代码搜索：batch
找到约 6,125 项符合「batch」的源代码
代码结果 6,125
www.eeworm.com/read/462460/1545831
bat sqlcli.bat
@echo off
rem Performs SQL Server Client Unattended Install operation
rem Before running this batch file, you must edit the corresponding
rem unattended install file (sqlcli.iss), and enter yo
www.eeworm.com/read/462460/1545836
bat sqlins.bat
@echo off
rem Performs SQL Server Full Server Unattended Install operation
rem Before running this batch file, you must edit the corresponding
rem unattended install file (sqlins.iss), and ent
www.eeworm.com/read/164931/5485782
src buildindex.src
#!/usr/bin/pbs_tclsh
# OpenPBS (Portable Batch System) v2.3 Software License
#
# Copyright (c) 1999-2000 Veridian Information Solutions, Inc.
# All rights reserved.
#
# ---------------------
www.eeworm.com/read/273525/4205620
ado whelp.ado
*! version 1.0.4 17feb2005
program whelp
version 9
if "`c(console)'" == "console" | "$S_MODE"=="batch" {
chelp `0'
}
else {
syntax [anything(everything)] [, noNew name(name) MARKer(n
www.eeworm.com/read/437018/1838519
txt spice.txt
SUBJECT: dashb
TITLE: -b
TEXT:
TEXT: G-b HRun in batch mode. Instead of prompting the user
TEXT: H interactively, Gspice Hwill execute the source files
TEXT: H given o
www.eeworm.com/read/396363/2422462
bat build.bat
@echo off
rem
rem This batch file builds and preverifies the code for the demos.
rem it then packages them in a JAR file appropriately.
rem
if "%OS%" == "Windows_NT" setlocal
set DEMO=FPDemo
se
www.eeworm.com/read/396363/2422464
bat run.bat
@echo off
rem This file runs the corresponded demo.
if "%OS%" == "Windows_NT" setlocal
set DEMO=FPDemo
if not exist .\%DEMO%.jad (
echo *** Run this batch file from its location directory o
www.eeworm.com/read/386597/2570100
m perceptron_bvi.m
function [test_targets, a] = Perceptron_BVI(train_patterns, train_targets, test_patterns, params)
% Classify using the batch variable increment Perceptron algorithm
% Inputs:
% train_patterns -
www.eeworm.com/read/386597/2570110
m backpropagation_quickprop.m
function [test_targets, Wh, Wo, J] = Backpropagation_Quickprop(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm and q