def create(name: str,
age: int,
weight: float,
human: bool,
hat_id: int = None) -> dict:
""" Create character """
result: dict = {}
try:
# if hat_id is not None, check if exists, throw exception instead
if hat_id is not None:
hat = HatModel.query.get(hat_id)
if hat is None:
raise ResourceDoesNotExist(
"Hat {} does not exist".format(hat_id))
character = CharacterModel(name=name,
age=age,
weight=weight,
human=human,
hat_id=hat_id)
character.save()
result = {
'id': character.id,
'name': character.name,
'age': character.age,
'weight': character.weight,
'human': character.human,
'hat_id': character.hat_id,
}
except IntegrityError:
CharacterModel.rollback()
# raise ResourceExists('Character already exists')
return result
def create(event, context):
logger.debug(f'Event received: {json.dumps(event)}')
data = json.loads(event.get('body'))
character = CharacterModel(id=str(uuid4()),
name=data.get('name'),
account=data.get('account', 'None'),
player_class=int(data.get('player_class')),
created_at=datetime.utcnow())
character.save()
response = {
'statusCode': 200,
'body': json.dumps(character, cls=ModelEncoder),
'headers': {
'Access-Control-Allow-Origin': '*'
}
}
logger.debug(f'Response: {json.dumps(response)}')
return response
char_train_dataset = CharacterDataset(train_texts,
train_selected_texts,
train_offsets,
train_start_logits_list,
train_end_logits_list)
char_val_dataset = CharacterDataset(val_texts, val_selected_texts,
val_offsets_list,
val_start_logits_list,
val_end_logits_list)
char_train_loader = torch.utils.data.DataLoader(
dataset=char_train_dataset,
batch_size=config.batch_size,
shuffle=False)
char_val_loader = torch.utils.data.DataLoader(
dataset=char_val_dataset,
batch_size=config.batch_size,
shuffle=False)
dataloaders_dict = {'train': char_train_loader, 'val': char_val_loader}
char_model = CharacterModel()
char_model.to(device)
optimizer = optim.AdamW(char_model.parameters(),
lr=config.character_lr,
betas=(0.9, 0.999))
print('Training Character Model for fold ' + str(fold))
train_character_model(char_model, device, dataloaders_dict, criterion,
optimizer, fold)
# }
# character = get(request, None)
# print()
# print()
# print(character['body'])
# print()
# print('All characters')
# response = list(None, None)
# print(response)
character_1 = CharacterModel(name='Angst')
character_1.save()
print(character_1)
character_1.add_item(
InventoryItemMap(id=str(uuid4()),
slot=1,
slot_name='Head',
damage=21,
crit_chance=.025))
character_1.save()
print()
print(character_1)