Evan Mays 285621aeda Cherry backprop for conv2d (#281) ... * quick math: 0 + x = x. * gradient w.r.t. x using cherry for conv * gradient w.r.t. w for conv on cherry but doing vector dot products * small optimization * [cherry] optimize conv backpass for large channel count * get rid of numpy einsum		2021-10-30 16:12:19 -07:00
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efficientnet	feat: add efficientnet test (#285)	2021-10-30 15:53:51 -07:00
mnist	Improved __getitem__ (#254)	2021-05-05 22:15:22 -07:00
__init__.py	All devices are equal! (#196)	2020-12-15 23:44:08 -08:00
test_efficientnet.py	feat: add efficientnet test (#285)	2021-10-30 15:53:51 -07:00
test_gc.py	Test split (#231)	2021-01-01 09:19:03 -05:00
test_mnist.py	Improved __getitem__ (#254)	2021-05-05 22:15:22 -07:00
test_net_speed.py	Test split (#231)	2021-01-01 09:19:03 -05:00
test_nn.py	Added ResNet-{18, 34, 50, 101, 152} (#271)	2021-06-21 09:37:24 -07:00
test_ops.py	Cherry backprop for conv2d (#281)	2021-10-30 16:12:19 -07:00
test_optim.py	Test split (#231)	2021-01-01 09:19:03 -05:00
test_tensor.py	Add dropout test (#265)	2021-06-19 08:49:13 -07:00
test_train.py	Added ResNet-{18, 34, 50, 101, 152} (#271)	2021-06-21 09:37:24 -07:00