@tensorflow/tfjs-core/dist/ops/linalg/band_part.d.ts

Hardware-accelerated JavaScript library for machine intelligence

/**
 * @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.
 * =============================================================================
 */
/// <amd-module name="@tensorflow/tfjs-core/dist/ops/linalg/band_part" />
import { Scalar, Tensor } from '../../tensor';
import { TensorLike } from '../../types';
/**
 * Copy a tensor setting everything outside a central band in each innermost
 * matrix to zero.
 *
 * The band part is computed as follows: Assume input has `k` dimensions
 * `[I, J, K, ..., M, N]`, then the output is a tensor with the same shape where
 * `band[i, j, k, ..., m, n] = in_band(m, n) * input[i, j, k, ..., m, n]`.
 * The indicator function
 * `in_band(m, n) = (num_lower < 0 || (m-n) <= num_lower)`
 * `&& (num_upper < 0 || (n-m) <= num_upper)`
 *
 * ```js
 * const x = tf.tensor2d([[ 0,  1,  2, 3],
 *                        [-1,  0,  1, 2],
 *                        [-2, -1,  0, 1],
 *                        [-3, -2, -1, 0]]);
 * let y = tf.linalg.bandPart(x, 1, -1);
 * y.print(); // [[ 0,  1,  2, 3],
 *            //  [-1,  0,  1, 2],
 *            //  [ 0, -1,  0, 1],
 *            //  [ 0, 0 , -1, 0]]
 * let z = tf.linalg.bandPart(x, 2, 1);
 * z.print(); // [[ 0,  1,  0, 0],
 *            //  [-1,  0,  1, 0],
 *            //  [-2, -1,  0, 1],
 *            //  [ 0, -2, -1, 0]]
 * ```
 *
 * @param x Rank `k` tensor
 * @param numLower Number of subdiagonals to keep.
 *   If negative, keep entire lower triangle.
 * @param numUpper Number of subdiagonals to keep.
 *   If negative, keep entire upper triangle.
 * @returns Rank `k` tensor of the same shape as input.
 *   The extracted banded tensor.
 *
 * @doc {heading:'Operations', subheading:'Linear Algebra', namespace:'linalg'}
 */
declare function bandPart_<T extends Tensor>(a: T | TensorLike, numLower: number | Scalar, numUpper: number | Scalar): T;
export declare const bandPart: typeof bandPart_;
export {};