@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
;
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
Object.defineProperty(exports, "__esModule", { value: true });
var backend_util = require("../../../backends/backend_util");
var util = require("../../../util");
var cpu_util_1 = require("../cpu_util");
function createBinaryKernelConfig(name, op) {
return {
kernelName: name,
backendName: 'cpu',
kernelFunc: function (_a) {
var inputs = _a.inputs, backend = _a.backend;
var _b = inputs, a = _b.a, b = _b.b;
var cpuBackend = backend;
cpu_util_1.assertNotComplex([a, b], name);
var aVals = cpuBackend.data.get(a.dataId).values;
var bVals = cpuBackend.data.get(b.dataId).values;
var _c = op(a.shape, b.shape, aVals, bVals, a.dtype), resultData = _c[0], resultShape = _c[1];
var dataId = cpuBackend.write(resultData, resultShape, a.dtype);
return { dataId: dataId, shape: resultShape, dtype: a.dtype };
}
};
}
exports.createBinaryKernelConfig = createBinaryKernelConfig;
function createBinaryKernelImpl(op) {
return function (aShape, bShape, aVals, bVals, dtype) {
var newShape = backend_util.assertAndGetBroadcastShape(aShape, bShape);
var resultRank = newShape.length;
var resultStrides = util.computeStrides(newShape);
var resultSize = util.sizeFromShape(newShape);
var result = util.getTypedArrayFromDType(dtype, resultSize);
var aRank = aShape.length;
var bRank = bShape.length;
var aStrides = util.computeStrides(aShape);
var bStrides = util.computeStrides(bShape);
var aBroadcastDims = backend_util.getBroadcastDims(aShape, newShape);
var bBroadcastDims = backend_util.getBroadcastDims(bShape, newShape);
if (aBroadcastDims.length + bBroadcastDims.length === 0) {
for (var i = 0; i < result.length; ++i) {
result[i] = op(aVals[i % aVals.length], bVals[i % bVals.length]);
}
}
else {
var _loop_1 = function (i) {
var loc = util.indexToLoc(i, resultRank, resultStrides);
var aLoc = loc.slice(-aRank);
aBroadcastDims.forEach(function (d) { return aLoc[d] = 0; });
var aIndex = util.locToIndex(aLoc, aRank, aStrides);
var bLoc = loc.slice(-bRank);
bBroadcastDims.forEach(function (d) { return bLoc[d] = 0; });
var bIndex = util.locToIndex(bLoc, bRank, bStrides);
result[i] = op(aVals[aIndex], bVals[bIndex]);
};
for (var i = 0; i < result.length; ++i) {
_loop_1(i);
}
}
return [result, newShape];
};
}
exports.createBinaryKernelImpl = createBinaryKernelImpl;
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