Tensor output;
    ASSERT_EQ(absl::OkStatus(), TF_TensorToTensor(dst, &output)) << line;
    ASSERT_EQ(src.NumElements(), output.NumElements()) << line;
    for (int64_t i = 0; i < src.NumElements(); ++i) {
      ASSERT_EQ(data[i], output.flat<tstring>()(i)) << line;
    }

    TF_DeleteTensor(dst);
  }
}

TEST(CAPI, TensorEncodeDecodeStrings) {

    /**
     * Returns all active profiles for the current project build.
     * <p>
     * Active profiles are those that have been explicitly activated through one of the following means:
     * <ul>
     *   <li>Command line activation using the -P flag</li>
     *   <li>Maven settings activation in settings.xml via &lt;activeProfiles&gt;</li>
     *   <li>Automatic activation via &lt;activation&gt; conditions</li>

## **Typer**, FastAPI의 CLI

<a href="https://typer.tiangolo.com" target="_blank"><img src="https://typer.tiangolo.com/img/logo-margin/logo-margin-vector.svg" style="width: 20%;"></a>

웹 API 대신 터미널에서 사용할 <abbr title="Command Line Interface">CLI</abbr> 앱을 만들고 있다면, <a href="https://typer.tiangolo.com/" class="external-link" target="_blank">**Typer**</a>를 확인해 보십시오.

**Typer**는 FastAPI의 동생입니다. 그리고 **FastAPI의 CLI**가 되기 위해 생겼습니다. ⌨️ 🚀

## 요구사항

<a href="https://typer.tiangolo.com" target="_blank"><img src="https://typer.tiangolo.com/img/logo-margin/logo-margin-vector.svg" style="width: 20%;"></a>

If you are building a <abbr title="Command Line Interface">CLI</abbr> app to be used in the terminal instead of a web API, check out <a href="https://typer.tiangolo.com/" class="external-link" target="_blank">**Typer**</a>.

pkg runtime, type Frame struct, Entry uintptr
pkg runtime, type Frame struct, File string
pkg runtime, type Frame struct, Func *Func
pkg runtime, type Frame struct, Function string
pkg runtime, type Frame struct, Line int
pkg runtime, type Frame struct, PC uintptr
pkg runtime, type Frames struct
pkg strings, method (*Reader) Reset(string)
pkg syscall (linux-386), type SysProcAttr struct, Unshareflags uintptr

      }
      return false;
    }

    @Override
    public int hashCode() {
      return Arrays.hashCode(functions);
    }
  }

  /**
   * Linear CongruentialGenerator to use for consistent hashing. See
   * http://en.wikipedia.org/wiki/Linear_congruential_generator
   */
  private static final class LinearCongruentialGenerator {
    private long state;

  private static final CharMatcher QUOTED_TEXT_MATCHER = ascii().and(CharMatcher.noneOf("\"\\\r"));

  /*
   * This matches the same characters as linear-white-space from RFC 822, but we make no effort to
   * enforce any particular rules with regards to line folding as stated in the class docs.
   */
  private static final CharMatcher LINEAR_WHITE_SPACE = CharMatcher.anyOf(" \t\r\n");

  // TODO(gak): make these public?

import java.util.NoSuchElementException;
import org.jspecify.annotations.Nullable;

/**
 * Implementation detail for the internal structure of {@link Range} instances. Represents a unique
 * way of "cutting" a "number line" (actually of instances of type {@code C}, not necessarily
 * "numbers") into two sections; this can be done below a certain value, above a certain value,

against a pending change. Search for "MLCI" internally to find it.

You may invoke a CI script of your choice by following these instructions:

```bash
cd tensorflow-git-dir

# Here is a single-line example of running a script on Linux to build the
# GPU version of TensorFlow for Python 3.12, using the public TF bazel cache and
# a local build cache:
TFCI=py312,linux_x86_cuda,public_cache,disk_cache ci/official/wheel.sh

func timeZone(offset time.Duration) *time.Location {
	const (
		minOffset   = -12 * time.Hour  // E.g., Baker island at -12:00
		maxOffset   = +14 * time.Hour  // E.g., Line island at +14:00
		offsetAlias = 15 * time.Minute // E.g., Nepal at +5:45
	)
	offset = offset.Round(offsetAlias)
	if offset < minOffset || maxOffset < offset {
		offset = 0
	}