Fix img_layers.protostr,img_trans_layers.protostr. Add test_BatchNorm3D.protostr

python/paddle/trainer_config_helpers/tests/configs/protostr/img_layers.protostr

@@ -62,6 +62,7 @@ layers {
   moving_average_fraction: 0.9
   height: 227
   width: 227
+  depth: 1
 }
 layers {
   name: "__crmnorm_0__"

python/paddle/trainer_config_helpers/tests/configs/protostr/img_trans_layers.protostr

@@ -62,6 +62,7 @@ layers {
   moving_average_fraction: 0.9
   height: 256
   width: 256
+  depth: 1
 }
 layers {
   name: "__crmnorm_0__"

python/paddle/trainer_config_helpers/tests/configs/protostr/test_BatchNorm3D.protostr

@@ -0,0 +1,92 @@
+type: "nn"
+layers {
+  name: "data3D"
+  type: "data"
+  size: 360
+  active_type: ""
+  height: 6
+  width: 20
+  depth: 3
+}
+layers {
+  name: "__batch_norm_0__"
+  type: "batch_norm"
+  size: 360
+  active_type: "relu"
+  inputs {
+    input_layer_name: "data3D"
+    input_parameter_name: "___batch_norm_0__.w0"
+    image_conf {
+      channels: 1
+      img_size: 20
+      img_size_y: 6
+      img_size_z: 3
+    }
+  }
+  inputs {
+    input_layer_name: "data3D"
+    input_parameter_name: "___batch_norm_0__.w1"
+  }
+  inputs {
+    input_layer_name: "data3D"
+    input_parameter_name: "___batch_norm_0__.w2"
+  }
+  bias_parameter_name: "___batch_norm_0__.wbias"
+  moving_average_fraction: 0.9
+  height: 6
+  width: 20
+  depth: 3
+}
+parameters {
+  name: "___batch_norm_0__.w0"
+  size: 1
+  initial_mean: 1.0
+  initial_std: 0.0
+  initial_strategy: 0
+  initial_smart: false
+}
+parameters {
+  name: "___batch_norm_0__.w1"
+  size: 1
+  initial_mean: 0.0
+  initial_std: 0.0
+  dims: 1
+  dims: 1
+  initial_strategy: 0
+  initial_smart: false
+  is_static: true
+  is_shared: true
+}
+parameters {
+  name: "___batch_norm_0__.w2"
+  size: 1
+  initial_mean: 0.0
+  initial_std: 0.0
+  dims: 1
+  dims: 1
+  initial_strategy: 0
+  initial_smart: false
+  is_static: true
+  is_shared: true
+}
+parameters {
+  name: "___batch_norm_0__.wbias"
+  size: 1
+  initial_mean: 0.0
+  initial_std: 0.0
+  dims: 1
+  dims: 1
+  initial_strategy: 0
+  initial_smart: false
+}
+input_layer_names: "data3D"
+output_layer_names: "__batch_norm_0__"
+sub_models {
+  name: "root"
+  layer_names: "data3D"
+  layer_names: "__batch_norm_0__"
+  input_layer_names: "data3D"
+  output_layer_names: "__batch_norm_0__"
+  is_recurrent_layer_group: false
+}
+

python/paddle/trainer_config_helpers/tests/configs/test_BatchNorm3D.py

@@ -2,16 +2,10 @@ from paddle.trainer_config_helpers import *
 
 settings(batch_size=1000, learning_rate=1e-4)
 
-data = data_layer(name='data', size=180, width=30, height=6)
+#data = data_layer(name='data', size=180, width=30, height=6)
-#
+#batchNorm = batch_norm_layer(data, num_channels=1)
-batchNorm = batch_norm_layer(data, num_channels=1)
+#outputs(batchNorm)
-#
-outputs(batchNorm)
 
-# #
+data3D = data_layer(name='data3D', size=120 * 3, width=20, height=6, depth=3)
-data3D = data_layer(name='data3D22', size=120 * 3, width=20, height=6, depth=3)
-#
-print(data3D)
 batchNorm3D = batch_norm_layer(data3D, num_channels=1, img3D=True)
-#
 outputs(batchNorm3D)