ultralytics 8.0.110 new profile and fraction train args (#2880)

docs/reference/nn/modules/conv.md

@@ -7,6 +7,11 @@ description: Explore convolutional neural network modules & techniques such as L
 :::ultralytics.nn.modules.conv.Conv
 <br><br>
 
+# Conv2
+---
+:::ultralytics.nn.modules.conv.Conv2
+<br><br>
+
 # LightConv
 ---
 :::ultralytics.nn.modules.conv.LightConv

docs/reference/yolo/data/augment.md

@@ -87,6 +87,11 @@ description: Use Ultralytics YOLO Data Augmentation transforms with Base, MixUp,
 :::ultralytics.yolo.data.augment.classify_transforms
 <br><br>
 
+# hsv2colorjitter
+---
+:::ultralytics.yolo.data.augment.hsv2colorjitter
+<br><br>
+
 # classify_albumentations
 ---
 :::ultralytics.yolo.data.augment.classify_albumentations

docs/reference/yolo/utils/benchmarks.md

@@ -2,6 +2,11 @@
 description: Improve your YOLO's performance and measure its speed. Benchmark utility for YOLOv5.
 ---
 
+# ProfileModels
+---
+:::ultralytics.yolo.utils.benchmarks.ProfileModels
+<br><br>
+
 # benchmark
 ---
 :::ultralytics.yolo.utils.benchmarks.benchmark

docs/reference/yolo/utils/torch_utils.md

@@ -57,11 +57,21 @@ description: Optimize your PyTorch models with Ultralytics YOLO's torch_utils fu
 :::ultralytics.yolo.utils.torch_utils.get_num_gradients
 <br><br>
 
+# model_info_for_loggers
+---
+:::ultralytics.yolo.utils.torch_utils.model_info_for_loggers
+<br><br>
+
 # get_flops
 ---
 :::ultralytics.yolo.utils.torch_utils.get_flops
 <br><br>
 
+# get_flops_with_torch_profiler
+---
+:::ultralytics.yolo.utils.torch_utils.get_flops_with_torch_profiler
+<br><br>
+
 # initialize_weights
 ---
 :::ultralytics.yolo.utils.torch_utils.initialize_weights