(def network-100-10-7-1
  [(layers/input 28 28 1 :id :data)
   (layers/linear 94)
   (layers/prelu)
   (layers/batch-normalization)
   (layers/relu)
   (layers/batch-normalization)
   (layers/prelu)
   (layers/linear 94)
   (layers/prelu)
   (layers/batch-normalization)
   (layers/linear 10)
   (layers/softmax :id :labels)])

;; Training network:
;; |                 type |         input |      output | :bias | :means | :neg-scale | :scale | :variances | :weights |
;; |----------------------+---------------+-------------+-------+--------+------------+--------+------------+----------|
;; |              :linear | 1x28x28 - 784 | 1x1x94 - 94 |  [94] |        |            |        |            | [94 784] |
;; |               :prelu |   1x1x94 - 94 | 1x1x94 - 94 |       |        |       [94] |        |            |          |
;; | :batch-normalization |   1x1x94 - 94 | 1x1x94 - 94 |  [94] |   [94] |            |   [94] |       [94] |          |
;; |                :relu |   1x1x94 - 94 | 1x1x94 - 94 |       |        |            |        |            |          |
;; | :batch-normalization |   1x1x94 - 94 | 1x1x94 - 94 |  [94] |   [94] |            |   [94] |       [94] |          |
;; |               :prelu |   1x1x94 - 94 | 1x1x94 - 94 |       |        |       [94] |        |            |          |
;; |              :linear |   1x1x94 - 94 | 1x1x94 - 94 |  [94] |        |            |        |            |  [94 94] |
;; |               :prelu |   1x1x94 - 94 | 1x1x94 - 94 |       |        |       [94] |        |            |          |
;; | :batch-normalization |   1x1x94 - 94 | 1x1x94 - 94 |  [94] |   [94] |            |   [94] |       [94] |          |
;; |              :linear |   1x1x94 - 94 | 1x1x10 - 10 |  [10] |        |            |        |            |  [10 94] |
;; |             :softmax |   1x1x10 - 10 | 1x1x10 - 10 |       |        |            |        |            |          |
;; Parameter count: 85080
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9509
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9636
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9699
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9714
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9731
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9738
;; Saving network to experiment.nippy
;; Classification accuracy: 0.974
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9747
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9753
;; Saving network to experiment.nippy
;; Classification accuracy: 0.9758
;; Classification accuracy: 0.9756
;; Classification accuracy: 0.9755
;; Classification accuracy: 0.9754
;; Classification accuracy: 0.9753
;; Classification accuracy: 0.9754
;; Classification accuracy: 0.9752
;; Classification accuracy: 0.975
;; Classification accuracy: 0.9749
;; Classification accuracy: 0.9753
;; Classification accuracy: 0.9752