(self, order)
| 14 | class TestMiniAlexNet(test_util.TestCase): |
| 15 | |
| 16 | def _MiniAlexNetNoDropout(self, order): |
| 17 | # First, AlexNet using the cnn wrapper. |
| 18 | model = model_helper.ModelHelper(name="alexnet") |
| 19 | conv1 = brew.conv( |
| 20 | model, |
| 21 | "data", |
| 22 | "conv1", |
| 23 | 3, |
| 24 | 16, |
| 25 | 11, |
| 26 | ("XavierFill", {}), |
| 27 | ("ConstantFill", {}), |
| 28 | stride=4, |
| 29 | pad=0 |
| 30 | ) |
| 31 | relu1 = brew.relu(model, conv1, "relu1") |
| 32 | norm1 = brew.lrn(model, relu1, "norm1", size=5, alpha=0.0001, beta=0.75) |
| 33 | pool1 = brew.max_pool(model, norm1, "pool1", kernel=3, stride=2) |
| 34 | conv2 = brew.group_conv( |
| 35 | model, |
| 36 | pool1, |
| 37 | "conv2", |
| 38 | 16, |
| 39 | 32, |
| 40 | 5, |
| 41 | ("XavierFill", {}), |
| 42 | ("ConstantFill", {"value": 0.1}), |
| 43 | group=2, |
| 44 | stride=1, |
| 45 | pad=2 |
| 46 | ) |
| 47 | relu2 = brew.relu(model, conv2, "relu2") |
| 48 | norm2 = brew.lrn(model, relu2, "norm2", size=5, alpha=0.0001, beta=0.75) |
| 49 | pool2 = brew.max_pool(model, norm2, "pool2", kernel=3, stride=2) |
| 50 | conv3 = brew.conv( |
| 51 | model, |
| 52 | pool2, |
| 53 | "conv3", |
| 54 | 32, |
| 55 | 64, |
| 56 | 3, |
| 57 | ("XavierFill", {'std': 0.01}), |
| 58 | ("ConstantFill", {}), |
| 59 | pad=1 |
| 60 | ) |
| 61 | relu3 = brew.relu(model, conv3, "relu3") |
| 62 | conv4 = brew.group_conv( |
| 63 | model, |
| 64 | relu3, |
| 65 | "conv4", |
| 66 | 64, |
| 67 | 64, |
| 68 | 3, |
| 69 | ("XavierFill", {}), |
| 70 | ("ConstantFill", {"value": 0.1}), |
| 71 | group=2, |
| 72 | pad=1 |
| 73 | ) |
no test coverage detected