[enco] Add residual_bn test (#2822)
author윤지영/On-Device Lab(SR)/Engineer/삼성전자 <jy910.yun@samsung.com>
Fri, 18 Jan 2019 05:55:42 +0000 (14:55 +0900)
committer박종현/On-Device Lab(SR)/Staff Engineer/삼성전자 <jh1302.park@samsung.com>
Fri, 18 Jan 2019 05:55:42 +0000 (14:55 +0900)
This commit adds the residual_bn test
by copying the original residual block from resnet18.prototxt.

Signed-off-by: Jiyoung Yun <jy910.yun@samsung.com>
contrib/enco/test/caffe/residual_bn/INFERENCE [new file with mode: 0644]
contrib/enco/test/caffe/residual_bn/test.prototxt [new file with mode: 0644]

diff --git a/contrib/enco/test/caffe/residual_bn/INFERENCE b/contrib/enco/test/caffe/residual_bn/INFERENCE
new file mode 100644 (file)
index 0000000..e69de29
diff --git a/contrib/enco/test/caffe/residual_bn/test.prototxt b/contrib/enco/test/caffe/residual_bn/test.prototxt
new file mode 100644 (file)
index 0000000..eaa321e
--- /dev/null
@@ -0,0 +1,110 @@
+name: "residual_bn"
+layer {
+  name: "input"
+  type: "Input"
+  top: "data"
+  input_param {
+    shape {
+      dim: 1
+      dim: 3
+      dim: 31
+      dim: 31
+    }
+  }
+}
+layer {
+  name: "MaxPool2dBackward4"
+  type: "Pooling"
+  bottom: "data"
+  top: "MaxPool2dBackward4"
+  pooling_param {
+    pool: MAX
+    kernel_size: 3
+    stride: 2
+    pad: 1
+  }
+}
+layer {
+  name: "ConvNdBackward5"
+  type: "Convolution"
+  bottom: "MaxPool2dBackward4"
+  top: "ConvNdBackward5"
+  convolution_param {
+    num_output: 5
+    pad_h: 1
+    pad_w: 1
+    kernel_h: 3
+    kernel_w: 3
+    stride: 1
+    bias_term: false
+  }
+}
+layer {
+  name: "BatchNormBackward6_bn"
+  type: "BatchNorm"
+  bottom: "ConvNdBackward5"
+  top: "BatchNormBackward6"
+  batch_norm_param {
+    use_global_stats: true
+    eps: 1e-05
+  }
+}
+layer {
+  name: "BatchNormBackward6_scale"
+  type: "Scale"
+  bottom: "BatchNormBackward6"
+  top: "BatchNormBackward6"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "ThresholdBackward7"
+  type: "ReLU"
+  bottom: "BatchNormBackward6"
+  top: "BatchNormBackward6"
+}
+layer {
+  name: "ConvNdBackward8"
+  type: "Convolution"
+  bottom: "BatchNormBackward6"
+  top: "ConvNdBackward8"
+  convolution_param {
+    num_output: 3
+    pad_h: 1
+    pad_w: 1
+    kernel_h: 3
+    kernel_w: 3
+    stride: 1
+    bias_term: false
+  }
+}
+layer {
+  name: "BatchNormBackward9_bn"
+  type: "BatchNorm"
+  bottom: "ConvNdBackward8"
+  top: "BatchNormBackward9"
+  batch_norm_param {
+    use_global_stats: true
+    eps: 1e-05
+  }
+}
+layer {
+  name: "BatchNormBackward9_scale"
+  type: "Scale"
+  bottom: "BatchNormBackward9"
+  top: "BatchNormBackward9"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "AddBackward11"
+  type: "Eltwise"
+  bottom: "BatchNormBackward9"
+  bottom: "MaxPool2dBackward4"
+  top: "AddBackward11"
+  eltwise_param {
+    operation: SUM
+  }
+}