代码搜索：batch

找到约 6,125 项符合「batch」的源代码

代码结果 6,125
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www.eeworm.com/read/124399/6049875

exp drtest01.exp

TRUE CLIPS> (batch "drtest01.bat") TRUE CLIPS> (toss "a") ; DR0001 FALSE CLIPS> (toss a) ; DR0001 FALSE CLIPS> (clear) ; DR000
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www.eeworm.com/read/124399/6050063

exp predcfnx.exp

TRUE CLIPS> (batch "predcfnx.bat") TRUE CLIPS> (numberp) ; 10.2.1 [ARGACCES4] Function numberp expected exactly 1 argument(s) CLIPS> (numberp 3 a) ; 10.2.
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www.eeworm.com/read/121298/6068848

java batchfiletokenmarker.java

/* * BatchFileTokenMarker.java - Batch file token marker * Copyright (C) 1998, 1999 Slava Pestov * * You may use and modify this package for any purpose. Redistribution is * permitted, in both so
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www.eeworm.com/read/115886/6116674

java batchfiletokenmarker.java

/* * BatchFileTokenMarker.java - Batch file token marker * Copyright (C) 1998, 1999 Slava Pestov * * You may use and modify this package for any purpose. Redistribution is * permitted, in both so
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www.eeworm.com/read/101082/6243752

todo

(Version 4.1 of 7/25/83) ****** Finish properly implementing SMTP: - check correct name in HELO exchange (?) ***** Add an accounting package. [acct.c] ***** When processing the queue, batch
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www.eeworm.com/read/359185/6352487

m perceptron_bvi.m

function D = Perceptron_BVI(train_features, train_targets, params, region) % Classify using the batch variable increment Perceptron algorithm % Inputs: % features - Train features % targets
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www.eeworm.com/read/359185/6352564

m backpropagation_cgd.m

function [D, Wh, Wo] = Backpropagation_CGD(train_features, train_targets, params, region) % Classify using a backpropagation network with a batch learning algorithm and conjugate gradient descent
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www.eeworm.com/read/359185/6352580

m backpropagation_recurrent.m

function [D, Wh, Wo] = Backpropagation_Recurrent(train_features, train_targets, params, region) % Classify using a backpropagation recurrent network with a batch learning algorithm % Inputs: % f
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www.eeworm.com/read/493206/6398465

m perceptron_bvi.m

function D = Perceptron_BVI(train_features, train_targets, params, region) % Classify using the batch variable increment Perceptron algorithm % Inputs: % features - Train features % targets
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www.eeworm.com/read/493206/6398574

m backpropagation_cgd.m

function [D, Wh, Wo] = Backpropagation_CGD(train_features, train_targets, params, region) % Classify using a backpropagation network with a batch learning algorithm and conjugate gradient descent
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