nlp_server_docker_run {NLPclient} | R Documentation |
Create the Docker Run Command
Description
This function helps to create the docker run command which can be copied into the terminal (Unix) or docker toolbox (Windows).
Usage
nlp_server_docker_run(name = "coreNLP", docker = "schwe/corenlp",
memory = "-mx8g", threads = NA, port = 9000L,
status_port = 9000L, timeout = 15000L, strict = FALSE,
quiet = FALSE, ssl = FALSE,
key = "edu/stanford/nlp/pipeline/corenlp.jks", username = "",
password = "", annotators = "all", preload = "",
server_properties = "", default_properties = "", cleanup = TRUE)
Arguments
name |
a character string giving the name of the docker container. |
docker |
a character string giving the image name. |
memory |
a character string giving the java memory options. |
threads |
an integer giving the number of threads to be used. The default is |
port |
an integer giving the server port. |
status_port |
an integer giving the port to run the liveness and readiness server on. |
timeout |
an integer giving the maximum amount of time, in milliseconds, to wait for an annotation to finish before cancelling it. |
strict |
a logical controlling whether server strictly follows the |
quiet |
a logical controlling whether the incoming requests are logged to |
ssl |
a logical controlling whether an |
key |
a character string giving the classpath or filepath to the |
username |
a character string giving the username of the server. |
password |
a character string giving the password of the server. |
annotators |
a character string giving the default annotators (e.g. |
preload |
a character string giving the set of annotators to warm up in the cache when the server boots up. |
server_properties |
a character giving the path to the default properties. |
default_properties |
a character string giving the server properties, to be written into the file |
cleanup |
a logical giving if docker should automatically clean up the container and remove the file system when the container exits. |
Value
A character string which can be copied into the terminal (or docker toolbox) to start the coreNLP
server.
Examples
nlp_server_docker_run(memory = "-mx6g")