| | |
|---|
| | | kwargs = download_model(**kwargs) |
|---|
| | | |
|---|
| | | set_all_random_seed(kwargs.get("seed", 0)) |
|---|
| | | |
|---|
| | | |
|---|
| | | device = kwargs.get("device", "cuda") |
|---|
| | | if not torch.cuda.is_available() or kwargs.get("ngpu", 1) == 0: |
|---|
| | | device = "cpu" |
|---|
| | |
|---|
| | | |
|---|
| | | # build model |
|---|
| | | model_class = tables.model_classes.get(kwargs["model"]) |
|---|
| | | pdb.set_trace() |
|---|
| | | model = model_class(**kwargs, **kwargs["model_conf"], vocab_size=vocab_size) |
|---|
| | | pdb.set_trace() |
|---|
| | | model.to(device) |
|---|
| | | |
|---|
| | | # init_param |
|---|
| | | init_param = kwargs.get("init_param", None) |
|---|
| | | pdb.set_trace() |
|---|
| | | if init_param is not None: |
|---|
| | | logging.info(f"Loading pretrained params from {init_param}") |
|---|
| | | load_pretrained_model( |
|---|
