@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
77 lines • 4.19 kB
JavaScript
;
var __decorate = (this && this.__decorate) || function (decorators, target, key, desc) {
var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;
if (typeof Reflect === "object" && typeof Reflect.decorate === "function") r = Reflect.decorate(decorators, target, key, desc);
else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;
return c > 3 && r && Object.defineProperty(target, key, r), r;
};
Object.defineProperty(exports, "__esModule", { value: true });
var doc_1 = require("../doc");
var environment_1 = require("../environment");
var types = require("../types");
var util = require("../util");
var broadcast_util = require("./broadcast_util");
var operation_1 = require("./operation");
var LogicalOps = (function () {
function LogicalOps() {
}
LogicalOps.logicalNot = function (x) {
util.assertArgumentsAreTensors({ x: x }, 'logicalNot');
util.assert(x.dtype === 'bool', 'Error Array must be of type bool.');
return environment_1.ENV.engine.runKernel(function (backend) { return backend.logicalNot(x); }, { x: x });
};
LogicalOps.logicalAnd = function (a, b) {
util.assertArgumentsAreTensors({ a: a, b: b }, 'logicalAnd');
util.assert(a.dtype === 'bool' && b.dtype === 'bool', 'Error Array must be of type bool.');
broadcast_util.assertAndGetBroadcastShape(a.shape, b.shape);
return environment_1.ENV.engine.runKernel(function (backend) { return backend.logicalAnd(a, b); }, { a: a, b: b });
};
LogicalOps.logicalOr = function (a, b) {
util.assertArgumentsAreTensors({ a: a, b: b }, 'logicalOr');
util.assert(a.dtype === 'bool' && b.dtype === 'bool', 'Error Array must be of type bool.');
broadcast_util.assertAndGetBroadcastShape(a.shape, b.shape);
return environment_1.ENV.engine.runKernel(function (backend) { return backend.logicalOr(a, b); }, { a: a, b: b });
};
LogicalOps.logicalXor = function (a, b) {
util.assertArgumentsAreTensors({ a: a, b: b }, 'logicalXor');
util.assert(a.dtype === 'bool' && b.dtype === 'bool', 'Error Array must be of type bool.');
broadcast_util.assertAndGetBroadcastShape(a.shape, b.shape);
return LogicalOps.logicalOr(a, b).logicalAnd(LogicalOps.logicalAnd(a, b).logicalNot());
};
LogicalOps.where = function (condition, a, b) {
util.assertArgumentsAreTensors({ condition: condition, a: a, b: b }, 'where');
util.assert(condition.dtype === 'bool' || a.dtype === 'bool' || b.dtype === 'bool', 'Error Array must be of type bool.');
util.assertShapesMatch(a.shape, b.shape, 'Error in where: ');
if (condition.rank === 1) {
util.assert(condition.shape[0] === a.shape[0], 'The first dimension of `a` must match the size of `condition`.');
}
else {
util.assertShapesMatch(condition.shape, b.shape, 'Error in where: ');
}
var dtype = types.upcastType(a.dtype, b.dtype);
return environment_1.ENV.engine.runKernel(function (backend) { return backend.where(condition, a, b, dtype); }, { condition: condition, a: a, b: b });
};
__decorate([
doc_1.doc({ heading: 'Operations', subheading: 'Logical' }),
operation_1.operation
], LogicalOps, "logicalNot", null);
__decorate([
doc_1.doc({ heading: 'Operations', subheading: 'Logical' }),
operation_1.operation
], LogicalOps, "logicalAnd", null);
__decorate([
doc_1.doc({ heading: 'Operations', subheading: 'Logical' }),
operation_1.operation
], LogicalOps, "logicalOr", null);
__decorate([
doc_1.doc({ heading: 'Operations', subheading: 'Logical' }),
operation_1.operation
], LogicalOps, "logicalXor", null);
__decorate([
doc_1.doc({ heading: 'Operations', subheading: 'Logical' }),
operation_1.operation
], LogicalOps, "where", null);
return LogicalOps;
}());
exports.LogicalOps = LogicalOps;
//# sourceMappingURL=logical_ops.js.map