpy as np
from tensorflow.contrib.tensorboard.plugins import projector

import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data
FLAGS = None

def generate_embeddings():
    # Import data
    mnist = input_data.read_data_sets(FLAGS.data_dir,
                                      one_hot=True,
                                      fake_data=FLAGS.fake_data)
    sess = tf.InteractiveSession()

    # Input set for Embedded TensorBoard visualization
    # Performed with cpu to conserve memory and processing power
    with tf.device("/cpu:0"):
        embedding = tf.Variable(tf.stack(mnist.test.images[:FLAGS.max_steps], axis=0), trainable=False, name='embedding')
    tf.summary.histogram("Embedding",embedding)
    tf.summary.tensor_summary("Embeddings", embedding)

    saver = tf.train.Saver()
    writer = tf.summary.FileWriter(FLAGS.log_dir + '/projector', sess.graph)

    merged_summ = tf.summary.merge_all()
    tf.global_variables_initializer().run()
    # Add embedding tensorboard visualization. Need tensorflow version
    # >= 0.12.0RC0
    config = projector.ProjectorConfig()
    embed= config.embeddings.add()
    embed.tensor_name = 'embedding'
    embed.metadata_path = os.path.join(FLAGS.log_dir + '/projector/metadata.tsv')
    embed.sprite.image_path = os.path.join(FLAGS.data_dir + '/mnist_10k_sprite.png')
    summ = sess.run(merged_summ)
    for i in range(20):
        writer.add_summary(summ,i)
    # Specify the width and height of a single thumbnail.
    embed.sprite.single_image_dim.extend([28, 28])
    projector.visualize_embeddings(writer, config)
    print(sess.run(embedding))
    saver.save(sess, os.path.join(
        FLAGS.log_dir, 'projector/a_model.ckpt'), global_step=FLAGS.max_steps)

def generate_metadata_file():
    # Import data
    mnist = input_data.read_data_sets(FLAGS.data_dir,
                                      one_hot=True,
                                      fake_data=FLAGS.fake_data)
    def save_metadata(file):
        with open(file, 'w') as f:
            for i in range(FLAGS.max_steps):
                c = np.nonzero(mnist.test.labels[::1])[1:][0][i]
                f.write('{}\n'.format(c))

    save_metadata(FLAGS.log_dir + '/projector/metadata.tsv')

def main(_):
    if tf.gfile.Exists(FLAGS.log_dir + '/projector'):
        tf.gfile.DeleteRecursively(FLAGS.log_dir + '/projector')
        tf.gfile.MkDir(FLAGS.log_dir + '/projector')
    tf.gfile.MakeDirs(FLAGS.log_dir  + '/projector') # fix the directory to be created
    generate_metadata_file()
    generate_embeddings()

if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--fake_data', nargs='?', const=True, type=bool,
                        default=False,
                        help='If true, uses fake data for unit testing.')
    parser.add_argument('--max_steps', type=int, default=50,
                        help='Number of steps to run trainer.')
    parser.add_argument('--data_dir', type=str, default='/Users/norman/Documents/workspace/mnist-tensorboard-embeddings/mnist_data',
                        help='Directory for storing input data')
    parser.add_argument('--log_dir', type=str, default='/Users/norman/Documents/workspace/mnist-tensorboard-embeddings/logs',
                        help='Summaries log directory')
    FLAGS, unparsed = parser.parse_known_args()
    tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)

这些是Tensorboard Graph，Histogram和Distribution选项卡的屏幕截图正常工作，但Embeddings选项卡除外：

空白嵌入标签：

我已经从支持GPU的源代码中卸载并重新安装了tensorflow。以下是输出：tensorboard --inspect --logdir=logs：

======================================================================
Processing event files... (this can take a few minutes)
======================================================================

Found event files in:
logs/projector

These tags are in logs/projector:
audio -
histograms
   Embedding
images -
scalars -
tensor

======================================================================

Event statistics for logs/projector:
audio -
graph
   first_step           0
   last_step            0
   max_step             0
   min_step             0
   num_steps            1
   outoforder_steps     []
histograms
   first_step           0
   last_step            19
   max_step             19
   min_step             0
   num_steps            20
   outoforder_steps     []
images -
scalars -
sessionlog:checkpoint -
sessionlog:start -
sessionlog:stop -
tensor
   first_step           0
   last_step            19
   max_step             19
   min_step             0
   num_steps            20
   outoforder_steps     []
======================================================================

Answer 1

我已经解决了这个问题，重新安装pip为：pip install tensorflow-tensorboard的tensorboard，正如GitHub问题所示：https://github.com/tensorflow/tensorflow/issues/10756，由eiennohito打开。

Tensorboard嵌入投影仪空白

1 个答案: