## Prerequisites

name: TensorFlow Issue Template
description: Use this template to report TensorFlow-related issues
body:
  - type: dropdown
    id: issue-type
    attributes:
      label: Issue type
      description: What type of issue would you like to report?
      multiple: false
      options:
        - Bug
        - Build/Install
        - Performance
        - Support
        - Feature Request
        - Documentation Feature Request

//   for tensors populated by the client.  So the client can do things
//   like shadowing a numpy array.
// * We do not provide TF_OK since it is not strictly necessary and we
//   are not optimizing for convenience.
// * We make assumption that one session has one graph.  This should be
//   fine since we have the ability to run sub-graphs.
// * We could allow NULL for some arguments (e.g., NULL options arg).

```

</div>

Dans la sortie, il y a une ligne semblable à :

```hl_lines="4"
INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

Cette ligne montre l’URL où votre application est servie, sur votre machine locale.

### Vérifier { #check-it }

    val logs = testLogHandler.takeAll()
    assertThat(countFrames(logs, "FINE: >> 0x00000000     8 PING          "))
      .isEqualTo(1)
    assertThat(countFrames(logs, "FINE: << 0x00000000     8 PING          "))
      .isEqualTo(1)
    assertThat(countFrames(logs, "FINE: >> 0x00000000     8 PING          ACK"))
      .isEqualTo(1)
    assertThat(countFrames(logs, "FINE: << 0x00000000     8 PING          ACK"))
      .isEqualTo(1)
  }

The assembler works on the semi-abstract form, so
when you see an instruction like <code>MOV</code>
what the toolchain actually generates for that operation might
not be a move instruction at all, perhaps a clear or load.
Or it might correspond exactly to the machine instruction with that name.
In general, machine-specific operations tend to appear as themselves, while more general concepts like
memory move and subroutine call and return are more abstract.

// TF_NewAttrBuilder() returns an object that you can set attributes on as
// though it were an op. This allows querying properties of that op for
// type-checking purposes like if the op will run on a particular device type.
typedef struct TF_AttrBuilder TF_AttrBuilder;
TF_CAPI_EXPORT extern TF_AttrBuilder* TF_NewAttrBuilder(const char* op_name);

 */
package org.apache.maven.cli.transfer;

import java.io.PrintStream;
import java.text.DecimalFormat;
import java.text.DecimalFormatSymbols;
import java.util.Locale;

import org.apache.maven.jline.MessageUtils;
import org.eclipse.aether.transfer.AbstractTransferListener;
import org.eclipse.aether.transfer.TransferCancelledException;
import org.eclipse.aether.transfer.TransferEvent;

import okhttp3.internal.unmodifiable

/**
 * An [RFC 7235][rfc_7235] challenge.
 *
 * [rfc_7235]: https://tools.ietf.org/html/rfc7235
 */
class Challenge(
  /** Returns the authentication scheme, like `Basic`. */
  @get:JvmName("scheme") val scheme: String,
  authParams: Map<String?, String>,
) {
  /**
   * Returns the auth params, including [realm] and [charset] if present, but as

     * @param localRepository    local repository
     * @param remoteRepositories remote repositories, {@link List} $lt; {@link ArtifactRepository} >
     * @return {@link List} $lt; {@link ArtifactVersion} >
     * @throws ArtifactMetadataRetrievalException
     *          in case of error while retrieving repository metadata from the repository.
     */