Add warmup and accumulation (#52)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/utils/configs/default.yaml

@@ -27,6 +27,7 @@ single_cls: False  # train multi-class data as single-class
 image_weights: False  # use weighted image selection for training
 shuffle: True
 rect: False  # support rectangular training
+cos_lr: False # Use cosine LR scheduler
 overlap_mask: True  # Segmentation masks overlap
 mask_ratio: 4  # Segmentation mask downsample ratio
 
@@ -71,6 +72,7 @@ mosaic: 1.0  # image mosaic (probability)
 mixup: 0.0  # image mixup (probability)
 copy_paste: 0.0  # segment copy-paste (probability)
 label_smoothing: 0.0
+nbs: 64 # nominal batch size
 # anchors: 3
 
 # Hydra configs --------------------------------------------------------------------------------------------------------

ultralytics/yolo/utils/torch_utils.py

@@ -194,6 +194,11 @@ def de_parallel(model):
     return model.module if is_parallel(model) else model
 
 
+def one_cycle(y1=0.0, y2=1.0, steps=100):
+    # lambda function for sinusoidal ramp from y1 to y2 https://arxiv.org/pdf/1812.01187.pdf
+    return lambda x: ((1 - math.cos(x * math.pi / steps)) / 2) * (y2 - y1) + y1
+
+
 class ModelEMA:
     """ Updated Exponential Moving Average (EMA) from https://github.com/rwightman/pytorch-image-models
     Keeps a moving average of everything in the model state_dict (parameters and buffers)