v1.4

• Add examples for image reconstruction and semantic segmentation with Poutyne.
• Add the following flags in ProgressionCallback:
  show_every_n_train_steps, show_every_n_valid_steps, show_every_n_test_steps. They allow to show only certain
  steps instead of all steps.
• Fix bug where all warnings were silenced.
• Add strict flag when loading checkpoints. In Model, a NamedTuple is returned as in PyTorch's load_state_dict. In
  Experiment, a warning is raised when there are missing or unexpected keys in the checkpoint.
• In CSVLogger, when multiple learning rates are used, we use the column names lr_group_0, lr_group_1, etc. instead
  of lr.
• Fix bug where EarlyStopping would be one epoch late and would anyway disregard the monitored metric at the last epoch.