let summary = "Outputs random values from a uniform distribution.";

  let description = [{
The generated values follow a uniform distribution in the range `[0, 1)`. The
lower bound 0 is included in the range, while the upper bound 1 is excluded.
  }];

  let arguments = (ins
    Arg<TF_I32OrI64Tensor, [{The shape of the output tensor.}]>:$shape,

    DefaultValuedOptionalAttr<I64Attr, "0">:$seed,

            "type": "string"
          },
          "remainingItemCount": {

"description": "NodeAffinityPolicy indicates how we will treat Pod's nodeAffinity/nodeSelector when calculating pod topology spread skew. Options are: - Honor: only nodes matching nodeAffinity/nodeSelector are included in the calculations. - Ignore: nodeAffinity/nodeSelector are ignored. All nodes are included in the calculations.\n\nIf this value is nil, the behavior is equivalent to the Honor policy. This is a beta-level feature default enabled by the NodeInclusionPolicyInPodTopologySpread feature flag.",...

Class <org.gradle.api.internal.artifacts.ivyservice.resolveengine.excludes.factories.DelegatingExcludeFactory> is not annotated (directly or via its package) with @org.gradle.api.NonNullApi in (DelegatingExcludeFactory.java:0)

### Known Caveats

* `tf.lite`
    * when converter flag "_experimenal_use_buffer_offset" is enabled, additional metadata is automatically excluded from the generated model. The behaviour is the same as "exclude_conversion_metadata" is set
    * If the model is larger than 2GB, then we also require "exclude_conversion_metadata" flag to be set