@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
71 lines • 2.76 kB
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.
* =============================================================================
*/
import { buffer } from './buffer';
import { expandDims } from './expand_dims';
import { op } from './operation';
import { reshape } from './reshape';
import { tile } from './tile';
/**
* Create an identity matrix.
*
* @param numRows Number of rows.
* @param numColumns Number of columns. Defaults to `numRows`.
* @param batchShape If provided, will add the batch shape to the beginning
* of the shape of the returned `tf.Tensor` by repeating the identity
* matrix.
* @param dtype Data type.
* @returns Identity matrix of the specified size and data type, possibly
* with batch repetition if `batchShape` is specified.
*
* @doc {heading: 'Tensors', subheading: 'Creation'}
*/
function eye_(numRows, numColumns, batchShape, dtype = 'float32') {
if (numColumns == null) {
numColumns = numRows;
}
const buff = buffer([numRows, numColumns], dtype);
const n = numRows <= numColumns ? numRows : numColumns;
for (let i = 0; i < n; ++i) {
buff.set(1, i, i);
}
const out = reshape(buff.toTensor(), [numRows, numColumns]);
if (batchShape == null) {
return out;
}
else {
if (batchShape.length === 1) {
return tile(expandDims(out, 0), [batchShape[0], 1, 1]);
}
else if (batchShape.length === 2) {
// tslint:disable-next-line:no-unnecessary-type-assertion
return tile(expandDims(expandDims(out, 0), 0), [batchShape[0], batchShape[1], 1, 1]);
}
else if (batchShape.length === 3) {
// tslint:disable-next-line:no-unnecessary-type-assertion
return tile(expandDims(expandDims(expandDims(out, 0), 0), 0), [
batchShape[0], batchShape[1], batchShape[2], 1, 1
]);
}
else {
throw new Error(`eye() currently supports only 1D and 2D ` +
// tslint:disable-next-line:no-any
`batchShapes, but received ${batchShape.length}D.`);
}
}
}
export const eye = op({ eye_ });
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