TF_Status* status);

// Returns the device type of the operation that produced `h`.
TF_CAPI_EXPORT extern const char* TFE_TensorHandleDeviceType(
    TFE_TensorHandle* h, TF_Status* status);

// Returns the device ID of the operation that produced `h`.
TF_CAPI_EXPORT extern int TFE_TensorHandleDeviceID(TFE_TensorHandle* h,

# Old config for backward compatibility
build:nvcc_clang --config=cuda_nvcc

# Debug config
build:dbg -c dbg
# Only include debug info for files under tensorflow/, excluding kernels, to
# reduce the size of the debug info in the binary. This is because if the debug
# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.

        newTop.distinctElements = distinctElements - 1;
        newTop.totalCount = totalCount - oldElemCount;
        return newTop.rebalance();
      }
    }

    // Removes the minimum node from this subtree to be reused elsewhere
    @CheckForNull
    private AvlNode<E> removeMin(AvlNode<E> node) {
      if (left == null) {
        return right;
      } else {
        left = left.removeMin(node);
        distinctElements--;

 * order. Any removal invalidates any ordering guarantees.
 *
 * <p>This class should not be assumed to be universally superior to {@code java.util.HashSet}.
 * Generally speaking, this class reduces object allocation and memory consumption at the price of
 * moderately increased constant factors of CPU. Only use this class when there is a specific reason
 * to prioritize memory over CPU.
 *
 * @author Dimitris Andreou

          <version>1.0.0+</version>
          <type>String</type>
          <description>
            The configurator type to use when injecting parameter values into this Mojo. The value is normally deduced
            from the Mojo's implementation language, but can be specified to allow a custom ComponentConfigurator
            implementation to be used.
          </description>
        </field>
        <field>

      </dependency>
      <!--
      We moved away from using dependencyManagement for test-only deps because of https://github.com/google/guava/issues/6654.
      We could probably have resumed it after https://github.com/google/guava/pull/6664.
      But it's always weird that published poms reference test-only libraries at all, so I'm not in any rush to do so.
      -->
    </dependencies>

      </dependency>
      <!--
      We moved away from using dependencyManagement for test-only deps because of https://github.com/google/guava/issues/6654.
      We could probably have resumed it after https://github.com/google/guava/pull/6664.
      But it's always weird that published poms reference test-only libraries at all, so I'm not in any rush to do so.
      -->
    </dependencies>

* **Rápido de programar**: Incrementa la velocidad de desarrollo entre 200% y 300%. *
* **Menos errores**: Reduce los errores humanos (de programador) aproximadamente un 40%. *

	return "Storage reached its minimum free drive threshold."
}

// SlowDown  too many file descriptors open or backend busy .
type SlowDown struct{}

func (e SlowDown) Error() string {
	return "Please reduce your request rate"
}

// RQErrType reason for read quorum error.
type RQErrType int

const (
	// RQInsufficientOnlineDrives - not enough online drives.
	RQInsufficientOnlineDrives RQErrType = 1 << iota

      .assertHeader("Test", "Redirect from /a to /b")

    // New connection.
    assertThat(server.takeRequest().sequenceNumber).isEqualTo(0)
    // Connection reused.
    assertThat(server.takeRequest().sequenceNumber).isEqualTo(1)
    // Connection reused again!
    assertThat(server.takeRequest().sequenceNumber).isEqualTo(2)
  }

  @Test
  fun postRedirectsToGet() {
    server.enqueue(