"options": {
        "colorMode": "none",
        "graphMode": "area",
        "justifyMode": "auto",
        "orientation": "horizontal",
        "reduceOptions": {
          "calcs": [
            "mean"
          ],
          "fields": "",
          "values": false
        },
        "textMode": "auto"
      },
      "pluginVersion": "10.1.5",
      "targets": [
        {

  if (offset && !IsOfRankedFloatTensorType(offset, 1))
    return op.emitOpError("requires offset to be a 1D float tensor");

  auto mean = GetRankedTensorTypeForOperand(op.getMean());
  if (mean && !IsOfRankedFloatTensorType(mean, 1))
    return op.emitOpError("requires mean to be a 1D float tensor");

  auto variance = GetRankedTensorTypeForOperand(op.getVariance());
  if (variance && !IsOfRankedFloatTensorType(variance, 1))

  let hasOptions = 0;
}

def TFL_MeanOp : TFL_Op<"mean", [
    PredOpTrait<"input and output must have same element type",
      TFL_TCresVTEtIsSameAsOp<0, 0>>,
    QuantizableResult,
    Pure]> {
  let summary = "Mean operator";

  let description = [{
    Computes the mean of elements across dimensions of a tensor.
    Reduces input_tensor along the dimensions given in axis.

            filter_tensor, filter_min, filter_max, num_bits=8, narrow_range=True
        )
        bias = array_ops.constant([0.1, 0.2], dtype=dtypes.float32)
        scale, offset = [1.0] * 2, [0.5] * 2
        mean, variance = scale, offset
        out = nn_ops.conv2d(
            q_input,
            q_filter,
            strides=[1, 1, 2, 1],
            dilations=[1, 1, 1, 1],
            padding='SAME',

	totalRx := int64(0)
	connectTime := time.Now()
	for {
		n, err := io.CopyN(xioutil.Discard, r.Body, 128*humanize.KiByte)
		if err != nil && err != io.EOF && err != io.ErrUnexpectedEOF {
			// would mean the network is not stable. Logging here will help in debugging network issues.
			if time.Since(connectTime) < (globalNetPerfMinDuration - time.Second) {
				adminLogIf(ctx, err)
			}
		}
		totalRx += n

   * to the cache because we incorrectly assumed that HttpsURLConnection was always HTTPS and
   * HttpURLConnection was always HTTP; in practice redirects mean that each can do either.
   *
   * https://github.com/square/okhttp/issues/214
   */
  @Test
  fun secureResponseCachingAndProtocolRedirects() {
    server2.useHttps(handshakeCertificates.sslSocketFactory())

  }

  /** Confirm that an unacknowledged write times out.  */
  @Test
  fun writeTimeouts() {
    val server = MockWebServer()
    // Sockets on some platforms can have large buffers that mean writes do not block when
    // required. These socket factories explicitly set the buffer sizes on sockets created.
    val socketBufferSize = 4 * 1024
    server.serverSocketFactory =

            "format": "int32",
            "type": "integer"
          }
        },

            "format": "int32",
            "type": "integer"
          }
        },

		}
	}

	// Note: We could decide that vet should compute export data for
	// all analyses, in which case we don't need to include the flags here.
	// But that would mean that if an analysis causes problems like
	// unexpected crashes there would be no way to turn it off.
	// It seems better to let the flags disable export analysis too.
	fmt.Fprintf(h, "vetflags %q\n", vetFlags)