xref: /aosp_15_r20/external/pytorch/benchmarks/dynamo/microbenchmarks/model.py (revision da0073e96a02ea20f0ac840b70461e3646d07c45) 
1# resnet50 layer shape
2resnet50_layers = (
3    # IN_H, IN_W, IN_C, KERNEL_H, KERNEL_W, KERNEL_N, stride, padding
4    (224, 224, 3, 7, 7, 64, (2, 2), (0, 0)),
5    # conv2_x
6    (56, 56, 64, 1, 1, 64, (1, 1), (0, 0)),
7    (56, 56, 64, 3, 3, 64, (1, 1), (0, 0)),
8    (56, 56, 64, 1, 1, 256, (1, 1), (0, 0)),
9    # conv3_x
10    (56, 56, 256, 1, 1, 128, (2, 2), (0, 0)),
11    (28, 28, 128, 3, 3, 128, (1, 1), (0, 0)),
12    (28, 28, 128, 1, 1, 512, (1, 1), (0, 0)),
13    # conv4_x
14    (28, 28, 512, 1, 1, 256, (2, 2), (0, 0)),
15    (14, 14, 256, 3, 3, 256, (1, 1), (0, 0)),
16    (14, 14, 256, 1, 1, 1024, (1, 1), (0, 0)),
17    # conv5_x
18    (14, 14, 1024, 1, 1, 512, (2, 2), (0, 0)),
19    (7, 7, 512, 3, 3, 512, (1, 1), (0, 0)),
20    (7, 7, 512, 1, 1, 2048, (1, 1), (0, 0)),
21)
22
23alexnet_layers = (
24    # IN_H, IN_W, IN_C, KERNEL_H, KERNEL_W, KERNEL_N, stride, padding
25    (224, 224, 3, 11, 11, 64, (4, 4), (2, 2)),
26)
27