# runai tensorflow exec

execute a command in a tf training workload

```
runai tensorflow exec [WORKLOAD_NAME] [flags]
```

## Examples

```
# Execute bash in the workload's main worker
runai training tf exec tf-01 --tty --stdin -- /bin/bash 

# Execute ls command in the workload's main worker
runai training tf exec tf-01 -- ls

# Execute a command in a specific the workload's worker
runai training tf exec tf-01 --pod tf-01-worker-1 -- nvidia-smi
```

## Options

```
  -c, --container string               Container name for log extraction
  -h, --help                           help for exec
      --pod string                     Workload pod ID for log extraction, default: master (0-0) if exists, else first worker by id
      --pod-running-timeout duration   Pod check for running state timeout.
  -p, --project string                 Specify the project to which the command applies. By default, commands apply to the default project. To change the default project use ‘runai config project <project name>’
  -i, --stdin                          Pass stdin to the container
  -t, --tty                            Stdin is a TTY
      --wait-timeout duration          Timeout for waiting for workload to be ready for log streaming
```

## Options inherited from parent commands

```
      --config-file string   config file name; can be set by environment variable RUNAI_CLI_CONFIG_FILE (default "config.json")
      --config-path string   config path; can be set by environment variable RUNAI_CLI_CONFIG_PATH
  -d, --debug                enable debug mode
  -q, --quiet                enable quiet mode, suppress all output except error messages
      --verbose              enable verbose mode
```

## SEE ALSO

* [runai tensorflow](https://run-ai-docs.nvidia.com/self-hosted/2.21/reference/cli/runai/runai_tensorflow) - alias for tensorflow management