// Copyright (c) 2015-2021 MinIO, Inc.
//
// This file is part of MinIO Object Storage stack
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful

// Copyright (c) 2015-2021 MinIO, Inc.
//
// This file is part of MinIO Object Storage stack
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful

- 'KubeSchedulerConfiguration' which used to be under GroupVersion 'componentconfig/v1alpha1',
is now under 'kubescheduler.config.k8s.io/v1alpha1'.  ([#66916](https://github.com/kubernetes/kubernetes/pull/66916), [@dixudx](https://github.com/dixudx)) Courtesy of SIG Cluster Lifecycle, SIG Scheduling, and SIG Testing

///

## Múltiplos modelos

Aqui está uma ideia geral de como os modelos poderiam parecer com seus campos de senha e os lugares onde são usados:

{* ../../docs_src/extra_models/tutorial001.py hl[9,11,16,22,24,29:30,33:35,40:41] *}

### Sobre `**user_in.dict()`

#### O `.dict()` do Pydantic

`user_in` é um modelo Pydantic da classe `UserIn`.

// Copyright (c) 2015-2024 MinIO, Inc.
//
// This file is part of MinIO Object Storage stack
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful

/*
 * © 2025 CodeLibs, Inc.
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of

            assertEquals(encoded, decoded);
            assertArrayEquals(ciphers, decodedContext.getCiphers());
        }

        @Test
        @DisplayName("Should preserve cipher order")
        void testCipherOrderPreservation() throws SMBProtocolDecodingException {
            int[] ciphers = { 5, 3, 1, 4, 2 };

// Copyright (c) 2015-2022 MinIO, Inc.
//
// This file is part of MinIO Object Storage stack
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful

// Copyright (c) 2015-2021 MinIO, Inc.
//
// This file is part of MinIO Object Storage stack
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful

Network isolation between different models is also important not only to prevent
unauthorized access to data or models, but also to prevent malicious users or
tenants sending graphs to execute under another tenant’s identity.

The isolation mechanisms are the responsibility of the users to design and
implement, and therefore security issues deriving from their absence are not
considered a vulnerability in TensorFlow.