passed to the op Both int32 and int64 are allowed and will be converted to
int32 internally.}]>:$sample_indices_or_row_splits,
    Arg<Variadic<TF_I32OrI64Tensor>, [{A list of rank 1 Tensors, indices into the embedding
tables. Both int32 and int64 are allowed and will be converted to
int32 internally.}]>:$embedding_indices,
    Arg<Variadic<TF_F32OrF64Tensor>, [{A list of rank 1 Tensors containing per training

Class <org.gradle.api.distribution.internal.DefaultDistribution> is not annotated (directly or via its package) with @org.gradle.api.NonNullApi in (DefaultDistribution.java:0)
Class <org.gradle.api.distribution.internal.DefaultDistributionContainer> is not annotated (directly or via its package) with @org.gradle.api.NonNullApi in (DefaultDistributionContainer.java:0)

        "description": "RawExtension is used to hold extensions in external versions.\n\nTo use this, make a field which has RawExtension as its type in your external, versioned struct, and Object in your internal struct. You also need to register your various plugin types.\n\n// Internal package:\n\n\ttype MyAPIObject struct {\n\t\truntime.TypeMeta `json:\",inline\"`\n\t\tMyPlugin runtime.Object `json:\"myPlugin\"`\n\t}\n\n\ttype PluginA struct {\n\t\tAOption string `json:\"aOption\"`\n\t}\n\n//...

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        "properties": {
          "apiVersion": {

          apiVersion:
            description: |-
              APIVersion defines the versioned schema of this representation of an object.
              Servers should convert recognized schemas to the latest internal value, and
              may reject unrecognized values.
              More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#resources
            type: string
          kind:

        call can greatly improve performance on TPUs or small models with a
        large Python overhead.
    *   A **major refactoring** of the internals of the Keras Functional API may
        affect code that is relying on certain internal details:
    *   Code that uses `isinstance(x, tf.Tensor)` instead of `tf.is_tensor` when
        checking Keras symbolic inputs/outputs should switch to using

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-----END PGP PUBLIC KEY BLOCK-----

pub    EFEC7EA866CC43AE
uid    scala-xml <scala-internals@googlegroups.com>

-----BEGIN PGP PUBLIC KEY BLOCK-----
Version: BCPG v1.68

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		{"OpenCurrentProcessToken", Func, 0},
		{"OpenProcess", Func, 0},
		{"OpenProcessToken", Func, 0},
		{"Openat", Func, 0},
		{"Overlapped", Type, 0},
		{"Overlapped.HEvent", Field, 0},
		{"Overlapped.Internal", Field, 0},
		{"Overlapped.InternalHigh", Field, 0},
		{"Overlapped.Offset", Field, 0},
		{"Overlapped.OffsetHigh", Field, 0},
		{"PACKET_ADD_MEMBERSHIP", Const, 0},
		{"PACKET_BROADCAST", Const, 0},

// Code generated from _gen/ARM64.rules using 'go generate'; DO NOT EDIT.

package ssa

import "cmd/compile/internal/types"

func rewriteValueARM64(v *Value) bool {
	switch v.Op {
	case OpARM64ADCSflags:
		return rewriteValueARM64_OpARM64ADCSflags(v)
	case OpARM64ADD:
		return rewriteValueARM64_OpARM64ADD(v)
	case OpARM64ADDSflags:
		return rewriteValueARM64_OpARM64ADDSflags(v)
	case OpARM64ADDconst: