add bn for inceptionv3

cnn_e2e/inception_model.py

@@ -3,20 +3,20 @@ from __future__ import division
 from __future__ import print_function
 
 import oneflow as flow
-from model_util import conv2d_layer
+from model_util import conv2d_layer_with_bn
 
 
 def InceptionA(in_blob, index):
     with flow.deprecated.variable_scope("mixed_{}".format(index)):
         with flow.deprecated.variable_scope("branch1x1"):
-            branch1x1 = conv2d_layer(
+            branch1x1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=64, kernel_size=1, strides=1, padding="SAME"
             )
         with flow.deprecated.variable_scope("branch5x5"):
-            branch5x5_1 = conv2d_layer(
+            branch5x5_1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=48, kernel_size=1, strides=1, padding="SAME"
             )
-            branch5x5_2 = conv2d_layer(
+            branch5x5_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch5x5_1,
                 filters=64,
@@ -25,10 +25,10 @@ def InceptionA(in_blob, index):
                 padding="SAME",
             )
         with flow.deprecated.variable_scope("branch3x3dbl"):
-            branch3x3dbl_1 = conv2d_layer(
+            branch3x3dbl_1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=64, kernel_size=1, strides=1, padding="SAME"
             )
-            branch3x3dbl_2 = conv2d_layer(
+            branch3x3dbl_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch3x3dbl_1,
                 filters=96,
@@ -36,7 +36,7 @@ def InceptionA(in_blob, index):
                 strides=1,
                 padding="SAME",
             )
-            branch3x3dbl_3 = conv2d_layer(
+            branch3x3dbl_3 = conv2d_layer_with_bn(
                 "conv2",
                 branch3x3dbl_2,
                 filters=96,
@@ -53,7 +53,7 @@ def InceptionA(in_blob, index):
                 data_format="NCHW",
                 name="pool",
             )
-            branch_pool_2 = conv2d_layer(
+            branch_pool_2 = conv2d_layer_with_bn(
                 "conv",
                 branch_pool_1,
                 filters=32 if index == 0 else 64,
@@ -76,14 +76,14 @@ def InceptionA(in_blob, index):
 def InceptionB(in_blob, index):
     with flow.deprecated.variable_scope("mixed_{}".format(index)):
         with flow.deprecated.variable_scope("branch3x3"):
-            branch3x3 = conv2d_layer(
+            branch3x3 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=384, kernel_size=3, strides=2, padding="VALID"
             )
         with flow.deprecated.variable_scope("branch3x3dbl"):
-            branch3x3dbl_1 = conv2d_layer(
+            branch3x3dbl_1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=64, kernel_size=1, strides=1, padding="SAME"
             )
-            branch3x3dbl_2 = conv2d_layer(
+            branch3x3dbl_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch3x3dbl_1,
                 filters=96,
@@ -91,7 +91,7 @@ def InceptionB(in_blob, index):
                 strides=1,
                 padding="SAME",
             )
-            branch3x3dbl_3 = conv2d_layer(
+            branch3x3dbl_3 = conv2d_layer_with_bn(
                 "conv2",
                 branch3x3dbl_2,
                 filters=96,
@@ -121,11 +121,11 @@ def InceptionB(in_blob, index):
 def InceptionC(in_blob, index, filters):
     with flow.deprecated.variable_scope("mixed_{}".format(index)):
         with flow.deprecated.variable_scope("branch1x1"):
-            branch1x1 = conv2d_layer(
+            branch1x1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=192, kernel_size=1, strides=1, padding="SAME"
             )
         with flow.deprecated.variable_scope("branch7x7"):
-            branch7x7_1 = conv2d_layer(
+            branch7x7_1 = conv2d_layer_with_bn(
                 "conv0",
                 in_blob,
                 filters=filters,
@@ -133,7 +133,7 @@ def InceptionC(in_blob, index, filters):
                 strides=1,
                 padding="SAME",
             )
-            branch7x7_2 = conv2d_layer(
+            branch7x7_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch7x7_1,
                 filters=filters,
@@ -141,7 +141,7 @@ def InceptionC(in_blob, index, filters):
                 strides=1,
                 padding="SAME",
             )
-            branch7x7_3 = conv2d_layer(
+            branch7x7_3 = conv2d_layer_with_bn(
                 "conv2",
                 branch7x7_2,
                 filters=192,
@@ -150,7 +150,7 @@ def InceptionC(in_blob, index, filters):
                 padding="SAME",
             )
         with flow.deprecated.variable_scope("branch7x7dbl"):
-            branch7x7dbl_1 = conv2d_layer(
+            branch7x7dbl_1 = conv2d_layer_with_bn(
                 "conv0",
                 in_blob,
                 filters=filters,
@@ -158,7 +158,7 @@ def InceptionC(in_blob, index, filters):
                 strides=1,
                 padding="SAME",
             )
-            branch7x7dbl_2 = conv2d_layer(
+            branch7x7dbl_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch7x7dbl_1,
                 filters=filters,
@@ -166,7 +166,7 @@ def InceptionC(in_blob, index, filters):
                 strides=1,
                 padding="SAME",
             )
-            branch7x7dbl_3 = conv2d_layer(
+            branch7x7dbl_3 = conv2d_layer_with_bn(
                 "conv2",
                 branch7x7dbl_2,
                 filters=filters,
@@ -174,7 +174,7 @@ def InceptionC(in_blob, index, filters):
                 strides=1,
                 padding="SAME",
             )
-            branch7x7dbl_4 = conv2d_layer(
+            branch7x7dbl_4 = conv2d_layer_with_bn(
                 "conv3",
                 branch7x7dbl_3,
                 filters=filters,
@@ -182,7 +182,7 @@ def InceptionC(in_blob, index, filters):
                 strides=1,
                 padding="SAME",
             )
-            branch7x7dbl_5 = conv2d_layer(
+            branch7x7dbl_5 = conv2d_layer_with_bn(
                 "conv4",
                 branch7x7dbl_4,
                 filters=192,
@@ -199,7 +199,7 @@ def InceptionC(in_blob, index, filters):
                 data_format="NCHW",
                 name="pool",
             )
-            branch_pool_2 = conv2d_layer(
+            branch_pool_2 = conv2d_layer_with_bn(
                 "conv",
                 branch_pool_1,
                 filters=192,
@@ -221,10 +221,10 @@ def InceptionC(in_blob, index, filters):
 def InceptionD(in_blob, index):
     with flow.deprecated.variable_scope("mixed_{}".format(index)):
         with flow.deprecated.variable_scope("branch3x3"):
-            branch3x3_1 = conv2d_layer(
+            branch3x3_1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=192, kernel_size=1, strides=1, padding="SAME"
             )
-            branch3x3_2 = conv2d_layer(
+            branch3x3_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch3x3_1,
                 filters=320,
@@ -233,10 +233,10 @@ def InceptionD(in_blob, index):
                 padding="VALID",
             )
         with flow.deprecated.variable_scope("branch7x7x3"):
-            branch7x7x3_1 = conv2d_layer(
+            branch7x7x3_1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=192, kernel_size=1, strides=1, padding="SAME"
             )
-            branch7x7x3_2 = conv2d_layer(
+            branch7x7x3_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch7x7x3_1,
                 filters=192,
@@ -244,7 +244,7 @@ def InceptionD(in_blob, index):
                 strides=1,
                 padding="SAME",
             )
-            branch7x7x3_3 = conv2d_layer(
+            branch7x7x3_3 = conv2d_layer_with_bn(
                 "conv2",
                 branch7x7x3_2,
                 filters=192,
@@ -252,7 +252,7 @@ def InceptionD(in_blob, index):
                 strides=1,
                 padding="SAME",
             )
-            branch7x7x3_4 = conv2d_layer(
+            branch7x7x3_4 = conv2d_layer_with_bn(
                 "conv3",
                 branch7x7x3_3,
                 filters=192,
@@ -283,14 +283,14 @@ def InceptionD(in_blob, index):
 def InceptionE(in_blob, index):
     with flow.deprecated.variable_scope("mixed_{}".format(index)):
         with flow.deprecated.variable_scope("branch1x1"):
-            branch1x1 = conv2d_layer(
+            branch1x1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=320, kernel_size=1, strides=1, padding="SAME"
             )
         with flow.deprecated.variable_scope("branch3x3"):
-            branch3x3_1 = conv2d_layer(
+            branch3x3_1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=384, kernel_size=1, strides=1, padding="SAME"
             )
-            branch3x3_2 = conv2d_layer(
+            branch3x3_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch3x3_1,
                 filters=384,
@@ -298,7 +298,7 @@ def InceptionE(in_blob, index):
                 strides=1,
                 padding="SAME",
             )
-            branch3x3_3 = conv2d_layer(
+            branch3x3_3 = conv2d_layer_with_bn(
                 "conv2",
                 branch3x3_1,
                 filters=384,
@@ -313,10 +313,10 @@ def InceptionE(in_blob, index):
                 values=inceptionE_1_bn, axis=1, name="concat"
             )
         with flow.deprecated.variable_scope("branch3x3dbl"):
-            branch3x3dbl_1 = conv2d_layer(
+            branch3x3dbl_1 = conv2d_layer_with_bn(
                 "conv0", in_blob, filters=448, kernel_size=1, strides=1, padding="SAME"
             )
-            branch3x3dbl_2 = conv2d_layer(
+            branch3x3dbl_2 = conv2d_layer_with_bn(
                 "conv1",
                 branch3x3dbl_1,
                 filters=384,
@@ -324,7 +324,7 @@ def InceptionE(in_blob, index):
                 strides=1,
                 padding="SAME",
             )
-            branch3x3dbl_3 = conv2d_layer(
+            branch3x3dbl_3 = conv2d_layer_with_bn(
                 "conv2",
                 branch3x3dbl_2,
                 filters=384,
@@ -332,7 +332,7 @@ def InceptionE(in_blob, index):
                 strides=1,
                 padding="SAME",
             )
-            branch3x3dbl_4 = conv2d_layer(
+            branch3x3dbl_4 = conv2d_layer_with_bn(
                 "conv3",
                 branch3x3dbl_2,
                 filters=384,
@@ -355,7 +355,7 @@ def InceptionE(in_blob, index):
                 data_format="NCHW",
                 name="pool",
             )
-            branch_pool_2 = conv2d_layer(
+            branch_pool_2 = conv2d_layer_with_bn(
                 "conv",
                 branch_pool_1,
                 filters=192,
@@ -382,22 +382,23 @@ def inceptionv3(images, trainable=True, need_transpose=False):
         images = flow.transpose(images, name="transpose", perm=[0, 3, 1, 2])
 
     with flow.deprecated.variable_scope("InceptionV3"):
-        conv0 = conv2d_layer(
+        # conv0: 299 x 299 x 3
+        conv0 = conv2d_layer_with_bn(
             "conv0", images, filters=32, kernel_size=3, strides=2, padding="VALID"
         )
-        conv1 = conv2d_layer(
+        conv1 = conv2d_layer_with_bn(
             "conv1", conv0, filters=32, kernel_size=3, strides=1, padding="VALID"
         )
-        conv2 = conv2d_layer(
+        conv2 = conv2d_layer_with_bn(
             "conv2", conv1, filters=64, kernel_size=3, strides=1, padding="SAME"
         )
         pool1 = flow.nn.max_pool2d(
             conv2, ksize=3, strides=2, padding="VALID", data_format="NCHW", name="pool1"
         )
-        conv3 = conv2d_layer(
+        conv3 = conv2d_layer_with_bn(
             "conv3", pool1, filters=80, kernel_size=1, strides=1, padding="VALID"
         )
-        conv4 = conv2d_layer(
+        conv4 = conv2d_layer_with_bn(
             "conv4", conv3, filters=192, kernel_size=3, strides=1, padding="VALID"
         )
         pool2 = flow.nn.max_pool2d(
@@ -408,7 +409,6 @@ def inceptionv3(images, trainable=True, need_transpose=False):
         mixed_0 = InceptionA(pool2, 0)
         mixed_1 = InceptionA(mixed_0, 1)
         mixed_2 = InceptionA(mixed_1, 2)
-
         # mixed_3
         mixed_3 = InceptionB(mixed_2, 3)
 
@@ -425,7 +425,6 @@ def inceptionv3(images, trainable=True, need_transpose=False):
         mixed_9 = InceptionE(mixed_8, 9)
         mixed_10 = InceptionE(mixed_9, 10)
 
-        # pool3
         pool3 = flow.nn.avg_pool2d(
             mixed_10, ksize=8, strides=1, padding="VALID", data_format="NCHW", name="pool3"
         )
@@ -433,10 +432,10 @@ def inceptionv3(images, trainable=True, need_transpose=False):
         # TODO: Need to transpose weight when converting model from TF to OF if
         # you want to use layers.dense interface.
         fc1 = flow.layers.dense(
-            flow.reshape(pool3, [pool3.shape[0], -1]),
-            1001,
+            inputs=flow.reshape(pool3, [pool3.shape[0], -1]),
+            units=1001,
             activation=None,
-            use_bias=False,
+            use_bias=True,
             kernel_initializer=flow.truncated_normal(0.816496580927726),
             bias_initializer=flow.constant_initializer(),
             trainable=trainable,