USAGE:
  mc batch COMMAND [COMMAND FLAGS | -h] [ARGUMENTS...]

COMMANDS:
  generate  generate a new batch job definition
  start     start a new batch job
  list, ls  list all current batch jobs
  status    summarize job events on MinIO server in real-time
  describe  describe job definition for a job
```

### Generate a job yaml
```
mc batch generate alias/ replicate
```

See [Gradle runtimes](runtimes.md) for a list of these runtimes and more details.

## Build state model

As Gradle executes, it acts on various pieces of the build definition, such as each project in the build.
Gradle tracks the state of each piece and transitions each piece through its lifecycle as the build runs.

All of these can be accessed via Prometheus dashboard. A sample list of exposed metrics along with their definition is available on our public demo server at

```sh
curl https://play.min.io/minio/v2/metrics/cluster
```

### List of metrics reported Cluster and Bucket level

* There are 4 minio distributed instances created by default. You can add more MinIO services (up to total 16) to your MinIO Compose deployment. To add a service
  * Replicate a service definition and change the name of the new service appropriately.
  * Update the command section in each service.
  * Add a new MinIO server instance to the upstream directive in the Nginx configuration file.

autogenerated from the registered Op and API definitions.

To regenerate them, run the script in this directory, `update_cpp_ops.sh`, with
no arguments. This script will overwrite the existing ops in-place at
***tensorflow/c/experimental/ops/\*_ops.{cc,h}***.

Run this `update_cpp_ops.sh` script when Op definitions change in the registry.

    -   Uses `pycpp.sh`, `code_check_changed_files.sh`

These "env" files match up with an environment matrix that roughly covers:

-   Different Python versions
-   Linux, MacOS, and Windows machines (these pool definitions are internal)
-   x86 and arm64
-   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs

## How to Test Your Changes to TensorFlow

You may check how your changes will affect TensorFlow by: