4213ac97be
a few other changes. Changes: - Some improvements to convolution by using 32-bit indices by @benoitsteiner. Not all calls converted yet. Also some improvements to pooling as well by @benoitsteiner. - Improvements to sparse matmul CPU implementation by Ashish - Some fixes to warnings by @vrv - Doc fixes to padding by @Yangqing - Some improvements to Tensor wrappers by Eider - Speed up of matrix inverse on CPU by Rasmus - Add an example of doing image inference from a pre-trained model by @petewarden. - fixed formula in mnist example by nodir - Updates to event accumulator by Cassandra - Slight changes to tensor c api by @mrry - Handling of strings in listdiff by Phil - Fix negative fraction-of-queue-full stats by Frank - Type-checking improvement to importer by Yaroslav - logdir recursive search for Tensorboard by @danmane - Session.run() checks for empty graph by Manoj Base CL: 108013706
140 lines
4.7 KiB
Python
140 lines
4.7 KiB
Python
"""Serve TensorFlow summary data to a web frontend.
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This is a simple web server to proxy data from the event_loader to the web, and
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serve static web files.
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import BaseHTTPServer
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import functools
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import os
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import socket
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import SocketServer
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import tensorflow.python.platform
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from tensorflow.python.platform import app
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from tensorflow.python.platform import flags
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from tensorflow.python.platform import logging
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from tensorflow.python.platform import status_bar
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from tensorflow.python.summary import event_accumulator
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from tensorflow.python.summary import event_multiplexer
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from tensorflow.tensorboard import tensorboard_handler
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flags.DEFINE_string('logdir', None, """logdir specifies the directory where
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TensorBoard will look to find TensorFlow event files that it can display.
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TensorBoard will recursively walk the directory structure rooted at logdir,
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looking for .*tfevents.* files.
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You may also pass a comma seperated list of log directories, and TensorBoard
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will watch each directory. You can also assign names to individual log
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directories by putting a colon between the name and the path, as in
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tensorboard --logdir=name1:/path/to/logs/1,name2:/path/to/logs/2
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""")
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flags.DEFINE_boolean('debug', False, 'Whether to run the app in debug mode. '
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'This increases log verbosity to DEBUG.')
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flags.DEFINE_string('host', '127.0.0.1', 'What host to listen to. Defaults to '
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'serving on localhost, set to 0.0.0.0 for remote access.')
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flags.DEFINE_integer('port', 6006, 'What port to serve TensorBoard on.')
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FLAGS = flags.FLAGS
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# How many elements to store per tag, by tag type
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TENSORBOARD_SIZE_GUIDANCE = {
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event_accumulator.COMPRESSED_HISTOGRAMS: 500,
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event_accumulator.IMAGES: 4,
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event_accumulator.SCALARS: 10000,
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event_accumulator.HISTOGRAMS: 1,
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}
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def ParseEventFilesFlag(flag_value):
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"""Parses the logdir flag into a map from paths to run group names.
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The events files flag format is a comma-separated list of path specifications.
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A path specification either looks like 'group_name:/path/to/directory' or
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'/path/to/directory'; in the latter case, the group is unnamed. Group names
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cannot start with a forward slash: /foo:bar/baz will be interpreted as a
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spec with no name and path '/foo:bar/baz'.
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Globs are not supported.
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Args:
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flag_value: A comma-separated list of run specifications.
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Returns:
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A dict mapping directory paths to names like {'/path/to/directory': 'name'}.
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Groups without an explicit name are named after their path. If flag_value
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is None, returns an empty dict, which is helpful for testing things that
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don't require any valid runs.
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"""
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files = {}
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if flag_value is None:
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return files
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for specification in flag_value.split(','):
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# If the spec looks like /foo:bar/baz, then we assume it's a path with a
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# colon.
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if ':' in specification and specification[0] != '/':
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# We split at most once so run_name:/path:with/a/colon will work.
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run_name, path = specification.split(':', 1)
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else:
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run_name = None
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path = specification
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files[path] = run_name
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return files
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class ThreadedHTTPServer(SocketServer.ThreadingMixIn,
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BaseHTTPServer.HTTPServer):
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"""A threaded HTTP server."""
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daemon = True
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def main(unused_argv=None):
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# Change current working directory to tensorflow/'s parent directory.
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server_root = os.path.join(os.path.dirname(__file__),
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os.pardir, os.pardir)
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os.chdir(server_root)
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if FLAGS.debug:
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logging.set_verbosity(logging.DEBUG)
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if not FLAGS.logdir:
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logging.error('A logdir must be specified. Run `tensorboard --help` for '
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'details and examples.')
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return -1
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if FLAGS.debug:
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logging.info('Starting TensorBoard in directory %s', os.getcwd())
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path_to_run = ParseEventFilesFlag(FLAGS.logdir)
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multiplexer = event_multiplexer.AutoloadingMultiplexer(
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path_to_run=path_to_run, interval_secs=60,
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size_guidance=TENSORBOARD_SIZE_GUIDANCE)
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multiplexer.AutoUpdate(interval=30)
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factory = functools.partial(tensorboard_handler.TensorboardHandler,
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multiplexer)
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try:
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server = ThreadedHTTPServer((FLAGS.host, FLAGS.port), factory)
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except socket.error:
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logging.error('Tried to connect to port %d, but that address is in use.',
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FLAGS.port)
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return -2
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status_bar.SetupStatusBarInsideGoogle('TensorBoard', FLAGS.port)
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print('Starting TensorBoard on port %d' % FLAGS.port)
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print('(You can navigate to http://localhost:%d)' % FLAGS.port)
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server.serve_forever()
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if __name__ == '__main__':
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app.run()
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