From 1d39358358e993a9a18bff89095e9358e702d51d Mon Sep 17 00:00:00 2001
From: weishengyu <weishengyu@baidu.com>
Date: Wed, 26 May 2021 00:31:08 +0800
Subject: [PATCH] dbg

---
 ppcls/arch/backbone/legendary_models/hrnet.py | 16 ++++------------
 1 file changed, 4 insertions(+), 12 deletions(-)

diff --git a/ppcls/arch/backbone/legendary_models/hrnet.py b/ppcls/arch/backbone/legendary_models/hrnet.py
index 5a0bf449..fd8713d4 100644
--- a/ppcls/arch/backbone/legendary_models/hrnet.py
+++ b/ppcls/arch/backbone/legendary_models/hrnet.py
@@ -218,7 +218,6 @@ class SELayer(TheseusLayer):
 
 class Stage(TheseusLayer):
     def __init__(self,
-                 num_channels,
                  num_modules,
                  num_filters,
                  has_se=False,
@@ -234,7 +233,6 @@ class Stage(TheseusLayer):
                 stage_func = self.add_sublayer(
                     "stage_{}_{}".format(name, i + 1),
                     HighResolutionModule(
-                        num_channels=num_channels,
                         num_filters=num_filters,
                         has_se=has_se,
                         multi_scale_output=False,
@@ -243,7 +241,6 @@ class Stage(TheseusLayer):
                 stage_func = self.add_sublayer(
                     "stage_{}_{}".format(name, i + 1),
                     HighResolutionModule(
-                        num_channels=num_channels,
                         num_filters=num_filters,
                         has_se=has_se,
                         name=name + '_' + str(i + 1)))
@@ -259,7 +256,6 @@ class Stage(TheseusLayer):
 
 class HighResolutionModule(TheseusLayer):
     def __init__(self,
-                 num_channels,
                  num_filters,
                  has_se=False,
                  multi_scale_output=True,
@@ -271,7 +267,7 @@ class HighResolutionModule(TheseusLayer):
         for i in range(len(num_filters)):
             self.basic_block_list.append([])
             for j in range(4):
-                in_ch = num_channels[i] if j == 0 else num_channels[i]
+                in_ch = num_filters[i]
                 basic_block_func = self.add_sublayer(
                     "bb_{}_branch_layer_{}_{}".format(name, i + 1, j + 1),
                     BasicBlock(
@@ -425,7 +421,6 @@ class HRNet(TheseusLayer):
         self._class_dim = class_dim
 
         channels_2, channels_3, channels_4 = self.channels[width]
-        num_modules_2, num_modules_3, num_modules_4 = 1, 4, 3
 
         self.conv_layer1_1 = ConvBNLayer(
             num_channels=3,
@@ -462,8 +457,7 @@ class HRNet(TheseusLayer):
         )
 
         self.st2 = Stage(
-            num_channels=channels_2,
-            num_modules=num_modules_2,
+            num_modules=1,
             num_filters=channels_2,
             has_se=self.has_se,
             name="st2")
@@ -475,8 +469,7 @@ class HRNet(TheseusLayer):
             stride=2
         )
         self.st3 = Stage(
-            num_channels=channels_3,
-            num_modules=num_modules_3,
+            num_modules=4,
             num_filters=channels_3,
             has_se=self.has_se,
             name="st3")
@@ -489,8 +482,7 @@ class HRNet(TheseusLayer):
         )
 
         self.st4 = Stage(
-            num_channels=channels_4,
-            num_modules=num_modules_4,
+            num_modules=3,
             num_filters=channels_4,
             has_se=self.has_se,
             name="st4")
-- 
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