}
	// Try base 64
	dst := make([]byte, base64.StdEncoding.DecodedLen(len(priv)))
	if n, err := base64.StdEncoding.Decode(dst, priv); err == nil {
		return x509.ParsePKCS1PrivateKey(dst[:n])
	}
	// Try Raw, return error
	return x509.ParsePKCS1PrivateKey(priv)
}

func fatalErr(err error) {
	if err == nil {
		return
	}
	log.Fatalln(err)
}

func fatalIf(b bool, msg string, v ...interface{}) {
	if !b {

    return count;
  }

  /**
   * Returns the <a href="http://en.wikipedia.org/wiki/Arithmetic_mean">arithmetic mean</a> of the
   * values. The count must be non-zero.
   *
   * <p>If these values are a sample drawn from a population, this is also an unbiased estimator of
   * the arithmetic mean of the population.
   *
   * <h3>Non-finite values</h3>
   *

                log.debug("Failed to load key from KeyStore: {}", e.getMessage());
            }
        }

        return key;
    }

    /**
     * Get raw key bytes
     *
     * @param sessionId unique session identifier
     * @return raw key bytes, or null if not found
     */
    public byte[] getRawKey(String sessionId) {
        checkNotClosed();

        byte[] key = rawKeys.get(sessionId);

when dealing with untrusted data. Based on the security history of these
libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,
including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could

	if len(setSQL) == 0 || len(getSQL) == 0 {
		return
	}

	err := DB.Connection(func(tx *gorm.DB) error {
		if err := tx.Exec(setSQL, expectedName).Error; err != nil {
			return err
		}

		if err := tx.Raw(getSQL).Scan(&actualName).Error; err != nil {
			return err
		}
		return nil
	})
	if err != nil {
		t.Errorf(fmt.Sprintf("WithSingleConnection should work, but got err %v", err))
	}

        }
    }

    /**
     * Create an {@code NtlmPasswordAuthentication} object with raw password
     * hashes. This is used exclusively by the {@code jcifs.smb1.http.NtlmSsp}
     * class which is in turn used by NTLM HTTP authentication functionality.
     */
    /**
     * Create an NtlmPasswordAuthentication object with raw password hashes.
     *
     * @param domain the authentication domain

      newCases += case.copy(wire = bytesOut.readByteString())
    }

    testDecoder(story.copy(cases = newCases))
  }

  companion object {
    private val RAW_DATA = arrayOf("raw-data")
  }

            if (x * i == n) return "${factor(x)} × $i"
          }
          return n.toString()
        }
      }

    val request =
      Request(
        url = "https://api.github.com/markdown/raw".toHttpUrl(),
        body = requestBody,
      )

    client.newCall(request).execute().use { response ->
      if (!response.isSuccessful) throw IOException("Unexpected code $response")

class PostFile {
  private val client = OkHttpClient()

  fun run() {
    val file = File("README.md")

    val request =
      Request(
        url = "https://api.github.com/markdown/raw".toHttpUrl(),
        body = file.asRequestBody(MEDIA_TYPE_MARKDOWN),
      )

    client.newCall(request).execute().use { response ->
      if (!response.isSuccessful) throw IOException("Unexpected code $response")

     * @return an {@link Optional} containing the file path, or empty if not set
     */
    @Nonnull
    Optional<String> logFile();

    /**
     * Returns whether raw streams should be logged.
     *
     * @return a boolean indicating whether raw streams should be logged
     */
    @Nonnull
    Optional<Boolean> rawStreams();

    /**
     * Returns the color setting for console output.
     *