text: import * as tf from '../index';
  import { describeWithFlags } from '../jasmine_util';
  import { ALL_ENVS, expectArraysClose, expectArraysEqual, expectNumbersClose } from '../test_util';
  import * as reduce_util from './reduce_util';
  describeWithFlags('min', ALL_ENVS, function () {
      it('Tensor1D', function () {
          var a = tf.tensor1d([3, -1, 0, 100, -7, 2]);
          expectNumbersClose(tf.min(a).get(), -7);
      });
      it('ignores NaNs', function () {
          var a = tf.tensor1d([3, NaN, 2]);
          expect(tf.min(a).get()).toEqual(2);
      });
      it('2D', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          expectNumbersClose(tf.min(a).get(), -7);
      });
      it('2D axis=[0,1]', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          expectNumbersClose(tf.min(a, [0, 1]).get(), -7);
      });
      it('2D, axis=0', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          var r = tf.min(a, 0);
          expect(r.shape).toEqual([3]);
          expectArraysClose(r, [3, -7, 0]);
      });
      it('2D, axis=0, keepDims', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          var r = tf.min(a, 0, true);
          expect(r.shape).toEqual([1, 3]);
          expectArraysClose(r, [3, -7, 0]);
      });
      it('2D, axis=1 provided as a number', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, 2], [2, 3]);
          var r = tf.min(a, 1);
          expectArraysClose(r, [2, -7]);
      });
      it('2D, axis = -1 provided as a number', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, 2], [2, 3]);
          var r = tf.min(a, -1);
          expectArraysClose(r, [2, -7]);
      });
      it('2D, axis=[1]', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, 2], [2, 3]);
          var r = tf.min(a, [1]);
          expectArraysClose(r, [2, -7]);
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.min({}); })
              .toThrowError(/Argument 'x' passed to 'min' must be a Tensor/);
      });
  });
  describeWithFlags('max', ALL_ENVS, function () {
      it('with one element dominating', function () {
          var a = tf.tensor1d([3, -1, 0, 100, -7, 2]);
          var r = tf.max(a);
          expectNumbersClose(r.get(), 100);
      });
      it('with all elements being the same', function () {
          var a = tf.tensor1d([3, 3, 3]);
          var r = tf.max(a);
          expectNumbersClose(r.get(), 3);
      });
      it('ignores NaNs', function () {
          expect(tf.max(tf.tensor1d([3, NaN, 2])).get()).toEqual(3);
      });
      it('2D', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          expectNumbersClose(tf.max(a).get(), 100);
      });
      it('2D axis=[0,1]', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          expectNumbersClose(tf.max(a, [0, 1]).get(), 100);
      });
      it('2D, axis=0', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          var r = tf.max(a, [0]);
          expect(r.shape).toEqual([3]);
          expectArraysClose(r, [100, -1, 2]);
      });
      it('2D, axis=0, keepDims', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          var r = tf.max(a, [0], true);
          expect(r.shape).toEqual([1, 3]);
          expectArraysClose(r, [100, -1, 2]);
      });
      it('2D, axis=1 provided as a number', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, 2], [2, 3]);
          var r = tf.max(a, 1);
          expectArraysClose(r, [5, 100]);
      });
      it('2D, axis = -1 provided as a number', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, 2], [2, 3]);
          var r = tf.max(a, -1);
          expectArraysClose(r, [5, 100]);
      });
      it('2D, axis=[1]', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, 2], [2, 3]);
          var r = tf.max(a, [1]);
          expectArraysClose(r, [5, 100]);
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.max({}); })
              .toThrowError(/Argument 'x' passed to 'max' must be a Tensor/);
      });
  });
  describeWithFlags('argmax', ALL_ENVS, function () {
      it('Tensor1D', function () {
          var a = tf.tensor1d([1, 0, 3, 2]);
          var result = tf.argMax(a);
          expect(result.dtype).toBe('int32');
          expect(result.get()).toBe(2);
      });
      it('one value', function () {
          var a = tf.tensor1d([10]);
          var result = tf.argMax(a);
          expect(result.dtype).toBe('int32');
          expect(result.get()).toBe(0);
      });
      it('N > than parallelization threshold', function () {
          var n = reduce_util.PARALLELIZE_THRESHOLD * 2;
          var values = new Float32Array(n);
          for (var i = 0; i < n; i++) {
              values[i] = i;
          }
          var a = tf.tensor1d(values);
          var result = tf.argMax(a);
          expect(result.dtype).toBe('int32');
          expect(result.get()).toBe(n - 1);
      });
      it('ignores NaNs', function () {
          var a = tf.tensor1d([0, 3, 5, NaN, 3]);
          var res = tf.argMax(a);
          expect(res.dtype).toBe('int32');
          expect(res.get()).toBe(2);
      });
      it('2D, no axis specified', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          expectArraysEqual(tf.argMax(a), [1, 0, 1]);
      });
      it('2D, axis=0', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          var r = tf.argMax(a, 0);
          expect(r.shape).toEqual([3]);
          expect(r.dtype).toBe('int32');
          expectArraysEqual(r, [1, 0, 1]);
      });
      it('2D, axis=1', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, 2], [2, 3]);
          var r = tf.argMax(a, 1);
          expect(r.dtype).toBe('int32');
          expectArraysEqual(r, [2, 0]);
      });
      it('2D, axis = -1', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, 2], [2, 3]);
          var r = tf.argMax(a, -1);
          expect(r.dtype).toBe('int32');
          expectArraysEqual(r, [2, 0]);
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.argMax({}); })
              .toThrowError(/Argument 'x' passed to 'argMax' must be a Tensor/);
      });
  });
  describeWithFlags('argmin', ALL_ENVS, function () {
      it('Tensor1D', function () {
          var a = tf.tensor1d([1, 0, 3, 2]);
          var result = tf.argMin(a);
          expect(result.get()).toBe(1);
      });
      it('one value', function () {
          var a = tf.tensor1d([10]);
          var result = tf.argMin(a);
          expect(result.get()).toBe(0);
      });
      it('N > than parallelization threshold', function () {
          var n = reduce_util.PARALLELIZE_THRESHOLD * 2;
          var values = new Float32Array(n);
          for (var i = 0; i < n; i++) {
              values[i] = n - i;
          }
          var a = tf.tensor1d(values);
          var result = tf.argMin(a);
          expect(result.dtype).toBe('int32');
          expect(result.get()).toBe(n - 1);
      });
      it('ignores NaNs', function () {
          var a = tf.tensor1d([5, 0, NaN, -1, 3]);
          var res = tf.argMin(a);
          expect(res.get()).toBe(3);
      });
      it('2D, no axis specified', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          expectArraysEqual(tf.argMin(a), [0, 1, 0]);
      });
      it('2D, axis=0', function () {
          var a = tf.tensor2d([3, -1, 0, 100, -7, 2], [2, 3]);
          var r = tf.argMin(a, 0);
          expect(r.shape).toEqual([3]);
          expect(r.dtype).toBe('int32');
          expectArraysEqual(r, [0, 1, 0]);
      });
      it('2D, axis=1', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, -8], [2, 3]);
          var r = tf.argMin(a, 1);
          expectArraysEqual(r, [1, 2]);
      });
      it('2D, axis = -1', function () {
          var a = tf.tensor2d([3, 2, 5, 100, -7, -8], [2, 3]);
          var r = tf.argMin(a, -1);
          expectArraysEqual(r, [1, 2]);
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.argMin({}); })
              .toThrowError(/Argument 'x' passed to 'argMin' must be a Tensor/);
      });
  });
  describeWithFlags('logSumExp', ALL_ENVS, function () {
      it('0', function () {
          var a = tf.scalar(0);
          var result = tf.logSumExp(a);
          expectNumbersClose(result.get(), 0);
      });
      it('basic', function () {
          var a = tf.tensor1d([1, 2, -3]);
          var result = tf.logSumExp(a);
          expectNumbersClose(result.get(), Math.log(Math.exp(1) + Math.exp(2) + Math.exp(-3)));
      });
      it('propagates NaNs', function () {
          var a = tf.tensor1d([1, 2, NaN]);
          var result = tf.logSumExp(a);
          expect(result.get()).toEqual(NaN);
      });
      it('axes=0 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var r = tf.logSumExp(a, [0]);
          expect(r.shape).toEqual([2]);
          var expected = [
              Math.log(Math.exp(1) + Math.exp(3) + Math.exp(0)),
              Math.log(Math.exp(2) + Math.exp(0) + Math.exp(1))
          ];
          expectArraysClose(r, expected);
      });
      it('axes=0 in 2D array, keepDims', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var r = tf.logSumExp(a, [0], true);
          expect(r.shape).toEqual([1, 2]);
          var expected = [
              Math.log(Math.exp(1) + Math.exp(3) + Math.exp(0)),
              Math.log(Math.exp(2) + Math.exp(0) + Math.exp(1))
          ];
          expectArraysClose(r, expected);
      });
      it('axes=1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.logSumExp(a, [1]);
          expect(res.shape).toEqual([3]);
          var expected = [
              Math.log(Math.exp(1) + Math.exp(2)),
              Math.log(Math.exp(3) + Math.exp(0)),
              Math.log(Math.exp(0) + Math.exp(1)),
          ];
          expectArraysClose(res, expected);
      });
      it('axes = -1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.logSumExp(a, -1);
          expect(res.shape).toEqual([3]);
          var expected = [
              Math.log(Math.exp(1) + Math.exp(2)),
              Math.log(Math.exp(3) + Math.exp(0)),
              Math.log(Math.exp(0) + Math.exp(1)),
          ];
          expectArraysClose(res, expected);
      });
      it('2D, axes=1 provided as a single digit', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [2, 3]);
          var res = tf.logSumExp(a, 1);
          expect(res.shape).toEqual([2]);
          var expected = [
              Math.log(Math.exp(1) + Math.exp(2) + Math.exp(3)),
              Math.log(Math.exp(0) + Math.exp(0) + Math.exp(1))
          ];
          expectArraysClose(res, expected);
      });
      it('axes=0,1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.logSumExp(a, [0, 1]);
          expect(res.shape).toEqual([]);
          var expected = [Math.log(Math.exp(1) + Math.exp(2) + Math.exp(3) + Math.exp(0) + Math.exp(0) +
                  Math.exp(1))];
          expectArraysClose(res, expected);
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.logSumExp({}); })
              .toThrowError(/Argument 'x' passed to 'logSumExp' must be a Tensor/);
      });
  });
  describeWithFlags('sum', ALL_ENVS, function () {
      it('basic', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var result = tf.sum(a);
          expectNumbersClose(result.get(), 7);
      });
      it('propagates NaNs', function () {
          var a = tf.tensor2d([1, 2, 3, NaN, 0, 1], [3, 2]);
          expect(tf.sum(a).get()).toEqual(NaN);
      });
      it('sum over dtype int32', function () {
          var a = tf.tensor1d([1, 5, 7, 3], 'int32');
          var sum = tf.sum(a);
          expect(sum.get()).toBe(16);
      });
      it('sum over dtype bool', function () {
          var a = tf.tensor1d([true, false, false, true, true], 'bool');
          var sum = tf.sum(a);
          expect(sum.get()).toBe(3);
      });
      it('sums all values in 2D array with keep dim', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.sum(a, null, true);
          expect(res.shape).toEqual([1, 1]);
          expectArraysClose(res, [7]);
      });
      it('sums across axis=0 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.sum(a, [0]);
          expect(res.shape).toEqual([2]);
          expectArraysClose(res, [4, 3]);
      });
      it('sums across axis=0 in 2D array, keepDims', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.sum(a, [0], true);
          expect(res.shape).toEqual([1, 2]);
          expectArraysClose(res, [4, 3]);
      });
      it('sums across axis=1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.sum(a, [1]);
          expect(res.shape).toEqual([3]);
          expectArraysClose(res, [3, 3, 1]);
      });
      it('2D, axis=1 provided as number', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [2, 3]);
          var res = tf.sum(a, 1);
          expect(res.shape).toEqual([2]);
          expectArraysClose(res, [6, 1]);
      });
      it('2D, axis = -1 provided as number', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [2, 3]);
          var res = tf.sum(a, -1);
          expect(res.shape).toEqual([2]);
          expectArraysClose(res, [6, 1]);
      });
      it('sums across axis=0,1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.sum(a, [0, 1]);
          expect(res.shape).toEqual([]);
          expectArraysClose(res, [7]);
      });
      it('2D, axis=[-1,-2] in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.sum(a, [-1, -2]);
          expect(res.shape).toEqual([]);
          expectArraysClose(res, [7]);
      });
      it('gradients: sum(2d)', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var dy = tf.scalar(10);
          var gradients = tf.grad(function (a) { return a.sum(); })(a, dy);
          expect(gradients.shape).toEqual(a.shape);
          expect(gradients.dtype).toEqual('float32');
          expectArraysClose(gradients, [10, 10, 10, 10, 10, 10]);
      });
      it('gradients: sum(2d, axis=0)', function () {
          var a = tf.tensor2d([[1, 2], [3, 0], [0, 1]], [3, 2]);
          var dy = tf.tensor1d([10, 20]);
          var axis = 0;
          var gradients = tf.grad(function (a) { return a.sum(axis); })(a, dy);
          expect(gradients.shape).toEqual(a.shape);
          expect(gradients.dtype).toEqual('float32');
          expectArraysClose(gradients, [10, 20, 10, 20, 10, 20]);
      });
      it('gradients: sum(2d, axis=1)', function () {
          var a = tf.tensor2d([[1, 2], [3, 0], [0, 1]], [3, 2]);
          var dy = tf.tensor1d([10, 20, 30]);
          var axis = 1;
          var gradients = tf.grad(function (a) { return a.sum(axis); })(a, dy);
          expect(gradients.shape).toEqual(a.shape);
          expect(gradients.dtype).toEqual('float32');
          expectArraysClose(gradients, [10, 10, 20, 20, 30, 30]);
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.sum({}); })
              .toThrowError(/Argument 'x' passed to 'sum' must be a Tensor/);
      });
  });
  describeWithFlags('mean', ALL_ENVS, function () {
      it('basic', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var r = tf.mean(a);
          expect(r.dtype).toBe('float32');
          expectNumbersClose(r.get(), 7 / 6);
      });
      it('propagates NaNs', function () {
          var a = tf.tensor2d([1, 2, 3, NaN, 0, 1], [3, 2]);
          var r = tf.mean(a);
          expect(r.dtype).toBe('float32');
          expect(r.get()).toEqual(NaN);
      });
      it('mean(int32) => float32', function () {
          var a = tf.tensor1d([1, 5, 7, 3], 'int32');
          var r = tf.mean(a);
          expect(r.dtype).toBe('float32');
          expectNumbersClose(r.get(), 4);
      });
      it('mean(bool) => float32', function () {
          var a = tf.tensor1d([true, false, false, true, true], 'bool');
          var r = tf.mean(a);
          expect(r.dtype).toBe('float32');
          expectNumbersClose(r.get(), 3 / 5);
      });
      it('2D array with keep dim', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.mean(a, null, true);
          expect(res.shape).toEqual([1, 1]);
          expect(res.dtype).toBe('float32');
          expectArraysClose(res, [7 / 6]);
      });
      it('axis=0 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.mean(a, [0]);
          expect(res.shape).toEqual([2]);
          expect(res.dtype).toBe('float32');
          expectArraysClose(res, [4 / 3, 1]);
      });
      it('axis=0 in 2D array, keepDims', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.mean(a, [0], true);
          expect(res.shape).toEqual([1, 2]);
          expect(res.dtype).toBe('float32');
          expectArraysClose(res, [4 / 3, 1]);
      });
      it('axis=1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.mean(a, [1]);
          expect(res.dtype).toBe('float32');
          expect(res.shape).toEqual([3]);
          expectArraysClose(res, [1.5, 1.5, 0.5]);
      });
      it('axis = -1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.mean(a, [-1]);
          expect(res.dtype).toBe('float32');
          expect(res.shape).toEqual([3]);
          expectArraysClose(res, [1.5, 1.5, 0.5]);
      });
      it('2D, axis=1 provided as number', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [2, 3]);
          var res = tf.mean(a, 1);
          expect(res.shape).toEqual([2]);
          expect(res.dtype).toBe('float32');
          expectArraysClose(res, [2, 1 / 3]);
      });
      it('axis=0,1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var res = tf.mean(a, [0, 1]);
          expect(res.shape).toEqual([]);
          expect(res.dtype).toBe('float32');
          expectArraysClose(res, [7 / 6]);
      });
      it('gradients', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var dy = tf.scalar(1.5);
          var da = tf.grad(function (a) { return a.mean(); })(a, dy);
          expect(da.shape).toEqual(a.shape);
          expectArraysClose(da, [
              dy.get() / a.size, dy.get() / a.size, dy.get() / a.size,
              dy.get() / a.size, dy.get() / a.size, dy.get() / a.size
          ]);
      });
      it('gradients throws for defined axis', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var dy = tf.scalar(1.5);
          expect(function () { return tf.grad(function (a) { return a.mean(1); })(a, dy); }).toThrowError();
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.mean({}); })
              .toThrowError(/Argument 'x' passed to 'mean' must be a Tensor/);
      });
  });
  describeWithFlags('moments', ALL_ENVS, function () {
      it('basic', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var _a = tf.moments(a), mean = _a.mean, variance = _a.variance;
          expect(mean.dtype).toBe('float32');
          expect(variance.dtype).toBe('float32');
          expectNumbersClose(mean.get(), 7 / 6);
          expectNumbersClose(variance.get(), 1.1389);
      });
      it('propagates NaNs', function () {
          var a = tf.tensor2d([1, 2, 3, NaN, 0, 1], [3, 2]);
          var _a = tf.moments(a), mean = _a.mean, variance = _a.variance;
          expect(mean.dtype).toBe('float32');
          expect(variance.dtype).toBe('float32');
          expect(mean.get()).toEqual(NaN);
          expect(variance.get()).toEqual(NaN);
      });
      it('moments(int32) => float32', function () {
          var a = tf.tensor1d([1, 5, 7, 3], 'int32');
          var _a = tf.moments(a), mean = _a.mean, variance = _a.variance;
          expect(mean.dtype).toBe('float32');
          expect(variance.dtype).toBe('float32');
          expectNumbersClose(mean.get(), 4);
          expectNumbersClose(variance.get(), 5);
      });
      it('moments(bool) => float32', function () {
          var a = tf.tensor1d([true, false, false, true, true], 'bool');
          var _a = tf.moments(a), mean = _a.mean, variance = _a.variance;
          expect(mean.dtype).toBe('float32');
          expect(variance.dtype).toBe('float32');
          expectNumbersClose(mean.get(), 3 / 5);
          expectNumbersClose(variance.get(), 0.23999998);
      });
      it('2D array with keep dim', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var _a = tf.moments(a, null, true), mean = _a.mean, variance = _a.variance;
          expect(mean.shape).toEqual([1, 1]);
          expect(mean.dtype).toBe('float32');
          expect(variance.shape).toEqual([1, 1]);
          expect(variance.dtype).toBe('float32');
          expectArraysClose(mean, [7 / 6]);
          expectArraysClose(variance, [1.138889]);
      });
      it('axis=0 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var _a = tf.moments(a, [0]), mean = _a.mean, variance = _a.variance;
          expect(mean.shape).toEqual([2]);
          expect(mean.dtype).toBe('float32');
          expect(variance.shape).toEqual([2]);
          expect(variance.dtype).toBe('float32');
          expectArraysClose(mean, [4 / 3, 1]);
          expectArraysClose(variance, [1.556, 2 / 3]);
      });
      it('axis=1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var _a = tf.moments(a, [1]), mean = _a.mean, variance = _a.variance;
          expect(mean.dtype).toBe('float32');
          expect(mean.shape).toEqual([3]);
          expect(variance.dtype).toBe('float32');
          expect(variance.shape).toEqual([3]);
          expectArraysClose(mean, [1.5, 1.5, 0.5]);
          expectArraysClose(variance, [0.25, 2.25, 0.25]);
      });
      it('2D, axis=1 provided as number', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [2, 3]);
          var _a = tf.moments(a, 1), mean = _a.mean, variance = _a.variance;
          expect(mean.shape).toEqual([2]);
          expect(mean.dtype).toBe('float32');
          expect(variance.shape).toEqual([2]);
          expect(variance.dtype).toBe('float32');
          expectArraysClose(mean, [2, 1 / 3]);
          expectArraysClose(variance, [2 / 3, 0.222]);
      });
      it('2D, axis=-1 provided as number', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [2, 3]);
          var _a = tf.moments(a, -1), mean = _a.mean, variance = _a.variance;
          expect(mean.shape).toEqual([2]);
          expect(mean.dtype).toBe('float32');
          expect(variance.shape).toEqual([2]);
          expect(variance.dtype).toBe('float32');
          expectArraysClose(mean, [2, 1 / 3]);
          expectArraysClose(variance, [2 / 3, 0.222]);
      });
      it('axis=0,1 in 2D array', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var _a = tf.moments(a, [0, 1]), mean = _a.mean, variance = _a.variance;
          expect(mean.shape).toEqual([]);
          expect(mean.dtype).toBe('float32');
          expect(variance.shape).toEqual([]);
          expect(variance.dtype).toBe('float32');
          expectArraysClose(mean, [7 / 6]);
          expectArraysClose(variance, [1.1389]);
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.moments({}); })
              .toThrowError(/Argument 'x' passed to 'moments' must be a Tensor/);
      });
  });
  describeWithFlags('norm', ALL_ENVS, function () {
      it('scalar norm', function () {
          var a = tf.scalar(-22.0);
          var norm = tf.norm(a);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 22);
      });
      it('vector inf norm', function () {
          var a = tf.tensor1d([1, -2, 3, -4]);
          var norm = tf.norm(a, Infinity);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 4);
      });
      it('vector -inf norm', function () {
          var a = tf.tensor1d([1, -2, 3, -4]);
          var norm = tf.norm(a, -Infinity);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 1);
      });
      it('vector 1 norm', function () {
          var a = tf.tensor1d([1, -2, 3, -4]);
          var norm = tf.norm(a, 1);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 10);
      });
      it('vector euclidean norm', function () {
          var a = tf.tensor1d([1, -2, 3, -4]);
          var norm = tf.norm(a, 'euclidean');
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 5.4772);
      });
      it('vector 2-norm', function () {
          var a = tf.tensor1d([1, -2, 3, -4]);
          var norm = tf.norm(a, 2);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 5.4772);
      });
      it('vector >2-norm to throw error', function () {
          var a = tf.tensor1d([1, -2, 3, -4]);
          expect(function () { return tf.norm(a, 3); }).toThrowError();
      });
      it('matrix inf norm', function () {
          var a = tf.tensor2d([1, 2, -3, 1, 0, 1], [3, 2]);
          var norm = tf.norm(a, Infinity, [0, 1]);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 4);
      });
      it('matrix -inf norm', function () {
          var a = tf.tensor2d([1, 2, -3, 1, 0, 1], [3, 2]);
          var norm = tf.norm(a, -Infinity, [0, 1]);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 1);
      });
      it('matrix 1 norm', function () {
          var a = tf.tensor2d([1, 2, -3, 1, 1, 1], [3, 2]);
          var norm = tf.norm(a, 1, [0, 1]);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 5);
      });
      it('matrix euclidean norm', function () {
          var a = tf.tensor2d([1, 2, -3, 1, 1, 1], [3, 2]);
          var norm = tf.norm(a, 'euclidean', [0, 1]);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 4.123);
      });
      it('matrix fro norm', function () {
          var a = tf.tensor2d([1, 2, -3, 1, 1, 1], [3, 2]);
          var norm = tf.norm(a, 'fro', [0, 1]);
          expect(norm.dtype).toBe('float32');
          expectNumbersClose(norm.get(), 4.123);
      });
      it('matrix other norm to throw error', function () {
          var a = tf.tensor2d([1, 2, -3, 1, 1, 1], [3, 2]);
          expect(function () { return tf.norm(a, 2, [0, 1]); }).toThrowError();
      });
      it('propagates NaNs for norm', function () {
          var a = tf.tensor2d([1, 2, 3, NaN, 0, 1], [3, 2]);
          var norm = tf.norm(a);
          expect(norm.dtype).toBe('float32');
          expect(norm.get()).toEqual(NaN);
      });
      it('axis=null in 2D array norm', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var norm = tf.norm(a, Infinity);
          expect(norm.shape).toEqual([]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3]);
      });
      it('2D array norm with keep dim', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var norm = tf.norm(a, Infinity, null, true);
          expect(norm.shape).toEqual([1, 1]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3]);
      });
      it('axis=0 in 2D array norm', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var norm = tf.norm(a, Infinity, [0]);
          expect(norm.shape).toEqual([2]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3, 2]);
      });
      it('axis=1 in 2D array norm', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var norm = tf.norm(a, Infinity, [1]);
          expect(norm.dtype).toBe('float32');
          expect(norm.shape).toEqual([3]);
          expectArraysClose(norm, [2, 3, 1]);
      });
      it('axis=1 keepDims in 2D array norm', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var norm = tf.norm(a, Infinity, [1], true);
          expect(norm.dtype).toBe('float32');
          expect(norm.shape).toEqual([3, 1]);
          expectArraysClose(norm, [2, 3, 1]);
      });
      it('2D norm with axis=1 provided as number', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [2, 3]);
          var norm = tf.norm(a, Infinity, 1);
          expect(norm.shape).toEqual([2]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3, 1]);
      });
      it('axis=0,1 in 2D array norm', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var norm = tf.norm(a, Infinity, [0, 1]);
          expect(norm.shape).toEqual([]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3]);
      });
      it('axis=0,1 keepDims in 2D array norm', function () {
          var a = tf.tensor2d([1, 2, 3, 0, 0, 1], [3, 2]);
          var norm = tf.norm(a, Infinity, [0, 1], true);
          expect(norm.shape).toEqual([1, 1]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3]);
      });
      it('3D norm axis=0,1, matrix inf norm', function () {
          var a = tf.tensor3d([1, 2, -3, 1, 0, 1], [3, 2, 1]);
          var norm = tf.norm(a, Infinity, [0, 1]);
          expect(norm.shape).toEqual([1]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [4]);
      });
      it('axis=0,1 keepDims in 3D array norm', function () {
          var a = tf.tensor3d([1, 2, 3, 0, 0, 1], [3, 2, 1]);
          var norm = tf.norm(a, Infinity, [0, 1], true);
          expect(norm.shape).toEqual([1, 1, 1]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3]);
      });
      it('axis=0,1 keepDims in 3D array norm', function () {
          var a = tf.tensor3d([1, 2, 3, 0, 0, 1, 1, 2, 3, 0, 0, 1], [3, 2, 2]);
          var norm = tf.norm(a, Infinity, [0, 1], true);
          expect(norm.shape).toEqual([1, 1, 2]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [4, 3]);
      });
      it('axis=null in 3D array norm', function () {
          var a = tf.tensor3d([1, 2, 3, 0, 0, 1], [3, 2, 1]);
          var norm = tf.norm(a, Infinity);
          expect(norm.shape).toEqual([]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3]);
      });
      it('axis=null in 4D array norm', function () {
          var a = tf.tensor4d([1, 2, 3, 0, 0, 1], [3, 2, 1, 1]);
          var norm = tf.norm(a, Infinity);
          expect(norm.shape).toEqual([]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [3]);
      });
      it('axis=0,1 in 4D array norm', function () {
          var a = tf.tensor4d([
              1, 2, 3, 0, 0, 1, 1, 2, 3, 0, 0, 1,
              1, 2, 3, 0, 0, 1, 1, 2, 3, 0, 0, 1
          ], [3, 2, 2, 2]);
          var norm = tf.norm(a, Infinity, [0, 1]);
          expect(norm.shape).toEqual([2, 2]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [4, 3, 4, 3]);
      });
      it('axis=0,1 in 4D array norm', function () {
          var a = tf.tensor4d([
              1, 2, 3, 0, 0, 1, 1, 2, 3, 0, 0, 1,
              1, 2, 3, 0, 0, 1, 1, 2, 3, 0, 0, 1
          ], [3, 2, 2, 2]);
          var norm = tf.norm(a, Infinity, [0, 1], true);
          expect(norm.shape).toEqual([1, 1, 2, 2]);
          expect(norm.dtype).toBe('float32');
          expectArraysClose(norm, [4, 3, 4, 3]);
      });
      it('throws when passed a non-tensor', function () {
          expect(function () { return tf.norm({}); })
              .toThrowError(/Argument 'x' passed to 'norm' must be a Tensor/);
      });
  });
  describeWithFlags('unsortedSegmentSum', ALL_ENVS, function () {
      it('tensor1D', function () {
          var t = tf.tensor1d([1, 2, 3, 4]);
          var segmentIds = tf.tensor1d([0, 2, 0, 1], 'int32');
          var numSegments = 3;
          var res = tf.unsortedSegmentSum(t, segmentIds, numSegments);
          expect(res.shape).toEqual([3]);
          expectArraysClose(res, [4, 4, 2]);
      });
      it('tensor2D axis=0', function () {
          var t = tf.tensor2d([1, 2, 3, 4], [2, 2]);
          var segmentIds = tf.tensor1d([0, 0], 'int32');
          var numSegments = 2;
          var res = tf.unsortedSegmentSum(t, segmentIds, numSegments);
          expect(res.shape).toEqual([2, 2]);
          expectArraysClose(res, [4, 6, 0, 0]);
      });
      it('tensor2D axis=11', function () {
          var t = tf.tensor2d([1, 2, 3, 4], [2, 2]);
          var segmentIds = tf.tensor1d([0, 0], 'int32');
          var numSegments = 2;
          var axis = 1;
          var res = tf.unsortedSegmentSum(t, segmentIds, numSegments, axis);
          expect(res.shape).toEqual([2, 2]);
          expectArraysClose(res, [3, 0, 7, 0]);
      });
      it('tensor3D axis=0', function () {
          var t = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [3, 2, 2]);
          var segmentIds = tf.tensor1d([2, 1, 2], 'int32');
          var numSegments = 3;
          var axis = 0;
          var res = tf.unsortedSegmentSum(t, segmentIds, numSegments, axis);
          expect(res.shape).toEqual([3, 2, 2]);
          expectArraysClose(res, [0, 0, 0, 0, 5, 6, 7, 8, 10, 12, 14, 16]);
      });
      it('tensor3D axis=1', function () {
          var t = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 3, 2]);
          var segmentIds = tf.tensor1d([2, 2, 2], 'int32');
          var numSegments = 3;
          var axis = 1;
          var res = tf.unsortedSegmentSum(t, segmentIds, numSegments, axis);
          expect(res.shape).toEqual([2, 3, 2]);
          expectArraysClose(res, [0, 0, 0, 0, 9, 12, 0, 0, 0, 0, 27, 30]);
      });
      it('tensor3D axis=2', function () {
          var t = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 3, 2]);
          var segmentIds = tf.tensor1d([0, 0], 'int32');
          var numSegments = 2;
          var axis = 2;
          var res = tf.unsortedSegmentSum(t, segmentIds, numSegments, axis);
          expect(res.shape).toEqual([2, 3, 2]);
          expectArraysClose(res, [3, 0, 7, 0, 11, 0, 15, 0, 19, 0, 23, 0]);
      });
  });
  //# sourceMappingURL=reduction_ops_test.js.map