How to train CNNs on ImageNet

I’ll go over how to get the ImageNet dataset, and train your convolutional neural net on it. I’ve added some advice and learnings specific to training CNNs with PyTorch.

Before you start

If you haven’t already, I recommend first trying to run your model on a sample image. When you’re starting out, it’sreally tempting to jump to a big dataset like ImageNet to train your next state of the art model. However, I’ve found it more effective to start small and slowly scale up your experiment. First, try an image to make sure your code works. Then, try a smaller dataset like CIFAR-10. Finally, try it out on ImageNet. Do sanity checks along the way and repeat them for each “scale up”.

Also, be aware of the differences in your model for the smaller image sizes of one dataset vs the other. For example, CIFAR-10 has only 32x32 size images which are smaller than ImageNet’s variable image sizes. The average resolution of an ImageNet image is 469x387. They are usually cropped to 256x256 or 224x224 in your image preprocessing step.

In PyTorch, we don’t define an input height or width like we would in TensorFlow, so it’s your job to make sure output channel sizes along the way are appropriate in your network for a given input size. My advice is to be wary of how dimensionality reduction occurs from shallow to deeper filters in your network, especially as you change your dataset.

Image for post

VGG-16 Network Architecture. Output channels have shrinking dimensions (h x w). What errors could we come across if we change the input size?

In general, as you increase the input resolution to a new dataset, the early receptive field should also increase in size (via increasing kernel size or adding pooling layers).

This is for two reasons:

  1. Increasing the size of the early receptive field is a form of regularisation to guard your CNN from learning ultra specific details of images that are less generalisable.
  2. When decreasing the input resolution, this will help avoid premature shrinkage of the channel size. Applying a convolution to a 256x1x1 size tensor is kind of useless.

Both of these errors fail silently. These errors result in only an 8% decrease in top 1 accuracy when an ImageNet shaped ResNet is improperly applied to CIFAR-10. To correct this error, when moving from CIFAR-10 to ImageNet, the ResNet authors add an early max-pool layer, and use a larger initial kernel size (5x5 → 7x7).

I’d really recommend reading this blog post by Andrej Karpathy for a deeper intuition of this art. I’d also recommend this post by Tim Rocktaschel on advice for short term ML projects

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Transaction Control is an active and related transformation that makes it possible for us to commit or rollback transactions during mapping execution. Commit and rollback practices are of major significance for data availability. Here, we will look after how transaction control transformation takes place in Informatica.

Data integration in Informatica

You can use Data integration in the Informatica Power center. It includes the ability to link and extract data from multiple heterogeneous data sources and process data.
For example, both the SQL Server Database and the Oracle Database can link and the data can integrate it into a third system.
The new available version of Informatica PowerCenter is 9.6.0. For PowerCenter, there are multiple editions available.
Standard edition
Advanced edition
Premium edition
Popular clients are using Informatica Power Center as data integration. IBM DataStage, Oracle OWB, Microsoft SSIS, and Ab Initio are common tools available on the market to compete against Informatica.

Transformation of Informatica Transaction Management.

There will be a scenario where committing the data to the target when they handle a high amount of data. Commit and rollback operations are of great significance as they ensure data access. Transformation of transaction management enables one to commit or rollback transactions during the mapping execution.

When a commit executes it too soon, it would be an overhead for the system. When a commit is complete too late, there are risks of data loss in the event of failure.
A transaction is the set of rows that the commit or rollback rows are bound by. Based on a varying number of input rows, you may describe a transaction. Based on a set of rows organized on a common key, such as employee ID or order entry date, you might want to identify transactions. The PowerCenter from Informatica helps you to monitor commit and rollback transactions based on a series of rows going through a transformation of Transaction Control.

Configuring the Transformation to Informatica Transaction Management

In the transaction control transformation, you can configure the following components:
Transformation Tab:
The transformation can rename and a summary adds.
Ports Tab:
You can build ports for input/output
Properties Tab:
You should describe the expression of transaction control and the degree of tracing.
Metadata Extensions Tab:
You can add Metadata details.

Expression of Informatica Transaction Power

In the Transaction Control State option on the Assets tab, you can enter the transaction control expression. To evaluate each row against the condition, the transaction control statement uses the IIF function. Using the notation that follows with an expression.

**Syntax: **

The IIF (condition, value1, value2)
EXAMPLE:
IIF(dept id=10, TC-COMMIT BEFORE, TC ROLLBACK BEFORE)
Transaction control transfers it to provide flexibility. In this transformation, five built-in variables are available to manage the operation.

**TC CONTINUE TRANSACTION **

For this line, the Integration Service does not make any transaction adjustments. This is the expression’s default meaning.

**TC COMMIT BEFORE **

The Integration Service commits the transaction, starts a new transaction, and writes the current row to the target. The existing line locates it in the latest deal.

**TC-COMMIT-AFTER **

The Integration Service writes the current row to the target, commits the transaction, and starts a new transaction. The current row includes it in the transaction committed.

**TC ROLLBACK BEFORE **

Rollback the current transaction from the Integration Service, launch a new transaction, and write the current row to the target. In the latest deal, the existing line is placed.

TC ROLLBACK AFTER

The Integration Service writes to the target the current line, rolls the transaction back, and starts a new transaction. In the rolled-back transaction, this is the existing line.

Guidelines and Evaluation for Mapping

When you build a map with a transaction control transformation, use the following rules and guidelines.
If the mapping contains an XML target, and you want to add or construct a new commit text, data must receive it from the same transaction control point by the input classes.
For such targets, transaction control transformations linked to any target other than relational, XML, or dynamic MQSeries targets are unsuccessful.
You must relate each target instance to a transformation of Transaction Power.
You can relate several goals to a single transformation of Transaction Power.
Just one active Transaction Control transition may link it to a goal.
In a pipeline branch that begins with a Sequence Generator transformation, you can not put a Transaction Control transformation.
A rolled-back transaction could result in unsynchronized target data if you use a dynamic Lookup transformation and a Transaction Control transformation within the same mapping.
Transformation of a Transaction Control can be successful for one goal and inefficient for another. If each target is related to an efficient transformation of Transaction Control, the mapping is true.
A successful transformation of Transaction Control can be related to either all the targets or none of the targets in the mapping.
To identify requirements to commit and rollback transactions from transactional targets, use the Transaction Control transition. Relational, XML, and dynamic MQSeries targets provide transactional targets.

Informatica Transaction control

The transaction control transition expression includes values that reflect acts that are done by the Integration Service based on a condition’s return value. On a row-by-row basis, the Integration Provider analyses the case. The return value defines when the Integration Provider commits, rolls back, or does not adjust a row for any transaction. When a commit or rollback is provided by the Integration Provider depending on the expression’s return value, a new transaction begins.
You configure it for the user-defined commit when you configure a session. The Integration Service commits and rolls back transactions during a user-defined commit session based on a row or group of rows going through a transition of Transaction Power. For each row that enters the transition, the Integration Service evaluates the transaction control expression. The transaction control expression’s return value determines the commit or rollback point.
PowerCenter designer
Originally, the mappings create it using PowerCenter Designer. If you use PowerCenter Express (PCX), it is not possible to import all mappings because PCX only contains the Informatica Developer tool and not the PowerCenter Designer tool.
The artifacts are based on the code page ‘UTF-8.’ XML can need to edit it if you have modified the file tab.
You will describe the transaction at the following levels in the Informatica power center.
Mapping level:
To identify the transactions, use a transaction control transformation.
Session level:
Session properties
In the Session Properties tab, you can define the “Commit type” option. The multiple ‘Commit Type’ options are Goal, Source and User Defined. The “Commit Type” will only be “User Defined” if you have used the transaction control transformation in the mapping.
The integration service calculates the expression for each row in the transaction control transition while you are running a session. When the expression evaluates it as commit, it commits all rows in the contract to the destination (s). Also, when the integration service calculates the expression as a rollback, all the rows in the transaction roll it back from the target (s).
If you have a flat file as the target, so each time the transaction is committed, the integration service generates an output file. You can label the target flat files dynamically. Look at the example of dynamically generating flat files: Dynamic creation of flat files.
Conclusion
There will be a condition when committing the data to the target when handling a high amount of data. When a commit executes it too soon, it would be an overhead for the system. When a commit completes it too late, there are risks of data loss in the event of failure. Transaction control transfer provides it to provide flexibility. Hence, learn further in this regard through online informatica training

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