lt
/tools/node/bin/lt -> /tools/node/lib/node_modules/localtunnel/bin/client + localtunnel@1.9.1 updated 1 package in 2.558s your url is: https://strong-rabbit-23.localtunnel.me your url is: https://spicy-cougar-27.localtunnel.me /tools/node/lib/node_modules/localtunnel/bin/client:65 throw err; ^ Error: connection refused: localtunnel.me:41522 (check your firewall settings) at Socket.<anonymous> (/tools/node/lib/node_modules/localtunnel/lib/TunnelCluster.js:47:32) at emitOne (events.js:116:13) at Socket.emit (events.js:211:7) at emitErrorNT (internal/streams/destroy.js:64:8) at _combinedTickCallback (internal/process/next_tick.js:138:11) at process._tickCallback (internal/process/next_tick.js:180:9) your url is: https://perfect-fox-89.localtunnel.me your url is: https://horrible-panda-62.localtunnel.me /tools/node/lib/node_modules/localtunnel/bin/client:65 throw err; ^ Error: connection refused: localtunnel.me:38245 (check your firewall settings) at Socket.<anonymous> (/tools/node/lib/node_modules/localtunnel/lib/TunnelCluster.js:47:32) at emitOne (events.js:116:13) at Socket.emit (events.js:211:7) at emitErrorNT (internal/streams/destroy.js:64:8) at _combinedTickCallback (internal/process/next_tick.js:138:11) at process._tickCallback (internal/process/next_tick.js:180:9) your url is: https://tender-wombat-80.localtunnel.me your url is: https://silent-mayfly-4.localtunnel.me your url is: https://lovely-pig-5.localtunnel.me your url is: https://stupid-ladybug-4.localtunnel.me /tools/node/lib/node_modules/localtunnel/bin/client:65 throw err; ^ Error: connection refused: localtunnel.me:34464 (check your firewall settings) at Socket.<anonymous> (/tools/node/lib/node_modules/localtunnel/lib/TunnelCluster.js:47:32) at emitOne (events.js:116:13) at Socket.emit (events.js:211:7) at emitErrorNT (internal/streams/destroy.js:64:8) at _combinedTickCallback (internal/process/next_tick.js:138:11) at process._tickCallback (internal/process/next_tick.js:180:9)
FileNotFoundError latest_net_G.pth
dataset [AlignedDataset] was created initialize network with normal model [Pix2PixModel] was created loading the model from log_train/sub_20190130_1324/pix2pix_popRam/latest_net_G.pth Traceback (most recent call last): File "pytorch-CycleGAN-and-pix2pix/test.py", line 47, in <module> model.setup(opt) # regular setup: load and print networks; create schedulers File "/content/pytorch-CycleGAN-and-pix2pix/models/base_model.py", line 88, in setup self.load_networks(load_suffix) File "/content/pytorch-CycleGAN-and-pix2pix/models/base_model.py", line 187, in load_networks state_dict = torch.load(load_path, map_location=str(self.device)) File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 365, in load f = open(f, 'rb') FileNotFoundError: [Errno 2] No such file or directory: 'log_train/sub_20190130_1324/pix2pix_popRam/latest_net_G.pth'
これかな?
parser.add_argument('--save_latest_freq', type=int, default=5000, help='frequency of saving the latest results')
train.py if total_iters % opt.save_latest_freq == 0: # cache our latest model every <save_latest_freq> iterations print('saving the latest model (epoch %d, total_iters %d)' % (epoch, total_iters)) save_suffix = 'iter_%d' % total_iters if opt.save_by_iter else 'latest' model.save_networks(save_suffix)
これで、5epochごとに、saveしている。
parser.add_argument('--save_epoch_freq', type=int, default=5, help='frequency of saving checkpoints at the end of epochs')
tensorboard --help
$ tensorboard --help usage: tensorboard [-h] [--helpfull] [--logdir PATH] [--host ADDR] [--port PORT] [--purge_orphaned_data BOOL] [--reload_interval SECONDS] [--db URI] [--db_import] [--db_import_use_op] [--inspect] [--tag TAG] [--event_file PATH] [--path_prefix PATH] [--window_title TEXT] [--max_reload_threads COUNT] [--reload_task TYPE] [--samples_per_plugin SAMPLES_PER_PLUGIN] [--master_tpu_unsecure_channel ADDR] [--debugger_data_server_grpc_port PORT] [--debugger_port PORT] TensorBoard is a suite of web applications for inspecting and understanding your TensorFlow runs and graphs. https://github.com/tensorflow/tensorboard optional arguments: -h, --help show this help message and exit --helpfull show full help message and exit --logdir PATH Directory where TensorBoard will look to find TensorFlow event files that it can display. TensorBoard will recursively walk the directory structure rooted at logdir, looking for .*tfevents.* files. You may also pass a comma separated list of log directories, and TensorBoard will watch each directory. You can also assign names to individual log directories by putting a colon between the name and the path, as in: `tensorboard --logdir=name1:/path/to/logs/1,name2:/path/to/logs/2` --host ADDR What host to listen to. Defaults to serving on all interfaces. Other commonly used values are 127.0.0.1 (localhost) and :: (for IPv6). --port PORT Port to serve TensorBoard on. Pass 0 to request an unused port selected by the operating system. (default: 6006) --purge_orphaned_data BOOL Whether to purge data that may have been orphaned due to TensorBoard restarts. Setting --purge_orphaned_data=False can be used to debug data disappearance. (default: True) --reload_interval SECONDS How often the backend should load more data, in seconds. Set to 0 to load just once at startup and a negative number to never reload at all. Not relevant for DB read-only mode. (default: 5.0) --db URI [experimental] sets SQL database URI and enables DB backend mode, which is read-only unless --db_import is also passed. --db_import [experimental] enables DB read-and-import mode, which in combination with --logdir imports event files into a DB backend on the fly. The backing DB is temporary unless --db is also passed to specify a DB path to use. --db_import_use_op [experimental] in combination with --db_import, if passed, use TensorFlow's import_event() op for importing event data, otherwise use TensorBoard's own sqlite ingestion logic. --inspect Prints digests of event files to command line. This is useful when no data is shown on TensorBoard, or the data shown looks weird. Example usage: `tensorboard --inspect --logdir mylogdir --tag loss` See tensorflow/python/summary/event_file_inspector.py for more info. --tag TAG tag to query for; used with --inspect --event_file PATH The particular event file to query for. Only used if --inspect is present and --logdir is not specified. --path_prefix PATH An optional, relative prefix to the path, e.g. "/path/to/tensorboard". resulting in the new base url being located at localhost:6006/path/to/tensorboard under default settings. A leading slash is required when specifying the path_prefix, however trailing slashes can be omitted. The path_prefix can be leveraged for path based routing of an elb when the website base_url is not available e.g. "example.site.com/path/to/tensorboard/". --window_title TEXT changes title of browser window --max_reload_threads COUNT The max number of threads that TensorBoard can use to reload runs. Not relevant for db read-only mode. Each thread reloads one run at a time. (default: 1) --reload_task TYPE [experimental] The mechanism to use for the background data reload task. The default "auto" option will conditionally use threads for legacy reloading and a child process for DB import reloading. The "process" option is only useful with DB import mode. The "blocking" option will block startup until reload finishes, and requires --load_interval=0. (default: auto) --samples_per_plugin SAMPLES_PER_PLUGIN An optional comma separated list of plugin_name=num_samples pairs to explicitly specify how many samples to keep per tag for that plugin. For unspecified plugins, TensorBoard randomly downsamples logged summaries to reasonable values to prevent out- of-memory errors for long running jobs. This flag allows fine control over that downsampling. Note that 0 means keep all samples of that type. For instance "scalars=500,images=0" keeps 500 scalars and all images. Most users should not need to set this flag. profile plugin: --master_tpu_unsecure_channel ADDR IP address of "master tpu", used for getting streaming trace data through tpu profiler analysis grpc. The grpc channel is not secured. debugger plugin: --debugger_data_server_grpc_port PORT The port at which the non-interactive debugger data server should receive debugging data via gRPC from one or more debugger-enabled TensorFlow runtimes. No debugger plugin or debugger data server will be started if this flag is not provided. This flag differs from the `--debugger_port` flag in that it starts a non-interactive mode. It is for use with the "health pills" feature of the Graph Dashboard. This flag is mutually exclusive with `--debugger_port`. --debugger_port PORT The port at which the interactive debugger data server (to be started by the debugger plugin) should receive debugging data via gRPC from one or more debugger- enabled TensorFlow runtimes. No debugger plugin or debugger data server will be started if this flag is not provided. This flag differs from the `--debugger_data_server_grpc_port` flag in that it starts an interactive mode that allows user to pause at selected nodes inside a TensorFlow Graph or between Session.runs. It is for use with the interactive Debugger Dashboard. This flag is mutually exclusive with `--debugger_data_server_grpc_port`.