Why InceptionResnetV2 has 1536 output feature maps

[Podidiving]

pretrained-models.pytorch/pretrainedmodels/models/inceptionresnetv2.py

Line 300 in 8aae3d8

self.conv2d_7b = BasicConv2d(2080, 1536, kernel_size=1, stride=1)

In this realization model has 1536 feature maps in the end.

However, according to https://arxiv.org/pdf/1602.07261.pdf it should be 2048 (fig 19).

Please, can you explain, why the realization is slightly different from the one, provided in the paper?

[Rupesh-rkgit]

I tried to understand the model and came to the conclusion that the whole model has followed the "schema of the Inception-v4 network", not InceptionResnetV2. Just see fig 9. It has also followed Inception A, Inception B, and Inception C block structure as we can see in fig 4,5,6.