-   type: input id: OS attributes: label: OS Platform and Distribution
    description: placeholder: e.g., Linux Ubuntu 16.04 validations: required:
    false

-   type: input id: Mobile attributes: label: Mobile device description:
    placeholder: e.g., Linux Ubuntu 16.04 validations: required: false

-   type: input id: Python attributes: label: Python version description:
    placeholder: e.g., 3.9 validations: required: false

// TF_NewAttrBuilder() returns an object that you can set attributes on as
// though it were an op. This allows querying properties of that op for
// type-checking purposes like if the op will run on a particular device type.
typedef struct TF_AttrBuilder TF_AttrBuilder;
TF_CAPI_EXPORT extern TF_AttrBuilder* TF_NewAttrBuilder(const char* op_name);
TF_CAPI_EXPORT extern void TF_DeleteAttrBuilder(TF_AttrBuilder* builder);

  mutex_lock l(graph->mu);
  return TF_NewOperationLocked(graph, op_type, oper_name);
}

void TF_SetDevice(TF_OperationDescription* desc, const char* device) {
  desc->node_builder.Device(device);
}

void TF_AddInput(TF_OperationDescription* desc, TF_Output input) {
  desc->node_builder.Input(&input.oper->node, input.index);
}

  opts->opts.validate_colocation_constraints = enable;
}

// Load a Pluggable Device library.
// On success, returns the handle to library in result and return OK from the
// function. Otherwise return nullptr in result and error Status from the
// function.
//
// If `library_filename` has already been loaded, we return a cached handle.
// Device and Kernels/Ops are registered as globals when a library is loaded
// for the first time.

  for _s in _site_packages_dirs:
    _plugin_dir = _os.path.join(_s, "tensorflow-plugins")
    if _os.path.exists(_plugin_dir):
      _ll.load_library(_plugin_dir)
      # Load Pluggable Device Library
      _ll.load_pluggable_device_library(_plugin_dir)

if _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH", ""):
  _ll.load_pluggable_device_library(
      _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH")
  )

			Typeflag: TypeSymlink,
		},
		fm: 0777 | fs.ModeSymlink,
	}, {
		// character device node.
		h: &Header{
			Name:     "dev/null",
			Mode:     0666,
			Size:     0,
			ModTime:  time.Unix(1360578951, 0),
			Typeflag: TypeChar,
		},
		fm: 0666 | fs.ModeDevice | fs.ModeCharDevice,
	}, {
		// block device node.
		h: &Header{
			Name:     "dev/sda",
			Mode:     0660,
			Size:     0,

[CUDA-enabled GPU cards](https://www.tensorflow.org/install/gpu) *(Ubuntu and
Windows)*:

```
$ pip install tensorflow
```

Other devices (DirectX and MacOS-metal) are supported using
[Device Plugins](https://www.tensorflow.org/install/gpu_plugins#available_devices).

A smaller CPU-only package is also available:

```
$ pip install tensorflow-cpu
```

    name = "is_cuda_enabled",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_enabled",
        "@local_config_cuda//cuda:using_config_cuda",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled
# with clang. It does not imply that CUDA support has been enabled.
alias(
    name = "is_cuda_compiler_clang",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_compiler_clang",

			Uid:      010000000,
			ModTime:  time.Unix(0, 0),
			Typeflag: '0',
		}},
	}, {
		// USTAR archive with a regular entry with non-zero device numbers.
		file: "testdata/ustar-file-devs.tar",
		headers: []*Header{{
			Name:     "file",
			Mode:     0644,
			Typeflag: '0',
			ModTime:  time.Unix(0, 0),
			Devmajor: 1,
			Devminor: 1,

        as arg with default value `None` to choose the I/O device for loading
        models and weights.
    *   Update `tf.saved_model.SaveOptions` with
        [`experimental_io_device`](https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/saved_model/SaveOptions?hl=en)
        as arg with default value `None` to choose the I/O device for saving
        models and weights.