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    <div class="item">
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        <span class="twemoji twitter">
          {% include ".icons/fontawesome/brands/twitter.svg" %}
        </span> Follow <strong>@fastapi</strong> on <strong>Twitter</strong> to stay updated
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## Introduction

Returns a set of temporary security credentials for applications/clients who have been authenticated through client credential grants provided by identity provider. Example providers include KeyCloak, Okta etc.

Harshavardhana <******@****.***> 1629336922 -0700

Dans ce cadre, j'ai dû étudier, tester et utiliser de nombreuses alternatives.

L'histoire de **FastAPI** est en grande partie l'histoire de ses prédécesseurs.

Comme dit dans la section [Alternatives](alternatives.md){.internal-link target=\_blank} :

<blockquote markdown="1">

//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package main

import (
	"bufio"
	crand "crypto/rand"
	"crypto/rsa"
	"crypto/x509"
	"encoding/json"
	"encoding/pem"
	"errors"
	"flag"
	"fmt"
	"io"
	"os"
	"strings"
	"time"
)

var (

// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package dsync

import (
	"math/rand"
	"sync"
)

// lockedRandSource provides protected rand source, implements rand.Source interface.
type lockedRandSource struct {
	lk  sync.Mutex
	src rand.Source
}

// Int63 returns a non-negative pseudo-random 63-bit integer as an int64.
func (r *lockedRandSource) Int63() (n int64) {

### 4. Test with MinIO STS API

Once etcd is configured, **any STS configuration** will work including Client Grants, Web Identity or AD/LDAP.

					r.URL)
				return
			}
			writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
			return
		}

		if len(acl.AccessControlList.Grants) == 0 {
			writeErrorResponse(ctx, w, toAPIError(ctx, NotImplemented{}), r.URL)
			return
		}

		if acl.AccessControlList.Grants[0].Permission != "FULL_CONTROL" {
			writeErrorResponse(ctx, w, toAPIError(ctx, NotImplemented{}), r.URL)
			return
		}
	}

        backward_function_deleter, in_grads, absl::MakeSpan(forward_grads)));
  } else {
    TF_RETURN_IF_ERROR(
        (*forward_function)(in_grads, &forward_grads, use_batch_));
  }
  for (int i = 0; i < forward_grads.size(); ++i) {
    if (forward_grads[i] != nullptr) {
      int64_t tensor_id = output_tensors[i].GetID();
      auto existing = accumulated_gradients_.find(tensor_id);