From 0b3cd1e6b9e4884b7ce67c08ca7dad0fca7bb357 Mon Sep 17 00:00:00 2001
From: Z-Fran <1396925302@qq.com>
Date: Thu, 20 Oct 2022 12:56:30 +0800
Subject: [PATCH] fix edsr

---
 configs/edsr/edsr_x2c64b16_1xb16-300k_div2k.py | 6 ++++--
 configs/edsr/edsr_x3c64b16_1xb16-300k_div2k.py | 8 +++++---
 configs/edsr/edsr_x4c64b16_1xb16-300k_div2k.py | 8 +++++---
 3 files changed, 14 insertions(+), 8 deletions(-)

diff --git a/configs/edsr/edsr_x2c64b16_1xb16-300k_div2k.py b/configs/edsr/edsr_x2c64b16_1xb16-300k_div2k.py
index 593753e342..ec5f7f4e09 100644
--- a/configs/edsr/edsr_x2c64b16_1xb16-300k_div2k.py
+++ b/configs/edsr/edsr_x2c64b16_1xb16-300k_div2k.py
@@ -73,7 +73,9 @@
 data_root = 'data'
 
 train_dataloader = dict(
-    num_workers=4,
+    num_workers=8,
+    batch_size=16,
+    drop_last=True,
     persistent_workers=False,
     sampler=dict(type='InfiniteSampler', shuffle=True),
     dataset=dict(
@@ -112,7 +114,7 @@
 optim_wrapper = dict(
     constructor='DefaultOptimWrapperConstructor',
     type='OptimWrapper',
-    optimizer=dict(type='Adam', lr=1e-4, betas=(0.9, 0.99)))
+    optimizer=dict(type='Adam', lr=1e-4, betas=(0.9, 0.999)))
 
 # learning policy
 param_scheduler = dict(
diff --git a/configs/edsr/edsr_x3c64b16_1xb16-300k_div2k.py b/configs/edsr/edsr_x3c64b16_1xb16-300k_div2k.py
index be54ae082d..3ac6695d05 100644
--- a/configs/edsr/edsr_x3c64b16_1xb16-300k_div2k.py
+++ b/configs/edsr/edsr_x3c64b16_1xb16-300k_div2k.py
@@ -43,7 +43,7 @@
         channel_order='rgb',
         imdecode_backend='cv2'),
     dict(type='SetValues', dictionary=dict(scale=scale)),
-    dict(type='PairedRandomCrop', gt_patch_size=96),
+    dict(type='PairedRandomCrop', gt_patch_size=144),
     dict(
         type='Flip',
         keys=['img', 'gt'],
@@ -75,7 +75,9 @@
 data_root = 'data'
 
 train_dataloader = dict(
-    num_workers=4,
+    num_workers=8,
+    batch_size=16,
+    drop_last=True,
     persistent_workers=False,
     sampler=dict(type='InfiniteSampler', shuffle=True),
     dataset=dict(
@@ -114,7 +116,7 @@
 optim_wrapper = dict(
     constructor='DefaultOptimWrapperConstructor',
     type='OptimWrapper',
-    optimizer=dict(type='Adam', lr=1e-4, betas=(0.9, 0.99)))
+    optimizer=dict(type='Adam', lr=1e-4, betas=(0.9, 0.999)))
 
 # learning policy
 param_scheduler = dict(
diff --git a/configs/edsr/edsr_x4c64b16_1xb16-300k_div2k.py b/configs/edsr/edsr_x4c64b16_1xb16-300k_div2k.py
index b57c5797d9..1e878cc725 100644
--- a/configs/edsr/edsr_x4c64b16_1xb16-300k_div2k.py
+++ b/configs/edsr/edsr_x4c64b16_1xb16-300k_div2k.py
@@ -43,7 +43,7 @@
         channel_order='rgb',
         imdecode_backend='cv2'),
     dict(type='SetValues', dictionary=dict(scale=scale)),
-    dict(type='PairedRandomCrop', gt_patch_size=96),
+    dict(type='PairedRandomCrop', gt_patch_size=196),
     dict(
         type='Flip',
         keys=['img', 'gt'],
@@ -75,7 +75,9 @@
 data_root = 'data'
 
 train_dataloader = dict(
-    num_workers=4,
+    num_workers=8,
+    batch_size=16,
+    drop_last=True,
     persistent_workers=False,
     sampler=dict(type='InfiniteSampler', shuffle=True),
     dataset=dict(
@@ -114,7 +116,7 @@
 optim_wrapper = dict(
     constructor='DefaultOptimWrapperConstructor',
     type='OptimWrapper',
-    optimizer=dict(type='Adam', lr=1e-4, betas=(0.9, 0.99)))
+    optimizer=dict(type='Adam', lr=1e-4, betas=(0.9, 0.999)))
 
 # learning policy
 param_scheduler = dict(