【发布时间】：2020-07-18 11:27:48
【问题描述】：
我正在尝试对 mnist 进行通用分析，如下所示。
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
import tensorflow as tf
# The MNIST dataset has 10 classes, representing the digits 0 through 9.
NUM_CLASSES = 10
# The MNIST images are always 28x28 pixels.
IMAGE_SIZE = 28
IMAGE_PIXELS = IMAGE_SIZE * IMAGE_SIZE
def inference(images, hidden1_units, hidden2_units):
"""Build the MNIST model up to where it may be used for inference.
Args:
images: Images placeholder, from inputs().
hidden1_units: Size of the first hidden layer.
hidden2_units: Size of the second hidden layer.
Returns:
softmax_linear: Output tensor with the computed logits.
"""
# Hidden 1
with tf.compat.v1.name_scope('hidden1'):
weights = tf.Variable(
tf.random.truncated_normal(
[IMAGE_PIXELS, hidden1_units],
stddev=1.0 / math.sqrt(float(IMAGE_PIXELS))), name='weights')
biases = tf.Variable(tf.zeros([hidden1_units]),
name='biases')
hidden1 = tf.nn.relu(tf.matmul(images, weights) + biases)
# Hidden 2
with tf.compat.v1.name_scope('hidden2'):
weights = tf.Variable(
tf.random.truncated_normal(
[hidden1_units, hidden2_units],
stddev=1.0 / math.sqrt(float(hidden1_units))), name='weights')
biases = tf.Variable(tf.zeros([hidden2_units]),
name='biases')
hidden2 = tf.nn.relu(tf.matmul(hidden1, weights) + biases)
# Linear
with tf.compat.v1.name_scope('softmax_linear'):
weights = tf.Variable(
tf.random.truncated_normal(
[hidden2_units, NUM_CLASSES],
stddev=1.0 / math.sqrt(float(hidden2_units))), name='weights')
biases = tf.Variable(tf.zeros([NUM_CLASSES]),
name='biases')
logits = tf.matmul(hidden2, weights) + biases
return logits
def loss(logits, labels):
"""Calculates the loss from the logits and the labels.
Args:
logits: Logits tensor, float - [batch_size, NUM_CLASSES].
labels: Labels tensor, int32 - [batch_size].
Returns:
loss: Loss tensor of type float.
"""
labels = tf.cast(labels, dtype=tf.int64)
return tf.compat.v1.losses.sparse_softmax_cross_entropy(
labels=labels, logits=logits)
def training(loss, learning_rate):
"""Sets up the training Ops.
Creates a summarizer to track the loss over time in TensorBoard.
Creates an optimizer and applies the gradients to all trainable variables.
The Op returned by this function is what must be passed to the
`sess.run()` call to cause the model to train.
Args:
loss: Loss tensor, from loss().
learning_rate: The learning rate to use for gradient descent.
Returns:
train_op: The Op for training.
"""
# Add a scalar summary for the snapshot loss.
tf.compat.v1.summary.scalar('loss', loss)
# Create the gradient descent optimizer with the given learning rate.
optimizer = tf.compat.v1.train.GradientDescentOptimizer(learning_rate)
# Create a variable to track the global step.
global_step = tf.Variable(0, name='global_step', trainable=False)
# Use the optimizer to apply the gradients that minimize the loss
# (and also increment the global step counter) as a single training step.
train_op = optimizer.minimize(loss, global_step=global_step)
return train_op
def evaluation(logits, labels):
"""Evaluate the quality of the logits at predicting the label.
Args:
logits: Logits tensor, float - [batch_size, NUM_CLASSES].
labels: Labels tensor, int32 - [batch_size], with values in the
range [0, NUM_CLASSES).
Returns:
A scalar int32 tensor with the number of examples (out of batch_size)
that were predicted correctly.
"""
# For a classifier model, we can use the in_top_k Op.
# It returns a bool tensor with shape [batch_size] that is true for
# the examples where the label is in the top k (here k=1)
# of all logits for that example.
correct = tf.nn.in_top_k(predictions=logits, targets=labels, k=1)
# Return the number of true entries.
return tf.reduce_sum(input_tensor=tf.cast(correct, tf.int32))
我在 Spyder 中运行代码；运行良好。
然后，我把这个命令行放在 Anaconda Prompt 中。
tensorboard --logdir="C:/Users/ryans/mnist_tutorial/"
我在命令提示符中看到以下消息。
(base) C:\Users\ryans>tensorboard --logdir="C:/Users/ryans/mnist_tutorial/"
C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
Traceback (most recent call last):
File "C:\Users\ryans\Anaconda3\Scripts\tensorboard-script.py", line 10, in <module>
sys.exit(run_main())
File "C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\main.py", line 64, in run_main
app.run(tensorboard.main, flags_parser=tensorboard.configure)
File "C:\Users\ryans\Anaconda3\lib\site-packages\absl\app.py", line 299, in run
_run_main(main, args)
File "C:\Users\ryans\Anaconda3\lib\site-packages\absl\app.py", line 250, in _run_main
sys.exit(main(argv))
File "C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\program.py", line 228, in main
server = self._make_server()
File "C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\program.py", line 309, in _make_server
self.assets_zip_provider)
File "C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\backend\application.py", line 161, in standard_tensorboard_wsgi
reload_task)
File "C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\backend\application.py", line 194, in TensorBoardWSGIApp
return TensorBoardWSGI(plugins, path_prefix)
File "C:\Users\ryans\Anaconda3\lib\site-packages\tensorboard\backend\application.py", line 245, in __init__
raise ValueError('Duplicate plugins for name %s' % plugin.plugin_name)
ValueError: Duplicate plugins for name projector
(base) C:\Users\ryans>
这是问题吗？在过去的几天里，我一直试图让这个工作。无论我做什么，我都无法让它工作。我想打开浏览器，输入“http://localhost:6006/”并查看 TensorBoard。我现在看到的只是一条消息，上面写着“无法连接”。想法？
更新：我卸载并重新安装了 tensorflow。然后，我运行了诊断脚本，得到了这个.....
### Diagnostics
<details>
<summary>Diagnostics output</summary>
``````
--- check: autoidentify
INFO: diagnose_tensorboard.py source unavailable
--- check: general
INFO: sys.version_info: sys.version_info(major=3, minor=7, micro=5, releaselevel='final', serial=0)
INFO: os.name: nt
INFO: os.uname(): N/A
INFO: sys.getwindowsversion(): sys.getwindowsversion(major=10, minor=0, build=17763, platform=2, service_pack='')
--- check: package_management
INFO: has conda-meta: True
INFO: $VIRTUAL_ENV: None
--- check: installed_packages
INFO: installed: tensorboard==2.0.2
INFO: installed: tensorflow==2.0.0
INFO: installed: tensorflow-estimator==2.0.1
--- check: tensorboard_python_version
INFO: tensorboard.version.VERSION: '2.0.2'
--- check: tensorflow_python_version
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\ryans\Anaconda3\lib\site-packages\tensorflow\python\framework\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
INFO: tensorflow.__version__: '1.14.0'
INFO: tensorflow.__git_version__: 'unknown'
--- check: tensorboard_binary_path
INFO: which tensorboard: b'C:\\Users\\ryans\\Anaconda3\\Scripts\\tensorboard.exe\r\nC:\\Users\\ryans\\AppData\\Local\\Programs\\Python\\Python38\\Scripts\\tensorboard.exe\r\n'
--- check: addrinfos
socket.has_ipv6 = True
socket.AF_UNSPEC = <AddressFamily.AF_UNSPEC: 0>
socket.SOCK_STREAM = <SocketKind.SOCK_STREAM: 1>
socket.AI_ADDRCONFIG = <AddressInfo.AI_ADDRCONFIG: 1024>
socket.AI_PASSIVE = <AddressInfo.AI_PASSIVE: 1>
Loopback flags: <AddressInfo.AI_ADDRCONFIG: 1024>
Loopback infos: [(<AddressFamily.AF_INET6: 23>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('::1', 0, 0, 0)), (<AddressFamily.AF_INET: 2>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('127.0.0.1', 0))]
Wildcard flags: <AddressInfo.AI_PASSIVE: 1>
Wildcard infos: [(<AddressFamily.AF_INET6: 23>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('::', 0, 0, 0)), (<AddressFamily.AF_INET: 2>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('0.0.0.0', 0))]
--- check: readable_fqdn
INFO: socket.getfqdn(): 'LAPTOP-CEDUMII6.nyc.rr.com'
--- check: stat_tensorboardinfo
INFO: directory: C:\Users\ryans\AppData\Local\Temp\.tensorboard-info
INFO: .tensorboard-info directory does not exist
--- check: source_trees_without_genfiles
INFO: tensorboard_roots (1): ['C:\\Users\\ryans\\Anaconda3\\lib\\site-packages']; bad_roots (0): []
--- check: full_pip_freeze
INFO: pip freeze --all:
absl-py==0.9.0
alabaster==0.7.12
altair==4.0.1
anaconda-client==1.7.2
anaconda-navigator==1.9.12
argh==0.26.2
asn1crypto==1.3.0
astor==0.8.1
astroid==2.3.3
atomicwrites==1.3.0
attrs==19.3.0
Automat==20.2.0
autopep8==1.4.4
Babel==2.8.0
backcall==0.1.0
backports.functools-lru-cache==1.6.1
backports.tempfile==1.0
backports.weakref==1.0.post1
bcrypt==3.1.7
beautifulsoup4==4.8.2
bleach==3.1.0
blis==0.4.1
boto3==1.11.14
botocore==1.14.14
bs4==0.0.1
cachetools==4.0.0
catalogue==1.0.0
catboost==0.22
certifi==2019.11.28
cffi==1.14.0
chardet==3.0.4
chart-studio==1.0.0
click==7.1.1
cloudpickle==1.3.0
clyent==1.2.2
colorama==0.3.9
colorlover==0.3.0
conda==4.8.3
conda-build==3.18.11
conda-package-handling==1.6.0
conda-verify==3.4.2
configparser==4.0.2
constantly==15.1.0
crayons==0.3.0
cryptography==2.8
cssselect==1.1.0
cufflinks==0.17.0
cycler==0.10.0
cymem==2.0.3
decorator==4.4.2
defusedxml==0.6.0
diff-match-patch==20181111
dill==0.3.1.1
doc2text==0.2.4
docutils==0.15.2
docx2txt==0.8
eli5==0.10.1
en-core-web-sm==2.2.5
entrypoints==0.3
feedparser==5.2.1
filelock==3.0.12
finance==0.2502
flake8==3.7.9
funcy==1.14
future==0.18.2
futures==3.1.1
fuzzywuzzy==0.18.0
gast==0.2.2
gensim==3.8.1
geographiclib==1.50
geopy==1.21.0
glob2==0.7
google-api-python-client==1.7.11
google-auth==1.10.0
google-auth-httplib2==0.0.3
google-auth-oauthlib==0.4.1
google-pasta==0.1.8
google-search-results==1.7.1
googleapis-common-protos==1.51.0
goslate==1.5.1
graphviz==0.13.2
grpcio==1.27.2
gspread==3.2.0
h5py==2.8.0
helpdev==0.6.10
httplib2==0.15.0
hyperlink==19.0.0
idna==2.9
imagesize==1.2.0
imbalanced-learn==0.6.2
imblearn==0.0
importlib-metadata==1.5.0
imutils==0.5.3
incremental==17.5.0
intervaltree==3.0.2
ipykernel==5.1.4
ipython==7.13.0
ipython-genutils==0.2.0
ipywidgets==7.5.1
isort==4.3.21
jedi==0.14.1
Jinja2==2.11.1
jmespath==0.9.4
joblib==0.14.1
json5==0.9.3
jsonschema==3.2.0
jupyter-client==6.1.2
jupyter-core==4.6.3
jupyterlab==1.2.6
jupyterlab-server==1.1.0
Keras==2.3.1
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.0
keyring==21.1.0
kiwisolver==1.1.0
langdetect==1.0.8
lazy-object-proxy==1.4.3
libarchive-c==2.8
lightgbm==2.3.1
Markdown==3.1.1
MarkupSafe==1.1.1
matplotlib==3.2.1
mccabe==0.6.1
menuinst==1.4.16
mime==0.1.0
mistune==0.8.4
mkl-fft==1.0.6
mkl-random==1.0.1
mlxtend==0.17.2
mpl-finance==0.10.0
mplfinance==0.12.3a3
multitasking==0.0.9
murmurhash==1.0.2
mysql==0.0.2
mysqlclient==1.4.6
navigator-updater==0.2.1
nbconvert==5.6.1
nbformat==5.0.4
notebook==6.0.3
numpy==1.18.2
numpy-financial==1.0.0
numpydoc==0.9.2
oauth2client==4.1.3
oauthlib==3.1.0
olefile==0.46
opencv-python==4.2.0.32
opt-einsum==3.1.0
packaging==20.3
pandas==1.0.3
pandas-datareader==0.8.1
pandocfilters==1.4.2
paramiko==2.7.1
parsel==1.5.2
parso==0.5.2
pathtools==0.1.2
pdfminer==20191125
pdfminer.six==20200124
pexpect==4.8.0
pickleshare==0.7.5
Pillow==7.0.0
pip==20.0.2
pipupgrade==1.7.1
pkginfo==1.5.0.1
plac==1.1.3
plotly==4.5.4
pluggy==0.13.1
preshed==3.0.2
prometheus-client==0.7.1
promise==2.3
prompt-toolkit==3.0.4
Protego==0.1.16
protobuf==3.11.4
psutil==5.7.0
psycopg2==2.8.4
ptyprocess==0.6.0
py4j==0.10.7
pyasn1==0.4.8
pyasn1-modules==0.2.7
pycodestyle==2.5.0
pycosat==0.6.3
pycparser==2.20
pycryptodome==3.9.4
PyDictionary==1.5.2
PyDispatcher==2.0.5
pydocstyle==5.0.1
pydot==1.4.1
pyflakes==2.1.1
pygame==1.9.6
Pygments==2.6.1
PyHamcrest==2.0.2
pyLDAvis==2.1.2
pylint==2.4.4
Pympler==0.8
PyNaCl==1.3.0
pyOpenSSL==19.1.0
pyparsing==2.4.6
PyPDF2==1.26.0
pypyodbc==1.3.4
PyQt5==5.12.3
PyQt5-sip==12.7.0
PyQtWebEngine==5.12.1
pyrsistent==0.16.0
PySocks==1.7.1
pyspark==2.4.5
pytesseract==0.3.2
python-dateutil==2.8.1
python-jsonrpc-server==0.3.4
python-language-server==0.31.9
pytz==2019.3
pywin32==227
pywin32-ctypes==0.2.0
pywinpty==0.5.7
PyYAML==5.3.1
pyzmq==18.1.1
QDarkStyle==2.8
QtAwesome==0.7.0
qtconsole==4.7.2
QtPy==1.9.0
queuelib==1.5.0
requests==2.23.0
requests-oauthlib==1.3.0
retrying==1.3.3
rope==0.16.0
rsa==4.0
Rtree==0.9.3
ruamel-yaml==0.15.87
s3transfer==0.3.3
scikit-learn==0.22.2.post1
scipy==1.1.0
Scrapy==1.8.0
seaborn==0.10.0
selenium==3.141.0
Send2Trash==1.5.0
service-identity==18.1.0
setuptools==46.1.3.post20200330
Shapely==1.7.0
simplified-scrapy==1.0.111
six==1.14.0
sklearn==0.0
smart-open==1.9.0
snowballstemmer==2.0.0
sortedcontainers==2.1.0
soupsieve==2.0
spacy==2.2.3
Sphinx==2.4.4
sphinxcontrib-applehelp==1.0.2
sphinxcontrib-devhelp==1.0.2
sphinxcontrib-htmlhelp==1.0.3
sphinxcontrib-jsmath==1.0.1
sphinxcontrib-qthelp==1.0.3
sphinxcontrib-serializinghtml==1.1.4
spyder==4.0.1
spyder-kernels==1.8.1
srsly==1.0.1
tabulate==0.8.6
TBB==0.1
tensorboard==2.0.2
tensorflow==2.0.0
tensorflow-datasets==2.0.0
tensorflow-estimator==2.0.1
tensorflow-hub==0.8.0
tensorflow-metadata==0.21.1
termcolor==1.1.0
terminado==0.8.3
testpath==0.4.4
textblob==0.15.3
thinc==7.3.1
torch==1.4.0
tornado==6.0.4
tqdm==4.44.1
traitlets==4.3.3
Twisted==19.10.0
typed-ast==1.4.0
ujson==1.35
uritemplate==3.0.1
urllib3==1.25.8
urlopen==1.0.0
vaderSentiment==3.2.1
vega-datasets==0.8.0
w3lib==1.21.0
wasabi==0.6.0
watchdog==0.10.2
wcwidth==0.1.9
webdriver-manager==2.3.0
webencodings==0.5.1
Werkzeug==1.0.1
wheel==0.34.2
widgetsnbextension==3.5.1
win-inet-pton==1.1.0
wincertstore==0.2
wordcloud==1.6.0
wordnet==0.0.1b2
wrapt==1.12.1
xgboost==1.0.2
xlutils==2.0.0
xmltodict==0.12.0
yapf==0.29.0
yellowbrick==1.0.1
yfinance==0.1.54
zipp==2.2.0
zope.interface==4.7.1
``````
</details>
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标签： python python-3.x tensorflow tensorflow2.0 tensorboard