@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
1,001 lines • 48 kB
JavaScript
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
var tf = require("../index");
var jasmine_util_1 = require("../jasmine_util");
var backend_webgl_1 = require("../kernels/backend_webgl");
var test_util_1 = require("../test_util");
jasmine_util_1.describeWithFlags('packed matmul', test_util_1.WEBGL_ENVS, function () {
it('should not leak memory', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8, 9], [3, 3]);
var b = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], [3, 5]);
var startNumBytes = tf.memory().numBytes;
tf.matMul(a, b);
var endNumBytes = tf.memory().numBytes;
expect(endNumBytes - startNumBytes).toEqual(60);
});
it('should work when input matrix dimensions are not divisible by 2', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8, 9], [3, 3]);
var b = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], [3, 5]);
var c = tf.matMul(a, b);
expect(c.shape).toEqual([3, 5]);
test_util_1.expectArraysClose(c, [46, 52, 58, 64, 70, 100, 115, 130, 145, 160, 154, 178, 202, 226, 250]);
});
it('should work when output texture shape != physical shape', function () {
var sharedDim = 16000;
var a = tf.buffer([2, sharedDim], 'float32');
var b = tf.buffer([sharedDim, 2], 'float32');
a.set(1, 0, sharedDim - 1);
a.set(1, 0, sharedDim - 2);
a.set(1, 1, sharedDim - 1);
b.set(1, sharedDim - 1, 0);
b.set(1, sharedDim - 2, 0);
var c = tf.matMul(a.toTensor(), b.toTensor());
var expected = [2, 0, 1, 0];
test_util_1.expectArraysClose(c, expected);
});
it('should work when input texture shapes != physical shape', function () {
var maxTextureSize = tf.ENV.get('WEBGL_MAX_TEXTURE_SIZE');
tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', 5);
var a = tf.tensor2d([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [1, 12]);
var b = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [12, 1]);
var c = tf.matMul(a, b);
tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', maxTextureSize);
test_util_1.expectArraysClose(c, [572]);
});
it('A x B', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([0, 1, -3, 2, 2, 1], [3, 2]);
var c = tf.matMul(a, b);
expect(c.shape).toEqual([2, 2]);
test_util_1.expectArraysClose(c, [0, 8, -3, 20]);
});
it('A x B^t', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([1, 0, 2, 4, 3, 0], [2, 3]);
var transposeA = false;
var transposeB = true;
var c = tf.matMul(a, b, transposeA, transposeB);
var expected = [7, 10, 16, 31];
test_util_1.expectArraysClose(c, expected);
});
it('A^t x B', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([1, 0, 2, 4, 3, 0], [2, 3]);
var transposeA = true;
var transposeB = false;
var c = tf.matMul(a, b, transposeA, transposeB);
var expected = [17, 12, 2, 22, 15, 4, 27, 18, 6];
test_util_1.expectArraysClose(c, expected);
});
it('A^t x B^t', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
var b = tf.tensor2d([1, 0, 2, 4, 3, 0], [2, 3]);
var transposeA = true;
var transposeB = true;
var c = tf.matMul(a, b, transposeA, transposeB);
var expected = [11, 13, 14, 20];
test_util_1.expectArraysClose(c, expected);
});
it('works when followed by an op that requires unpacked inputs', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([0, 1, -3, 2, 2, 1], [3, 2]);
var c = tf.matMul(a, b);
var webglPackBinarySaved = tf.ENV.get('WEBGL_PACK_BINARY_OPERATIONS');
tf.ENV.set('WEBGL_PACK_BINARY_OPERATIONS', false);
var d = tf.add(c, 1);
tf.ENV.set('WEBGL_PACK_BINARY_OPERATIONS', webglPackBinarySaved);
test_util_1.expectArraysClose(d, [1, 9, -2, 21]);
});
it('works when followed by a packed reshape that changes texture layout, and then an unpacked op', function () {
var webglLazilyUnpackSaved = tf.ENV.get('WEBGL_LAZILY_UNPACK');
tf.ENV.set('WEBGL_LAZILY_UNPACK', true);
var a = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8, 9], [9, 1]);
var b = tf.tensor2d([1], [1, 1]);
var c = tf.matMul(a, b);
var d = tf.reshape(c, [1, 3, 3, 1]);
var webglPackBinarySaved = tf.ENV.get('WEBGL_PACK_BINARY_OPERATIONS');
tf.ENV.set('WEBGL_PACK_BINARY_OPERATIONS', false);
var e = tf.add(d, 1);
tf.ENV.set('WEBGL_PACK_BINARY_OPERATIONS', webglPackBinarySaved);
tf.ENV.set('WEBGL_LAZILY_UNPACK', webglLazilyUnpackSaved);
test_util_1.expectArraysClose(e, [2, 3, 4, 5, 6, 7, 8, 9, 10]);
});
it('works when preceded by an op that requires packed inputs', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([0, 1, -3, 2, 2, 1], [3, 2]);
var c = tf.add(a, 1);
var d = tf.matMul(b, c);
test_util_1.expectArraysClose(d, [5, 6, 7, 4, 3, 2, 9, 12, 15]);
});
});
jasmine_util_1.describeWithFlags('matmul', test_util_1.ALL_ENVS, function () {
it('A x B', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([0, 1, -3, 2, 2, 1], [3, 2]);
var c = tf.matMul(a, b);
expect(c.shape).toEqual([2, 2]);
test_util_1.expectArraysClose(c, [0, 8, -3, 20]);
});
it('upcasts when dtypes dont match', function () {
var a = [1, 2, 3, 4, 5, 6];
var b = [0, 1, -3, 2, 2, 1];
var c = tf.matMul(tf.tensor(a, [2, 3], 'float32'), tf.tensor(b, [3, 2], 'int32'));
expect(c.shape).toEqual([2, 2]);
expect(c.dtype).toBe('float32');
test_util_1.expectArraysClose(c, [0, 8, -3, 20]);
c = tf.matMul(tf.tensor(a, [2, 3], 'int32'), tf.tensor(b, [3, 2], 'bool'));
expect(c.shape).toEqual([2, 2]);
expect(c.dtype).toBe('int32');
test_util_1.expectArraysClose(c, [5, 6, 11, 15]);
});
it('A x B^t', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([1, 0, 2, 4, 3, 0], [2, 3]);
var transposeA = false;
var transposeB = true;
var c = tf.matMul(a, b, transposeA, transposeB);
var expected = [7, 10, 16, 31];
test_util_1.expectArraysClose(c, expected);
});
it('A^t x B', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([1, 0, 2, 4, 3, 0], [2, 3]);
var transposeA = true;
var transposeB = false;
var c = tf.matMul(a, b, transposeA, transposeB);
var expected = [17, 12, 2, 22, 15, 4, 27, 18, 6];
test_util_1.expectArraysClose(c, expected);
});
it('A^t x B^t', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
var b = tf.tensor2d([1, 0, 2, 4, 3, 0], [2, 3]);
var transposeA = true;
var transposeB = true;
var c = tf.matMul(a, b, transposeA, transposeB);
var expected = [11, 13, 14, 20];
test_util_1.expectArraysClose(c, expected);
});
it('A x B^t shapes do not match', function () {
var a = tf.zeros([2, 3]);
var b = tf.zeros([3, 2]);
var f = function () {
var transposeA = false;
var transposeB = true;
tf.matMul(a, b, transposeA, transposeB);
};
expect(f).toThrowError();
});
it('A^t x B shapes do not match', function () {
var a = tf.zeros([2, 3]);
var b = tf.zeros([3, 2]);
var f = function () {
var transposeA = true;
var transposeB = false;
tf.matMul(a, b, transposeA, transposeB);
};
expect(f).toThrowError();
});
it('A^t x B^t shapes do not match', function () {
var a = tf.zeros([3, 2]);
var b = tf.zeros([3, 2]);
var f = function () {
var transposeA = true;
var transposeB = true;
tf.matMul(a, b, transposeA, transposeB);
};
expect(f).toThrowError();
});
it('matmul throws when inner dimensions dont match', function () {
var a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var b = tf.tensor2d([0, 1, -3, 2, 2, 1, 2, 2], [4, 2]);
expect(function () { return tf.matMul(a, b); }).toThrowError();
});
it('matmul throws when passed non matrices', function () {
var a = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 3, 2]);
var b = tf.tensor2d([0, 1, -3, 2, 2, 1, 2, 2], [4, 2]);
expect(function () { return tf.matMul(a, b); }).toThrowError();
expect(function () { return tf.matMul(b, a); }).toThrowError();
});
it('matmul throws when passed a vector', function () {
var v = tf.tensor1d([2, 3]);
var matrix = tf.tensor2d([1, 2, 3, 4], [2, 2]);
expect(function () { return tf.matMul(matrix, v); }).toThrowError();
});
it('Vector times matrix', function () {
var v = tf.tensor1d([2, 3]);
var matrix = tf.tensor2d([1, 2, 3, 4], [2, 2]);
var result = tf.dot(v, matrix);
var expected = [11, 16];
test_util_1.expectArraysClose(result, expected);
});
it('Vector times matrix with implicit reshape', function () {
var v = tf.tensor1d([2, 3]);
var matrix = tf.tensor2d([1, 2, 3, 4], [2, 2]);
var result = tf.dot(v, matrix);
var expected = [11, 16];
test_util_1.expectArraysClose(result, expected);
});
it('Matrix times vector', function () {
var matrix = tf.tensor2d([1, 2, 3, 4], [2, 2]);
var v = tf.tensor1d([2, 3]);
var result = tf.dot(matrix, v);
var expected = [8, 18];
test_util_1.expectArraysClose(result, expected);
});
it('batched matmul with the matrices being vectors', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.tensor(values, [batch, 1, sharedDim]);
var b = tf.tensor(values, [batch, sharedDim, 1]);
var result = tf.matMul(a, b);
expect(result.shape).toEqual([batch, 1, 1]);
test_util_1.expectArraysClose(result, [4, 0, 0]);
});
it('batched matmul with the matrices being vectors transposedA', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.tensor(values, [batch, sharedDim, 1]);
var b = tf.tensor(values, [batch, sharedDim, 1]);
var transposeA = true;
var transposeB = false;
var result = tf.matMul(a, b, transposeA, transposeB);
expect(result.shape).toEqual([batch, 1, 1]);
test_util_1.expectArraysClose(result, [4, 0, 0]);
});
it('batched matmul with the matrices being vectors transposedB', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.tensor(values, [batch, 1, sharedDim]);
var b = tf.tensor(values, [batch, 1, sharedDim]);
var transposeA = false;
var transposeB = true;
var result = tf.matMul(a, b, transposeA, transposeB);
expect(result.shape).toEqual([batch, 1, 1]);
test_util_1.expectArraysClose(result, [4, 0, 0]);
});
it('batched matmul with matrix x vector', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.ones([batch, 2, sharedDim]);
var b = tf.tensor(values, [batch, sharedDim, 1]);
var result = tf.matMul(a, b);
expect(result.shape).toEqual([batch, 2, 1]);
test_util_1.expectArraysClose(result, [2, 2, 0, 0, 0, 0]);
});
it('batched matmul with matrix x vector transposedA', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.ones([batch, sharedDim, 2]);
var b = tf.tensor(values, [batch, sharedDim, 1]);
var transposeA = true;
var transposeB = false;
var result = tf.matMul(a, b, transposeA, transposeB);
expect(result.shape).toEqual([batch, 2, 1]);
test_util_1.expectArraysClose(result, [2, 2, 0, 0, 0, 0]);
});
it('batched matmul with matrix x vector transposedB', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.ones([batch, 2, sharedDim]);
var b = tf.tensor(values, [batch, 1, sharedDim]);
var transposeA = false;
var transposeB = true;
var result = tf.matMul(a, b, transposeA, transposeB);
expect(result.shape).toEqual([batch, 2, 1]);
test_util_1.expectArraysClose(result, [2, 2, 0, 0, 0, 0]);
});
it('batched matmul with vector x matrix', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.tensor(values, [batch, 1, sharedDim]);
var b = tf.ones([batch, sharedDim, 2]);
var result = tf.matMul(a, b);
expect(result.shape).toEqual([batch, 1, 2]);
test_util_1.expectArraysClose(result, [2, 2, 0, 0, 0, 0]);
});
it('batched matmul with vector x matrix transposedA', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.tensor(values, [batch, sharedDim, 1]);
var b = tf.ones([batch, sharedDim, 2]);
var transposeA = true;
var transposeB = false;
var result = tf.matMul(a, b, transposeA, transposeB);
expect(result.shape).toEqual([batch, 1, 2]);
test_util_1.expectArraysClose(result, [2, 2, 0, 0, 0, 0]);
});
it('batched matmul with vector x matrix transposedB', function () {
var batch = 3;
var sharedDim = backend_webgl_1.MATMUL_SHARED_DIM_THRESHOLD + 1;
var values = new Float32Array(batch * sharedDim);
values[10] = 2;
var a = tf.tensor(values, [batch, 1, sharedDim]);
var b = tf.ones([batch, 2, sharedDim]);
var transposeA = false;
var transposeB = true;
var result = tf.matMul(a, b, transposeA, transposeB);
expect(result.shape).toEqual([batch, 1, 2]);
test_util_1.expectArraysClose(result, [2, 2, 0, 0, 0, 0]);
});
it('Matrix * vector propagates NaNs', function () {
var matrix = tf.tensor2d([1, 2, 3, 4], [2, 2]);
var v = tf.tensor1d([2, NaN]);
var result = tf.dot(matrix, v);
var expected = [NaN, NaN];
test_util_1.expectArraysClose(result, expected);
});
it('matrix times vector throws when not passed a matrix', function () {
var v = tf.tensor1d([2, 3]);
var matrix = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2]);
expect(function () { return tf.dot(matrix, v); }).toThrowError();
});
it('Dot product', function () {
var v1 = tf.tensor1d([2, 3]);
var v2 = tf.tensor1d([2, 1]);
var result = tf.dot(v1, v2);
test_util_1.expectNumbersClose(result.get(), 7);
});
it('Dot product propagates NaNs', function () {
var v1 = tf.tensor1d([2, NaN]);
var v2 = tf.tensor1d([2, 1]);
var result = tf.dot(v1, v2);
expect(result.get()).toEqual(NaN);
});
it('Dot product throws when vectors are different size', function () {
var v1 = tf.tensor1d([2, 3, 3]);
var v2 = tf.tensor1d([2, 1]);
expect(function () { return tf.dot(v1, v2); }).toThrowError();
expect(function () { return tf.dot(v2, v1); }).toThrowError();
});
it('Outer product', function () {
var v1 = tf.tensor1d([2, 3]);
var v2 = tf.tensor1d([2, 1]);
var result = tf.outerProduct(v1, v2);
var expected = [4, 2, 6, 3];
expect(result.shape).toEqual([2, 2]);
test_util_1.expectArraysClose(result, expected);
});
it('outer product accepts a tensor-like object', function () {
var v1 = [2, 3];
var v2 = [2, 1];
var result = tf.outerProduct(v1, v2);
var expected = [4, 2, 6, 3];
expect(result.shape).toEqual([2, 2]);
test_util_1.expectArraysClose(result, expected);
});
it('gradients: A * B', function () {
var a = tf.tensor2d([1, 2, 3, 10, 20, 30], [2, 3]);
var b = tf.tensor2d([2, 3, 4, 1, 2, 3], [3, 2]);
var dy = tf.tensor2d([1, 10, 20, 30], [2, 2]);
var transposeA = false;
var transposeB = false;
var grads = tf.grads(function (a, b) {
return tf.matMul(a, b, transposeA, transposeB);
});
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
dy.get(0, 0) * b.get(0, 0) + dy.get(0, 1) * b.get(0, 1),
dy.get(0, 0) * b.get(1, 0) + dy.get(0, 1) * b.get(1, 1),
dy.get(0, 0) * b.get(2, 0) + dy.get(0, 1) * b.get(2, 1),
dy.get(1, 0) * b.get(0, 0) + dy.get(1, 1) * b.get(0, 1),
dy.get(1, 0) * b.get(1, 0) + dy.get(1, 1) * b.get(1, 1),
dy.get(1, 0) * b.get(2, 0) + dy.get(1, 1) * b.get(2, 1)
], 1e-1);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
a.get(0, 0) * dy.get(0, 0) + a.get(1, 0) * dy.get(1, 0),
a.get(0, 0) * dy.get(0, 1) + a.get(1, 0) * dy.get(1, 1),
a.get(0, 1) * dy.get(0, 0) + a.get(1, 1) * dy.get(1, 0),
a.get(0, 1) * dy.get(0, 1) + a.get(1, 1) * dy.get(1, 1),
a.get(0, 2) * dy.get(0, 0) + a.get(1, 2) * dy.get(1, 0),
a.get(0, 2) * dy.get(0, 1) + a.get(1, 2) * dy.get(1, 1)
]);
});
it('gradients: a * bT', function () {
var a = tf.tensor2d([1, 2, 3, 10, 20, 30], [3, 2]);
var b = tf.tensor2d([2, 3, 4, 1, 2, 3], [3, 2]);
var dy = tf.tensor2d([1, 10, 20, 30, 40, 50, 60, 70, 80], [3, 3]);
var transposeA = false;
var transposeB = true;
var grads = tf.grads(function (a, b) {
return tf.matMul(a, b, transposeA, transposeB);
});
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
dy.get(0, 0) * b.get(0, 0) + dy.get(0, 1) * b.get(1, 0) +
dy.get(0, 2) * b.get(2, 0),
dy.get(0, 0) * b.get(0, 1) + dy.get(0, 1) * b.get(1, 1) +
dy.get(0, 2) * b.get(2, 1),
dy.get(1, 0) * b.get(0, 0) + dy.get(1, 1) * b.get(1, 0) +
dy.get(1, 2) * b.get(2, 0),
dy.get(1, 0) * b.get(0, 1) + dy.get(1, 1) * b.get(1, 1) +
dy.get(1, 2) * b.get(2, 1),
dy.get(2, 0) * b.get(0, 0) + dy.get(2, 1) * b.get(1, 0) +
dy.get(2, 2) * b.get(2, 0),
dy.get(2, 0) * b.get(0, 1) + dy.get(2, 1) * b.get(1, 1) +
dy.get(2, 2) * b.get(2, 1)
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
dy.get(0, 0) * a.get(0, 0) + dy.get(1, 0) * a.get(1, 0) +
dy.get(2, 0) * a.get(2, 0),
dy.get(0, 0) * a.get(0, 1) + dy.get(1, 0) * a.get(1, 1) +
dy.get(2, 0) * a.get(2, 1),
dy.get(0, 1) * a.get(0, 0) + dy.get(1, 1) * a.get(1, 0) +
dy.get(2, 1) * a.get(2, 0),
dy.get(0, 1) * a.get(0, 1) + dy.get(1, 1) * a.get(1, 1) +
dy.get(2, 1) * a.get(2, 1),
dy.get(0, 2) * a.get(0, 0) + dy.get(1, 2) * a.get(1, 0) +
dy.get(2, 2) * a.get(2, 0),
dy.get(0, 2) * a.get(0, 1) + dy.get(1, 2) * a.get(1, 1) +
dy.get(2, 2) * a.get(2, 1)
]);
});
it('gradients: aT * b', function () {
var a = tf.tensor2d([1, 2, 3, 10, 20, 30], [3, 2]);
var b = tf.tensor2d([2, 3, 4, 1, 2, 3], [3, 2]);
var dy = tf.tensor2d([1, 10, 20, 30], [2, 2]);
var transposeA = true;
var transposeB = false;
var grads = tf.grads(function (a, b) {
return tf.matMul(a, b, transposeA, transposeB);
});
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
dy.get(0, 0) * b.get(0, 0) + dy.get(0, 1) * b.get(0, 1),
dy.get(1, 0) * b.get(0, 0) + dy.get(1, 1) * b.get(0, 1),
dy.get(0, 0) * b.get(1, 0) + dy.get(0, 1) * b.get(1, 1),
dy.get(1, 0) * b.get(1, 0) + dy.get(1, 1) * b.get(1, 1),
dy.get(0, 0) * b.get(2, 0) + dy.get(0, 1) * b.get(2, 1),
dy.get(1, 0) * b.get(2, 0) + dy.get(1, 1) * b.get(2, 1)
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
dy.get(0, 0) * a.get(0, 0) + dy.get(1, 0) * a.get(0, 1),
dy.get(0, 1) * a.get(0, 0) + dy.get(1, 1) * a.get(0, 1),
dy.get(0, 0) * a.get(1, 0) + dy.get(1, 0) * a.get(1, 1),
dy.get(0, 1) * a.get(1, 0) + dy.get(1, 1) * a.get(1, 1),
dy.get(0, 0) * a.get(2, 0) + dy.get(1, 0) * a.get(2, 1),
dy.get(0, 1) * a.get(2, 0) + dy.get(1, 1) * a.get(2, 1)
]);
});
it('gradients: aT * bT', function () {
var a = tf.tensor2d([1, 2, 3, 10, 20, 30], [3, 2]);
var b = tf.tensor2d([2, 3, 4, 1, 2, 3], [2, 3]);
var dy = tf.tensor2d([1, 10, 20, 30], [2, 2]);
var transposeA = true;
var transposeB = true;
var grads = tf.grads(function (a, b) {
return tf.matMul(a, b, transposeA, transposeB);
});
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
dy.get(0, 0) * b.get(0, 0) + dy.get(0, 1) * b.get(1, 0),
dy.get(1, 0) * b.get(0, 0) + dy.get(1, 1) * b.get(1, 0),
dy.get(0, 0) * b.get(0, 1) + dy.get(0, 1) * b.get(1, 1),
dy.get(1, 0) * b.get(0, 1) + dy.get(1, 1) * b.get(1, 1),
dy.get(0, 0) * b.get(0, 2) + dy.get(0, 1) * b.get(1, 2),
dy.get(1, 0) * b.get(0, 2) + dy.get(1, 1) * b.get(1, 2)
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
dy.get(0, 0) * a.get(0, 0) + dy.get(1, 0) * a.get(0, 1),
dy.get(0, 0) * a.get(1, 0) + dy.get(1, 0) * a.get(1, 1),
dy.get(0, 0) * a.get(2, 0) + dy.get(1, 0) * a.get(2, 1),
dy.get(0, 1) * a.get(0, 0) + dy.get(1, 1) * a.get(0, 1),
dy.get(0, 1) * a.get(1, 0) + dy.get(1, 1) * a.get(1, 1),
dy.get(0, 1) * a.get(2, 0) + dy.get(1, 1) * a.get(2, 1)
]);
});
it('throws when passed a as a non-tensor', function () {
expect(function () { return tf.matMul({}, tf.tensor2d([2], [1, 1])); })
.toThrowError(/Argument 'a' passed to 'matMul' must be a Tensor/);
});
it('throws when passed b as a non-tensor', function () {
expect(function () { return tf.matMul(tf.tensor2d([2], [1, 1]), {}); })
.toThrowError(/Argument 'b' passed to 'matMul' must be a Tensor/);
});
it('accepts a tensor-like object', function () {
var a = [[1, 2, 3], [4, 5, 6]];
var b = [[0, 1], [-3, 2], [2, 1]];
var c = tf.matMul(a, b);
expect(c.shape).toEqual([2, 2]);
test_util_1.expectArraysClose(c, [0, 8, -3, 20]);
});
it('accepts a tensor-like object chained', function () {
var a = tf.tensor2d([[1, 2, 3], [4, 5, 6]], [2, 3]);
var b = [[0, 1], [-3, 2], [2, 1]];
var c = a.matMul(b);
expect(c.shape).toEqual([2, 2]);
test_util_1.expectArraysClose(c, [0, 8, -3, 20]);
});
it('a * b where a has zero in its shape', function () {
var a = tf.tensor2d([], [0, 3]);
var b = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
var c = tf.matMul(a, b);
expect(c.shape).toEqual([0, 2]);
expect(c.rank).toBe(2);
expect(c.size).toBe(0);
test_util_1.expectArraysClose(c, []);
});
it('(a * b) * c where a has zero in its shape, so a*b does also', function () {
var a = tf.tensor2d([], [0, 3]);
var b = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
var ab = tf.matMul(a, b);
expect(ab.shape).toEqual([0, 2]);
test_util_1.expectArraysClose(ab, []);
var c = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
var res = tf.matMul(ab, c);
expect(res.shape).toEqual([0, 3]);
test_util_1.expectArraysClose(res, []);
});
it('throws error for string tensor', function () {
expect(function () { return tf.matMul([['a']], [['b']]); })
.toThrowError(/Argument 'a' passed to 'matMul' must be numeric tensor/);
});
});
jasmine_util_1.describeWithFlags('matmulBatch', test_util_1.ALL_ENVS, function () {
it('A x B', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3, 7, -2, 5,
-6, 3, 8, 7, -8, 1, 4, -4, 6, 4, -4, -9, -5, 2, -2
], [5, 2, 3]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 3, 2]);
var c = tf.matMul(a, b);
expect(c.shape).toEqual([5, 2, 2]);
test_util_1.expectArraysClose(c, [
87, 20, -6, -32, -24, -50, -36, -5, 24, 98,
70, 33, -64, 47, -42, -28, -71, 24, 37, 5
]);
});
it('A x B in 4D', function () {
var a = tf.tensor4d([
-2, 3, 5, -5, 3, 9, -3, -5, 1, 1, -9, 9, -6, 6, -8,
-7, -1, 3, 9, -7, -7, 2, 10, -6, -8, -6, 9, -6, 4, -1,
9, -6, 10, 8, -9, 5, -8, -7, 0, 2, -5, -1, -9, -4, 3,
-2, 6, -4, 7, 1, -5, -4, 9, -8, -6, -8, 4, -1, 4, 3,
-7, 8, -7, 5, -3, -2, -4, 9, 2, -1, 1, -10, -3, 5, -4,
6, -8, -8, 9, -3, -5, 10, 3, -3, -3, 9, 3, -3, 2, -8,
10, 1, 9, -2, -2, -3, -4, 6, -10, -1, 8, -8, 7, 3, -2,
3, 6, -2, -2, -4, 1, -5, -4, 0, 5, 1, 9, -8, -2, -1
], [4, 5, 2, 3]);
var b = tf.tensor4d([
-4, -3, -2, -6, 6, -1, -4, -1, 7, -4, 8, -9, -9, 0, -1,
-4, -6, -7, -3, -4, -7, 6, -8, 1, -2, 1, -1, -3, 8, -5,
9, -2, 5, 9, -2, 2, -5, -5, -8, -1, -2, -3, -2, -10, 6,
-3, 0, 1, 6, 7, 1, 2, -4, -5, 2, -5, -7, 9, 3, -6,
6, 4, -4, 6, 10, -3, -2, 8, 10, -8, 10, -1, -9, -7, -8,
-3, 1, 1, -2, -9, -7, -6, -1, 0, 7, -9, -7, -5, 0, -4,
-4, -7, 2, 4, 6, 6, -4, -6, -8, 3, -8, -9, 6, 9, -4,
1, -1, 0, 8, 9, 0, -5, 3, -1, 5, 0, -10, 7, -2, 6
], [4, 5, 3, 2]);
var transposeA = false;
var transposeB = false;
var c = tf.matMul(a, b, transposeA, transposeB);
test_util_1.expectArraysClose(c, [
32, -17, 68, -12, -15, 14, 5, -46, 96, 32, 46, -17, 78, -85,
-28, 46, 94, -35, 0, -13, 31, -52, 17, -87, 96, 47, 32, -2,
-6, 105, 40, -2, 63, 76, 17, 30, 56, -66, -21, 23, -144, 41,
22, 8, 118, -106, -88, -6, -17, 2, 2, -26, 8, -63, -38, -108,
-84, -30, -35, 49, 16, -12, -14, -12, 48, 132, 4, 102, 32, 66,
-4, 33, -13, 1, -40, -25, -3, 61, -18, -20
]);
});
it('A x B^t', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3, 7, -2, 5,
-6, 3, 8, 7, -8, 1, 4, -4, 6, 4, -4, -9, -5, 2, -2
], [5, 2, 3]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 2, 3]);
var transposeA = false;
var transposeB = true;
var c = tf.matMul(a, b, transposeA, transposeB);
expect(c.shape).toEqual([5, 2, 2]);
test_util_1.expectArraysClose(c, [
66, 35, -48, 14, -45, -33, -12, 7, -76, 64,
3, 66, -119, -9, -64, -60, -76, 48, 33, -16
]);
});
it('A^t x B', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3, 7, -2, 5,
-6, 3, 8, 7, -8, 1, 4, -4, 6, 4, -4, -9, -5, 2, -2
], [5, 2, 3]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 2, 3]);
var transposeA = true;
var transposeB = false;
var c = tf.matMul(a, b, transposeA, transposeB);
test_util_1.expectArraysClose(c, [
40, -36, 5, 40, 34, 5, 48, 80, 6, -6, 21, -48, -23, -20, -50,
-12, -21, -12, -58, 15, -96, 23, 6, 39, 20, 109, 42, -67, 45, -40,
76, -52, 40, -15, 1, -60, -58, -3, 36, 40, -6, -24, 51, -33, -28
]);
});
it('A^t x B in 4D', function () {
var a = tf.tensor4d([
-2, 3, 5, -5, 3, 9, -3, -5, 1, 1, -9, 9, -6, 6, -8,
-7, -1, 3, 9, -7, -7, 2, 10, -6, -8, -6, 9, -6, 4, -1,
9, -6, 10, 8, -9, 5, -8, -7, 0, 2, -5, -1, -9, -4, 3,
-2, 6, -4, 7, 1, -5, -4, 9, -8, -6, -8, 4, -1, 4, 3,
-7, 8, -7, 5, -3, -2, -4, 9, 2, -1, 1, -10, -3, 5, -4,
6, -8, -8, 9, -3, -5, 10, 3, -3, -3, 9, 3, -3, 2, -8,
10, 1, 9, -2, -2, -3, -4, 6, -10, -1, 8, -8, 7, 3, -2,
3, 6, -2, -2, -4, 1, -5, -4, 0, 5, 1, 9, -8, -2, -1
], [4, 5, 2, 3]);
var b = tf.tensor4d([
-4, -3, -2, -6, 6, -1, -4, -1, 7, -4, 8, -9, -9, 0, -1,
-4, -6, -7, -3, -4, -7, 6, -8, 1, -2, 1, -1, -3, 8, -5,
9, -2, 5, 9, -2, 2, -5, -5, -8, -1, -2, -3, -2, -10, 6,
-3, 0, 1, 6, 7, 1, 2, -4, -5, 2, -5, -7, 9, 3, -6,
6, 4, -4, 6, 10, -3, -2, 8, 10, -8, 10, -1, -9, -7, -8,
-3, 1, 1, -2, -9, -7, -6, -1, 0, 7, -9, -7, -5, 0, -4,
-4, -7, 2, 4, 6, 6, -4, -6, -8, 3, -8, -9, 6, 9, -4,
1, -1, 0, 8, 9, 0, -5, 3, -1, 5, 0, -10, 7, -2, 6
], [4, 5, 2, 3]);
var transposeA = true;
var transposeB = false;
var c = tf.matMul(a, b, transposeA, transposeB);
test_util_1.expectArraysClose(c, [
38, -24, 9, -30, 9, -9, -74, 39, -19, 8, 11, -30, 56, -67,
46, -40, 71, -74, 82, 42, 55, -50, 6, 1, 60, -18, -13, -15,
-52, -61, 81, -52, 59, -15, 76, 43, 34, -56, 38, 0, 26, -14,
-15, 1, -4, 153, -34, 61, -135, 30, -48, 135, -30, 60, 38, 36,
58, 40, 45, 71, 1, 2, 3, 24, 90, -56, -10, 40, -18, 6,
-30, 14, 34, 65, 27, 24, -29, -44, -46, -3, 35, -21, 27, 48,
20, 52, 32, 35, -11, -46, -12, 22, 13, 30, 2, -23, -54, -48,
34, 16, -42, -39, -26, 82, 89, 76, -84, 30, 9, 27, 30, -21,
-43, -48, 60, 20, 24, -78, -91, -63, -12, 24, 21, 28, 48, 35,
-6, 27, 33, 53, -81, -71, 61, -27, 11, -48, -82, 8, -12, -19,
-10, -48, -81, 0, 13, 32, 41, 0, -100, -120, 16, 124, 152, 45,
60, -28, 24, 21, -12, -14, -16, 8, 9, -33, 5, -12, -48, 4,
8, 9, 0, -31, 16, -98, -9, 4, -22, 38, 2, -96
]);
});
it('A^t x B^t', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3, 7, -2, 5,
-6, 3, 8, 7, -8, 1, 4, -4, 6, 4, -4, -9, -5, 2, -2
], [5, 3, 2]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 2, 3]);
var transposeA = true;
var transposeB = true;
var c = tf.matMul(a, b, transposeA, transposeB);
test_util_1.expectArraysClose(c, [
66, 42, 16, -56, -12, 6, -30, 19, -1, 102,
-94, 14, -56, 32, 100, -56, -47, -11, 5, -31
]);
});
it('batch dimensions do not match', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3,
7, -2, 5, -6, 3, 8, 7, -8, 1, 4, -4, 6
], [4, 3, 2]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 2, 3]);
var f = function () {
tf.matMul(a, b, false, false);
};
expect(f).toThrowError();
});
it('gradients: A x B', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3, 7, -2, 5,
-6, 3, 8, 7, -8, 1, 4, -4, 6, 4, -4, -9, -5, 2, -2
], [5, 2, 3]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 3, 2]);
var dy = tf.tensor3d([8, 2, -3, -2, -8, 4, 5, 7, 4, -4, -4, 5, 8, 10, 1, 0, 6, 6, -4, 7], [5, 2, 2]);
var grads = tf.grads(function (a, b) { return tf.matMul(a, b, false, false); });
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
-72, -8, -56, 32, 3, 21, -12, -40, 40, 36, 44, 51, -52, -44, -4,
61, 49, 13, -2, -10, -108, -9, 0, -1, -24, 60, -6, 49, 26, -40
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
-64, -26, -34, -6, -24, 4, -77, -47, 51, -35, 63, -3, 52, -58, -20,
23, -12, 20, 60, 70, -68, -80, 14, 10, 44, -11, -32, -10, -46, -68
]);
});
it('4d gradients: A x B', function () {
var a = tf.tensor4d([
-2, 3, 5, -5, 3, 9, -3, -5, 1, 1, -9, 9, -6, 6, -8,
-7, -1, 3, 9, -7, -7, 2, 10, -6, -8, -6, 9, -6, 4, -1,
9, -6, 10, 8, -9, 5, -8, -7, 0, 2, -5, -1, -9, -4, 3,
-2, 6, -4, 7, 1, -5, -4, 9, -8, -6, -8, 4, -1, 4, 3,
-7, 8, -7, 5, -3, -2, -4, 9, 2, -1, 1, -10, -3, 5, -4,
6, -8, -8, 9, -3, -5, 10, 3, -3, -3, 9, 3, -3, 2, -8,
10, 1, 9, -2, -2, -3, -4, 6, -10, -1, 8, -8, 7, 3, -2,
3, 6, -2, -2, -4, 1, -5, -4, 0, 5, 1, 9, -8, -2, -1
], [4, 5, 2, 3]);
var b = tf.tensor4d([
-4, -3, -2, -6, 6, -1, -4, -1, 7, -4, 8, -9, -9, 0, -1,
-4, -6, -7, -3, -4, -7, 6, -8, 1, -2, 1, -1, -3, 8, -5,
9, -2, 5, 9, -2, 2, -5, -5, -8, -1, -2, -3, -2, -10, 6,
-3, 0, 1, 6, 7, 1, 2, -4, -5, 2, -5, -7, 9, 3, -6,
6, 4, -4, 6, 10, -3, -2, 8, 10, -8, 10, -1, -9, -7, -8,
-3, 1, 1, -2, -9, -7, -6, -1, 0, 7, -9, -7, -5, 0, -4,
-4, -7, 2, 4, 6, 6, -4, -6, -8, 3, -8, -9, 6, 9, -4,
1, -1, 0, 8, 9, 0, -5, 3, -1, 5, 0, -10, 7, -2, 6
], [4, 5, 3, 2]);
var dy = tf.tensor4d([
8, -7, 0, -9, -5, -5, 0, 3, 7, -4, 6, -8, -8, 0, -1, -8,
-9, -7, -4, -9, 2, 3, 5, 8, -5, -7, 3, -10, -5, -9, -5, 1,
7, 1, -9, -10, 8, 5, 0, 8, -6, 4, 0, -5, 8, -7, -2, 1,
-8, 9, 9, -7, 1, 7, -2, 5, -2, 9, 1, -5, 7, 5, -7, -6,
6, 7, -8, 7, 4, -5, 4, -5, 3, -4, -5, 4, -6, 3, -8, 10
], [4, 5, 2, 2]);
var grads = tf.grads(function (a, b) { return tf.matMul(a, b, false, false); });
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
-11, 26, 55, 27, 54, 9, 25, -15, 5, -3, -12, -27, -63, 9,
-14, -54, 26, 20, 24, 56, 64, 35, -41, 0, 11, 30, -37, -1,
31, 13, 12, 37, 2, 29, 97, 6, 60, 47, 31, 35, -14, 24,
100, -3, -9, 0, -33, 1, 49, 9, -33, -124, -29, 86, -9, -11,
-6, -40, 72, -48, -20, 48, -72, -20, -30, 15, -72, 136, 87, 12,
-28, -21, 9, 37, 1, -32, -51, 2, -65, -49, -1, -41, -16, 2,
-95, -31, -36, 52, 18, 20, -63, 34, 72, 70, -38, -78, -66, -27,
-111, -10, 85, 1, -21, -21, -4, -21, -21, -4, -12, 20, 13, -4,
-20, -19, -30, 81, 30, -40, 150, 76
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
-16, 59, 24, -48, 40, -116, 15, 18, 25, -2, -5, 22, -84, 80,
36, -16, -38, 8, -74, -16, 46, -80, 62, 48, 96, 110, 38, 6,
-77, -54, 58, 91, -57, -90, 45, 70, 46, 36, 20, 99, -3, 10,
55, 79, -10, 42, 5, -31, 85, 47, -74, -89, 37, 75, -48, -38,
-64, -8, 32, 44, 42, -53, -48, 47, 42, -18, -30, 27, 70, -62,
36, -24, 78, -69, -112, 101, -40, 20, -11, 113, -9, -6, 1, -50,
3, -12, -16, 71, -14, 67, 84, 62, 21, 17, 84, 63, -16, -35,
-28, 98, 4, -126, 40, -50, 36, -45, -16, 20, 19, -12, 8, 0,
3, -4, 34, -65, 10, -17, -46, 17
]);
});
it('gradients: A x B^t', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3, 7, -2, 5,
-6, 3, 8, 7, -8, 1, 4, -4, 6, 4, -4, -9, -5, 2, -2
], [5, 3, 2]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 3, 2]);
var dy = tf.tensor3d([
-0, 7, 5, 0, -9, 5, -7, 6, -5, -3, -2, -2, -4, 10, -3,
5, -1, 3, -2, -9, 4, -5, 7, 9, -10, -8, -8, -5, -0, -1,
3, 3, 4, 9, -7, 6, -2, -9, 5, 1, -5, -3, -1, 9, 4
], [5, 3, 3]);
var grads = tf.grads(function (a, b) { return tf.matMul(a, b, false, true); });
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
-42, 0, -26, 0, 85, 28, -19, -29, 51, -16, 6, 37, 94, -27, 50,
71, 24, -202, 46, -25, -31, -22, -87, 10, -7, -80, -36, -15, 55, 35
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
14, 56, 7, -155, -45, 55, 7, 72, -67, -79, 7, 50, -69, -46, -52,
-88, 49, -126, -68, 106, 31, -30, -27, 60, -19, 5, 27, 43, 55, -13
]);
});
it('4d gradients: A x B^t', function () {
var a = tf.tensor4d([
-2, 3, 5, -5, 3, 9, -3, -5, 1, 1, -9, 9, -6, 6, -8,
-7, -1, 3, 9, -7, -7, 2, 10, -6, -8, -6, 9, -6, 4, -1,
9, -6, 10, 8, -9, 5, -8, -7, 0, 2, -5, -1, -9, -4, 3,
-2, 6, -4, 7, 1, -5, -4, 9, -8, -6, -8, 4, -1, 4, 3,
-7, 8, -7, 5, -3, -2, -4, 9, 2, -1, 1, -10, -3, 5, -4,
6, -8, -8, 9, -3, -5, 10, 3, -3, -3, 9, 3, -3, 2, -8,
10, 1, 9, -2, -2, -3, -4, 6, -10, -1, 8, -8, 7, 3, -2,
3, 6, -2, -2, -4, 1, -5, -4, 0, 5, 1, 9, -8, -2, -1
], [4, 5, 3, 2]);
var b = tf.tensor4d([
-4, -3, -2, -6, 6, -1, -4, -1, 7, -4, 8, -9, -9, 0, -1,
-4, -6, -7, -3, -4, -7, 6, -8, 1, -2, 1, -1, -3, 8, -5,
9, -2, 5, 9, -2, 2, -5, -5, -8, -1, -2, -3, -2, -10, 6,
-3, 0, 1, 6, 7, 1, 2, -4, -5, 2, -5, -7, 9, 3, -6,
6, 4, -4, 6, 10, -3, -2, 8, 10, -8, 10, -1, -9, -7, -8,
-3, 1, 1, -2, -9, -7, -6, -1, 0, 7, -9, -7, -5, 0, -4,
-4, -7, 2, 4, 6, 6, -4, -6, -8, 3, -8, -9, 6, 9, -4,
1, -1, 0, 8, 9, 0, -5, 3, -1, 5, 0, -10, 7, -2, 6
], [4, 5, 3, 2]);
var dy = tf.tensor4d([
5, -1, -5, -4, -1, 9, 1, -2, 10, 7, -1, 6, -8, 8, -3,
9, -4, 2, -4, -8, 8, 4, 8, -10, -8, -8, 6, 6, -5, 9,
-1, -7, -5, -3, -3, 2, -6, 5, 8, -9, 5, -8, -3, 8, 6,
2, 8, 5, 9, 7, 6, 2, -3, 10, 7, 7, -3, 4, -3, -6,
-8, -8, 9, 0, -8, -3, -2, -2, 8, 2, 3, -6, 3, 6, -3,
7, 7, -9, -3, 8, 7, 7, -1, -6, 5, 2, -1, -1, 1, 5,
0, -4, 3, -4, -10, 1, -2, -8, -9, -6, 4, 4, -7, -1, -1,
-9, 7, 1, -1, 8, 0, -2, -7, 5, 7, 8, 9, -3, -8, -6,
-7, -8, -1, 8, -4, 7, 5, -9, 9, 3, 0, -10, 7, -9, 4,
-7, 5, -2, -2, 3, 3, -6, 2, 0, 8, -5, -10, 3, -7, 0,
-6, 2, 3, -1, 3, 3, -10, 1, 3, -7, -1, 8, -2, -1, -1,
-3, -9, 7, 4, -6, 3, 0, -7, -4, -5, -8, -6, 10, -6, 4
], [4, 5, 3, 3]);
var grads = tf.grads(function (a, b) { return tf.matMul(a, b, false, true); });
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
-48, -4, 72, 9, 60, -1, 13, -57, 64, 3, -48, -11, -4, -24,
16, 38, 44, -10, -55, -45, 92, -43, 14, -4, 71, -61, -51, 16,
46, -57, 48, 78, 104, 57, -17, -11, -85, -33, 16, 1, 86, 21,
-48, 21, -8, 34, 14, -35, 36, 48, 85, 108, -38, -40, 3, -8,
-7, -1, 6, -16, 46, -33, 26, -79, -70, -29, 92, -84, -6, -47,
98, -129, -55, -17, 79, 40, -118, -64, 68, 75, 71, 111, 5, -48,
98, -36, 21, 13, 112, -34, 26, 57, 32, 44, 28, 50, 88, 27,
44, -39, -16, 15, -21, -6, -67, -89, -46, -64, -19, -12, -3, 11,
41, 63, 78, -73, 67, -92, 102, -18
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
-27, 44, -9, -16, 85, 30, -110, 38, 47, -23, -39, -15, 0, -76,
-8, -128, 26, 136, 31, -26, -26, 39, 136, -85, -45, 93, 37, -68,
-112, -6, 90, 70, 169, -7, 15, 68, -16, -33, -16, -47, -21, 0,
6, -4, 84, 24, 15, 20, -41, -1, 79, -86, 87, -23, -26, -64,
18, 9, 52, 64, 34, -16, 122, -66, -1, 47, 1, 43, -11, -33,
-17, 27, -45, -73, -60, -66, -92, -42, 32, -85, -44, -44, -28, -13,
8, -20, 9, -9, -49, 79, -76, 15, 73, -7, 7, -8, -110, 93,
106, -39, 64, -84, -29, -19, 13, 14, 63, 2, -15, 23, 17, 49,
-3, -31, -65, 30, -95, 63, -82, 40
]);
});
it('gradients: A^t x B', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3, 7, -2, 5,
-6, 3, 8, 7, -8, 1, 4, -4, 6, 4, -4, -9, -5, 2, -2
], [5, 3, 2]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 3, 2]);
var dy = tf.tensor3d([8, 2, -3, -2, -8, 4, 5, 7, 4, -4, -4, 5, 8, 10, 1, 0, 6, 6, -4, 7], [5, 2, 2]);
var grads = tf.grads(function (a, b) { return tf.matMul(a, b, true, false); });
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
-72, 32, -8, 3, -56, 21, -12, 36, -40, 44, 40, 51, -52, 61, -44,
49, -4, 13, -2, -9, -10, 0, -108, -1, -24, 49, 60, 26, -6, -40
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
-25, 0, -72, -28, 8, 12, -67, -33, 3, -87, 23, 17, 36, -38, 44,
-50, -20, 28, 48, 70, 12, 10, -26, -40, 40, -4, -34, -89, 20, -2
]);
});
it('gradients: A^t x B^t', function () {
var a = tf.tensor3d([
-5, -5, -6, 8, -2, -8, 4, -7, -6, -9, -1, 3, 7, -2, 5,
-6, 3, 8, 7, -8, 1, 4, -4, 6, 4, -4, -9, -5, 2, -2
], [5, 3, 2]);
var b = tf.tensor3d([
-8, -4, -1, 0, -7, 0, 3, 3, 6, 2, -1, 8, -4, 9, -6,
5, 8, 9, -9, 7, 0, -1, -1, -10, -7, 3, 4, 6, 3, -4
], [5, 2, 3]);
var dy = tf.tensor3d([8, 2, -3, -2, -8, 4, 5, 7, 4, -4, -4, 5, 8, 10, 1, 0, 6, 6, -4, 7], [5, 2, 2]);
var grads = tf.grads(function (a, b) { return tf.matMul(a, b, true, true); });
var _a = grads([a, b], dy), da = _a[0], db = _a[1];
expect(da.shape).toEqual(a.shape);
test_util_1.expectArraysClose(da, [
-64, 24, -46, 26, -8, 3, -16, 29, -28, 8, -16, 86, -36, 41, 4,
4, -60, 69, -82, -9, 46, 7, -100, 0, -6, 70, 36, 9, 0, -44
]);
expect(db.shape).toEqual(b.shape);
test_util_1.expectArraysClose(db, [
-25, -72, 8, 0, -28, 12, -67, 3, 23, -33, -87, 17, 36, 44, -20,
-38, -50, 28, 48, 12, -26, 70, 10, -40, 40, -34, 20, -4, -89, -2
]);
});
});
jasmine_util_1.describeWithFlags('matmul webgl-only', test_util_1.WEBGL_ENVS, function () {
it('Matrix times vector, large matrix', function () {
var maxTexSize = 16000;
var sharedDim = maxTexSize + 4;
var matrix = tf.buffer([2, sharedDim], 'float32');
matrix.set(1, 0, sharedDim - 3);
matrix.set(1, 0, sharedDim - 2);
var v = tf.buffer([sharedDim], 'float32');
v.set(1, sharedDim - 3);
v.set(1, sharedDim - 2);
var result = tf.dot(matrix.toTensor(), v.toTensor());
var expected = [2, 0];
test_util_1.expectArraysClose(result, expected);
});
});
jasmine_util_1.describeWithFlags('dot', test_util_1.ALL_ENVS, function () {
var a;
var b;
var c;
var d;
var e;
beforeEach(function () {
a = tf.tensor1d([1, 2]);
b = tf.tensor2d([[1, 2], [3, 4]]);
c = tf.tensor2d([[1, 2, 3], [4, 5, 6]]);
d = tf.tensor3d([1, 2], [1, 1, 2]);
e = tf.scalar(1);
});
it('vector-vector', function () {
var aa = tf.dot(a, a);
test_util_1.expectArraysClose(aa, [5]);
expect(aa.shape).toEqual([]);
});
it('vector-matrix', function () {
var ab = tf.dot(a, b);
var ac = tf.dot(a, c);
expect(ab.shape).toEqual([2]);
expect(ac.shape).toEqual([3]);
test_util_1.expectArraysClose(ab, [7, 10]);
test_util_1.expectArraysClose(ac, [9, 12, 15]);
});
it('matrix-vector', function () {
var ba = b.dot(a);
expect(ba.shape).toEqual([2]);
test_util_1.expectArraysClose(ba, [5, 11]);
});
it('matrix-matrix', function () {
var bb = tf.dot(b, b);
var bc = tf.dot(b, c);
expect(bb.shape).toEqual([2, 2]);
expect(bc.shape).toEqual([2, 3]);
test_util_1.expectArraysClose(bb, [7, 10, 15, 22]);
test_util_1.expectArraysClose(bc, [9, 12, 15, 19, 26, 33]);
});
it('throws error on incompatible dimensions', function () {
expect(function () { return tf.dot(c, a); }).toThrowError();
expect(function () { return tf.dot(c, b); }).toThrowError();
});
it('throws error when inputs are not rank 1 or 2', function () {
expect(function () { return tf.dot(a, d); }).toThrowError();
expect(function () { return tf.dot(a, e); }).toThrowError();
});
it('accepts a tensor-like object', function () {
var a = [1, 2, 3];
var res = tf.dot(a, a);
test_util_1.expectArraysClose(res, [14]);
expect(res.shape).toEqual([]);
});
it('throws error for string tensors', function () {
expect(function () { return tf.dot('a', 'b'); })
.toThrowError(/Argument 't1' passed to 'dot' must be numeric tensor/);
});
});
//# sourceMappingURL=matmul_test.js.map