tot := ts.User + ts.System + ts.Idle + ts.Iowait + ts.Nice + ts.Steal
					cpuUserVal := math.Round(ts.User/tot*100*100) / 100
					updateResourceMetrics(cpuSubsystem, cpuUser, cpuUserVal, labels, false)
					cpuSystemVal := math.Round(ts.System/tot*100*100) / 100
					updateResourceMetrics(cpuSubsystem, cpuSystem, cpuSystemVal, labels, false)
					cpuIdleVal := math.Round(ts.Idle/tot*100*100) / 100

  private static final double[] VALUES = {
    Double.NEGATIVE_INFINITY,
    -Double.MAX_VALUE,
    (double) Long.MIN_VALUE,
    (double) Integer.MIN_VALUE,
    -Math.PI,
    -1.0,
    -Double.MIN_VALUE,
    -0.0,
    +0.0,
    Double.MIN_VALUE,
    1.0,
    Math.PI,
    (double) Integer.MAX_VALUE,
    (double) Long.MAX_VALUE,
    Double.MAX_VALUE,
    Double.POSITIVE_INFINITY,
    Double.NaN,
    Float.MAX_VALUE,

    ],
    deps = [
        "//tensorflow/c/eager:abstract_context",
        "//tensorflow/c/eager:gradients_internal",
    ],
)

cc_library(
    name = "math_grad",
    srcs = ["math_grad.cc"],
    hdrs = [
        "math_grad.h",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        "//tensorflow/c/eager:abstract_tensor_handle",

        });
    });

    summaries.forEach(summary => {
        summary.additionPercent = Math.round(summary.additions / (totalAdditions + totalDeletions) * 100, 2);
        summary.deletionPercent = Math.round(summary.deletions / (totalAdditions + totalDeletions) * 100, 2);
        summary.filesPercent = Math.round(summary.files.length / totalChangedFiles * 100, 2);
    });

    console.log("computeStatistics: ");

  private static final double[] VALUES = {
    Double.NEGATIVE_INFINITY,
    -Double.MAX_VALUE,
    (double) Long.MIN_VALUE,
    (double) Integer.MIN_VALUE,
    -Math.PI,
    -1.0,
    -Double.MIN_VALUE,
    -0.0,
    +0.0,
    Double.MIN_VALUE,
    1.0,
    Math.PI,
    (double) Integer.MAX_VALUE,
    (double) Long.MAX_VALUE,
    Double.MAX_VALUE,
    Double.POSITIVE_INFINITY,
    Double.NaN,
    Float.MAX_VALUE,

import jsinterop.annotations.JsPackage;

/** Web specializations for {@link Ints} methods. */
public abstract class IntsMethodsForWeb {

  @JsMethod(name = "Math.min", namespace = JsPackage.GLOBAL)
  public static native int min(int... array);

  @JsMethod(name = "Math.max", namespace = JsPackage.GLOBAL)
  public static native int max(int... array);

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TFE_Op* matmul = MatMulOp(ctx, h0_task1, h1_task1);
  TFE_OpSetDevice(matmul, remote_device_name, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TFE_TensorHandle* retvals[1];
  int num_retvals = 1;
  TFE_Execute(matmul, &retvals[0], &num_retvals, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

    *   New endpoints in tf.math namespace: `tf.math.acos`, `tf.math.acosh`,
        `tf.math.add`, `tf.math.asin`, `tf.math.asinh`, `tf.math.atan`,
        `tf.math.atan2`, `tf.math.atanh`, `tf.math.betainc`, `tf.math.ceil`,
        `tf.math.cos`, `tf.math.cosh`, `tf.math.digamma`, `tf.math.equal`,
        `tf.math.erfc`, `tf.math.exp`, `tf.math.expm1`, `tf.math.floor`,
        `tf.math.greater`, `tf.math.greater_equal`, `tf.math.igamma`,

    in.put(Number.class, 0);
    in.put(Double.class, Math.PI);
    ClassToInstanceMap<Number> map = ImmutableClassToInstanceMap.copyOf(in);
    assertEquals(2, map.size());

    Number zero = map.getInstance(Number.class);
    assertEquals(0, zero);

    Double pi = map.getInstance(Double.class);
    assertEquals(Math.PI, pi, 0.0);

    assertSame(map, ImmutableClassToInstanceMap.copyOf(map));
  }

			r.opts.HeaderSize = 0
			need = int(math.Min(float64(b-hdr), float64(need))) // use remaining tokens towards payload
			tokens = need + hdr

		} else { // part of header can be accommodated
			r.opts.HeaderSize -= b - 1
			need = 1 // to ensure we read at least one byte for every Read
			tokens = b
		}
	} else { // all tokens go towards payload
		need = int(math.Min(float64(b), float64(need)))
		tokens = need
	}