add cspnet

ppcls/modeling/architectures/__init__.py

@@ -46,4 +46,4 @@ from .resnet_acnet import ResNet18_ACNet, ResNet34_ACNet, ResNet50_ACNet, ResNet
 # distillation model
 from .distillation_models import ResNet50_vd_distill_MobileNetV3_large_x1_0, ResNeXt101_32x16d_wsl_distill_ResNet50_vd
 
-from .csp_resnet import CSPResNet50
+from .csp_resnet import *

ppcls/modeling/architectures/csp_resnet.py

@@ -18,11 +18,10 @@ from __future__ import print_function
 
 import math
 
-import paddle
 import paddle.fluid as fluid
 from paddle.fluid.param_attr import ParamAttr
 
-__all__ = ["CSPResNet50", ]
+__all__ = ["CSPResNet50", "CSPResNet101"]
 
 
 class CSPResNet():
@@ -31,19 +30,16 @@ class CSPResNet():
 
     def net(self, input, class_dim=1000, data_format="NCHW"):
         layers = self.layers
-        supported_layers = [18, 34, 50, 101, 152]
+        supported_layers = [50, 101]
         assert layers in supported_layers, \
             "supported layers are {} but input layer is {}".format(
                 supported_layers, layers)
 
-        if layers == 18:
-            depth = [2, 2, 2, 2]
-        elif layers == 34 or layers == 50:
+        if layers == 50:
             depth = [3, 3, 5, 2]
         elif layers == 101:
-            depth = [3, 4, 23, 3]
-        elif layers == 152:
-            depth = [3, 8, 36, 3]
+            depth = [3, 3, 22, 2]
+
         num_filters = [64, 128, 256, 512]
 
         conv = self.conv_bn_layer(
@@ -62,7 +58,6 @@ class CSPResNet():
             pool_type='max',
             data_format=data_format)
 
-        if layers >= 50:
         for block in range(len(depth)):
             conv_name = "res" + str(block + 2) + chr(97)
             if block != 0:
@@ -75,11 +70,7 @@ class CSPResNet():
                     name=conv_name + "_downsample",
                     data_format=data_format)
 
-                # layer warp
-                #                 left, right = fluid.layers.split(
-                #                     conv,
-                #                     num_or_sections=[conv.shape[1]//2, conv.shape[1]//2],
-                #                     dim=1)
+            # split
             left = conv
             right = conv
             if block == 0:
@@ -129,8 +120,6 @@ class CSPResNet():
                 act="leaky_relu",
                 name=conv_name + "_merged_transition",
                 data_format=data_format)
-        else:
-            assert False, "not implemented now!!!"
 
         pool = fluid.layers.pool2d(
             input=conv,
@@ -193,7 +182,7 @@ class CSPResNet():
             ch_in = input.shape[1]
         else:
             ch_in = input.shape[-1]
-        if ch_in != ch_out or stride != 1 or is_first == True:
+        if ch_in != ch_out or stride != 1 or is_first is True:
             return self.conv_bn_layer(
                 input, ch_out, 1, stride, name=name, data_format=data_format)
         else:
@@ -239,3 +228,8 @@ class CSPResNet():
 def CSPResNet50():
     model = CSPResNet(layers=50)
     return model
+
+
+def CSPResNet101():
+    model = CSPResNet(layers=101)
+    return model