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Added conditional layer for extracting flattened feature vector before classification layer to the Phinet and Xinet networks. #86

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Description

Phinet and Xinet networks are modified to expose a conditional layer, that will return the flattened feature vector before the classification stage for when the classification head is not needed. Furthermore a new variable "features_dim" is added in the class to facilitate access to the size of the feature vector at runtime.

Also implemented the fixes from issue #85

Type of change

Please delete options that are not relevant.

  • New feature (non-breaking change which adds functionality)
  • This change requires a documentation update

How Has This Been Tested?

  • Ran both Phinet and Xinet with solo learn
  • Run image classification test on CIFAR10 both for Xinet and Phinet.

Checklist:

  • My code follows the style guidelines of this project
  • I have performed a self-review of my code
  • My changes generate no new warnings

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