Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
of the Software, and to permit persons to whom the Software is furnished to do
so, subject to the following conditions:

# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

#!/bin/bash
# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,

#!/usr/bin/env bash
#
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

 *
 */
public interface SMBSigningDigest {

    /**
     * Performs MAC signing of the SMB. This is done as follows.
     * The signature field of the SMB is overwritten with the sequence number;
     * The MD5 digest of the MAC signing key + the entire SMB is taken;
     * The first 8 bytes of this are placed in the signature field.
     *
     * @param data
     *            The data.
     * @param offset

#!/bin/bash
# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

        dstIndex += writeHeaderWireFormat( dst, dstIndex );
        dstIndex += writeAndXWireFormat( dst, dstIndex );
        length = dstIndex - start;

        if( digest != null ) {
            digest.sign( dst, headerStart, length, this, response );
        }

        return length;
    }

    /*
     * We overload this because we want readAndXWireFormat to

// Copyright 2022 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// This file encapsulates some of the odd characteristics of the
// Loong64 (LoongArch64) instruction set, to minimize its interaction
// with the core of the assembler.

package arch

import (
	"cmd/internal/obj"
	"cmd/internal/obj/loong64"
)

func jumpLoong64(word string) bool {

COPYRIGHT

All contributions by the University of California:

Copyright (c) 2014, The Regents of the University of California (Regents)
All rights reserved.

All other contributions:

Copyright (c) 2014, the respective contributors
All rights reserved.

Caffe uses a shared copyright model: each contributor holds copyright over
their contributions to Caffe. The project versioning records all such