Error while training on custom data using Image dataset input loading

[KoushikSamudrala]

1. I am trying to train on my custom dataset using SelfSupModel but while training the model does not read the training images from the train split file and indicates 0 images there and read all the images in the testing set and outputs an error. It would be very kind of you if you can help me here. I am using Image_dataset as a loading input reference.
   2)Also, how can we able to measure validation_loss from the code in this repo as validation_epoch_end returns **metrics_dict and not loss_and_metrics like the training loop? I'm a beginner to this programming and any help in this regard to estimating validation loss is helpful for me.

My config file looks like this:
arch:
max_epochs: 10
checkpoint:
filepath: '/content/drive/MyDrive/packnetsfm/checkpoints/'
monitor: 'abs_rel_pp_gt'
#monitor_index: 0
save_top_k: -1
mode: 'min'
model:
name: 'SelfSupModel'
checkpoint_path: '/content/drive/MyDrive/packnetsfm/checkpoints/PackNet01_MR_velsup_CStoK.ckpt'
optimizer:
name: 'Adam'
depth:
lr: 0.0001
pose:
lr: 0.0001
scheduler:
name: 'StepLR'
step_size: 30
gamma: 0.5
depth_net:
name: 'PackNet01'
version: '1A'
pose_net:
name: 'PoseNet'
version: ''
params:
crop: 'garg'
min_depth: 0.0
max_depth: 200.0
datasets:
augmentation:
image_shape: (384,640)
train:
batch_size: 3
dataset: ['Image']
path: ['/content/drive/MyDrive/data']
split: ['{:02}']
validation:
dataset: ['Image']
path: ['/content/drive/MyDrive/data']
split: ['{:03}']