How to get the current epoch time

本文详细介绍了在不同编程语言中获取当前时间戳的方法,并提供了将时间戳转换为可读日期和从可读日期转换为时间戳的示例。

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 How to get the current epoch time in ...

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Perltime
PHPtime()
RubyTime.now (or Time.new ). To display the epoch: Time.now.to_i
Pythonimport time first, then time.time()
Javalong epoch = System.currentTimeMillis()/1000;
Microsoft .NET C#epoch = (DateTime.Now.ToUniversalTime().Ticks - 621355968000000000) / 10000000;
VBScript/ASPDateDiff("s", "01/01/1970 00:00:00", Now())
Erlangcalendar:datetime_to_gregorian_seconds(calendar:now_to_universal_time( now()))-719528*24*3600.
MySQLSELECT unix_timestamp(now()) More 
information
PostgreSQLSELECT extract(epoch FROM now());
Oracle PL/SQLSELECT (SYSDATE - TO_DATE('01-01-1970 00:00:00', 'DD-MM-YYYY HH24:MI:SS')) *
24 * 60 * 60 FROM DUAL
SQL ServerSELECT DATEDIFF(s, '1970-01-01 00:00:00', GETUTCDATE())
JavaScriptMath.round(new Date().getTime()/1000.0) getTime() returns time in milliseconds.
Unix/Linuxdate +%s
Other OS's Command line: perl -e "print time" (If Perl is installed on your system)

 Convert from human readable date to epoch

PerlUse these Perl Epoch routines
PHPmktime(hour , minute , second , month , day , year ) More 
information
RubyTime.local(year , month , day , hour , minute , second , usec ) (or Time.gm for GMT/UTC input). To display add .to_i
Pythonimport time first, then int(time.mktime(time.strptime('2000-01-01 12:34:00', '%Y-%m-%d %H:%M:%S'))) - time.timezone
Javalong epoch = new java.text.SimpleDateFormat ("dd/MM/yyyy HH:mm:ss").parse("01/01/1970 01:00:00");
VBScript/ASPDateDiff("s", "01/01/1970 00:00:00", time field ) More 
information
MySQLSELECT unix_timestamp(time ) Time format: YYYY-MM-DD HH:MM:SS or YYMMDD or YYYYMMDD
More on using Epoch timestamps with MySQL
PostgreSQLSELECT extract(epoch FROM date('2000-01-01 12:34'));
With timestamp: SELECT EXTRACT(EPOCH FROM TIMESTAMP WITH TIME ZONE '2001-02-16 20:38:40-08');
With interval: SELECT EXTRACT(EPOCH FROM INTERVAL '5 days 3 hours');
SQL Server SELECT DATEDIFF(s, '1970-01-01 00:00:00', time field )
JavaScriptuse the JavaScript Date object
Unix/Linuxdate +%s -d"Jan 1, 1980 00:00:01" Replace '-d' with '-ud' to input in GMT/UTC time.

 Convert from epoch to human readable date

PerlUse these Perl Epoch routines
PHPdate(output format , epoch ); Output format example: 'r' = RFC 2822 date More 
information
RubyTime.at(epoch )
Pythonimport time first, then time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.localtime(epoch )) Replace time.localtime with time.gmtime for GMT time. More 
information
JavaString date = new java.text.SimpleDateFormat("dd/MM/yyyy HH:mm:ss").format(new java.util.Date (epoch *1000));
VBScript/ASPDateAdd("s", epoch , "01/01/1970 00:00:00") More 
information
PostgreSQLPostgreSQL version 8.1 and higher: SELECT to_timestamp(epoch ); More
 information Older versions: SELECT TIMESTAMP WITH TIME ZONE 'epoch' + epoch * INTERVAL '1 second';
MySQLfrom_unixtime(epoch , optional output format ) The default output format is YYY-MM-DD HH:MM:SS more ...
SQL Server DATEADD(s, epoch , '1970-01-01 00:00:00')
Microsoft Excel =(A1 / 86400) + 25569 Format the result cell for date/time, the result will be in GMT time (A1 is the cell with the epoch number). For other timezones: =((A1 +/- timezone adjustment) / 86400) + 25569.
JavaScriptuse the JavaScript Date object
Unix/Linuxdate -d @1190000000 Replace 1190000000 with your epoch, needs recent version of 'date'. Replace '-d' with '-ud' for GMT/UTC time.
Other OS'sCommand line: perl -e "print scalar(localtime(epoch ))" (If Perl is installed) Replace 'localtime' with 'gmtime' for GMT/UTC time.
train with base lr in the first 100 epochs # and half the lr in the last 100 epochs To train with a base learning rate for the first 100 epochs and half the learning rate for the last 100 epochs, you can use a learning rate scheduler in PyTorch. Here's an example of how you can modify the training loop in your code: import torch import torch.nn as nn import torch.optim as optim from torch.optim.lr_scheduler import MultiStepLR # Define your model, criterion, and optimizer model = YourModel() criterion = nn.CrossEntropyLoss() optimizer = optim.SGD(model.parameters(), lr=0.01) # Define the number of epochs and the milestone epochs num_epochs = 200 milestones = [100] # Create a learning rate scheduler scheduler = MultiStepLR(optimizer, milestones=milestones, gamma=0.5) # Train the model for epoch in range(num_epochs): # Train with base lr for the first 100 epochs, and half the lr for the last 100 epochs if epoch >= milestones[0]: scheduler.step() for inputs, labels in train_loader: # Forward pass outputs = model(inputs) loss = criterion(outputs, labels) # Backward pass and optimization optimizer.zero_grad() loss.backward() optimizer.step() # Perform validation or testing after each epoch with torch.no_grad(): # Validation or testing code # Print training information print(f"Epoch [{epoch+1}/{num_epochs}], Loss: {loss.item()}, LR: {scheduler.get_last_lr()[0]}") # Save the model or perform other operations after training In this code snippet, we create a MultiStepLR scheduler and specify the milestones as [100] and gamma as 0.5. The learning rate is halved at the specified milestone epochs. Inside the training loop, we check if the current epoch is greater than or equal to the milestone epoch, and if so, we call scheduler.step() to update the learning rate. Remember to adjust the num_epochs and other hyperparameters according to your specific requirements. 翻译成中文
07-16
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