remove error causeing (?) ResNET parameter and reduce range of lr

configs/hparams_search/focusResNetMSE_150.yaml

@@ -55,12 +55,11 @@ hydra:
  choices: [true, false]
  model.lr:
  type: float
- low: 0.0001
+ low: 0.001
  high: 0.01
  model.resnet_type:
  type: categorical
- choices: [
- "ResNet", 
+ choices: [ 
  "resnet18",
  "resnet34",
  "resnet50",

src/models/focus_resnet_module.py

@@ -12,7 +12,7 @@ import torchvision.models as models
 class ResNetLitModule(LightningModule):
  def __init__(
  self,
- resnet_type: str = "ResNet",
+ resnet_type: str = "resnet18",
  pretrained=False,
  lr: float = 0.001,
  weight_decay: float = 0.0005,
@@ -22,7 +22,7 @@ class ResNetLitModule(LightningModule):
  Args:
  resnet_type (str, optional): Type of the used resnet network. Defaults to
  "ResNet".
- Can be one of the following values: "ResNet", "resnet18",
+ Can be one of the following values: "resnet18",
  "resnet34", "resnet50", "resnet101", "resnet152", "resnext50_32x4d",
  "resnext101_32x8d", "wide_resnet50_2", "wide_resnet101_2"
  pretrained (bool, optional): if True loads pytorch pretrained models.
@@ -48,9 +48,7 @@ class ResNetLitModule(LightningModule):
 
  self.pretrained = pretrained
 
- if resnet_type == "ResNet":
- resnet_constructor = models.ResNet
- elif resnet_type == "resnet18":
+ if resnet_type == "resnet18":
  resnet_constructor = models.resnet18
  elif resnet_type == "resnet34":
  resnet_constructor = models.resnet34