gx

chenyc

2025-06-12 7b72ac13a83764a662159d4a49b7fffb90476ecb

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/**
 * @license
 * Copyright 2018 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
import { ValueError } from '../errors';
import { pyListRepeat } from './generic_utils';
import { isInteger, max } from './math_utils';
/**
 * Transforms a single number of array of numbers into an array of numbers.
 * @param value
 * @param n: The size of the tuple to be returned.
 * @param name: Name of the parameter, used for generating error messages.
 * @returns An array of numbers.
 */
export function normalizeArray(value, n, name) {
    if (typeof value === 'number') {
        return pyListRepeat(value, n);
    }
    else {
        if (value.length !== n) {
            throw new ValueError(`The ${name} argument must be an integer or tuple of ${n} integers.` +
                ` Received: ${value.length} elements.`);
        }
        for (let i = 0; i < n; ++i) {
            const singleValue = value[i];
            if (!isInteger(singleValue)) {
                throw new ValueError(`The ${name} argument must be an integer or tuple of ${n}` +
                    ` integers. Received: ${JSON.stringify(value)} including a` +
                    ` non-integer number ${singleValue}`);
            }
        }
        return value;
    }
}
/**
 * Determines output length of a convolution given input length.
 * @param inputLength
 * @param filterSize
 * @param padding
 * @param stride
 * @param dilation: dilation rate.
 */
export function convOutputLength(inputLength, filterSize, padding, stride, dilation = 1) {
    if (inputLength == null) {
        return inputLength;
    }
    const dilatedFilterSize = filterSize + (filterSize - 1) * (dilation - 1);
    let outputLength;
    if (padding === 'same') {
        outputLength = inputLength;
    }
    else { // VALID
        outputLength = inputLength - dilatedFilterSize + 1;
    }
    return Math.floor((outputLength + stride - 1) / stride);
}
export function deconvLength(dimSize, strideSize, kernelSize, padding) {
    if (dimSize == null) {
        return null;
    }
    if (padding === 'valid') {
        dimSize = dimSize * strideSize + max([kernelSize - strideSize, 0]);
    }
    else if (padding === 'same') {
        dimSize = dimSize * strideSize;
    }
    else {
        throw new ValueError(`Unsupport padding mode: ${padding}.`);
    }
    return dimSize;
}
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