help="Path of the corpus to evaluate on",
default=None)
argp.add_argument('--outputs_path', default=None)
args = argp.parse_args()
# Save the device
device = torch.cuda.current_device() if torch.cuda.is_available() else 'cpu'
# Keep the block size 128
# Why is the pretraining corpus always required (even if we're not pretraining?)
# It's because we're using it as a hack to always have the same vocabulary
# (that is, the same mapping from character to integer, and we build the
# vocab from the pretraining corpus.)
block_size = 128
text = open(args.pretrain_corpus_path).read()
pretrain_dataset = dataset.CharCorruptionDataset(text, block_size)
# We don't suggest you change these hyperparameters, as they're known to work.
# use them for both the vanilla and the synthesizer models
mconf = model.GPTConfig(pretrain_dataset.vocab_size,
pretrain_dataset.block_size,
n_layer=4,
n_head=8,
n_embd=256)
"""
Don't change above here; write your code below
"""
if args.variant == 'vanilla':
pass # TODO [part c]: Make some model here
elif args.variant == 'synthesizer':
argp.add_argument('--eval_corpus_path',
help="Path of the corpus to evaluate on", default=None)
argp.add_argument('--outputs_path', default=None)
args = argp.parse_args()
# Save the device
device = torch.cuda.current_device() if torch.cuda.is_available() else 'cpu'
# Keep the block size 128
# Why is the pretraining corpus always required (even if we're not pretraining?)
# It's because we're using it as a hack to always have the same vocabulary
# (that is, the same mapping from character to integer, and we build the
# vocab from the pretraining corpus.)
block_size = 128
text = open(args.pretrain_corpus_path).read()
pretrain_dataset = dataset.CharCorruptionDataset(text, block_size)
# We don't suggest you change these hyperparameters, as they're known to work.
# use them for both the vanilla and the synthesizer models
mconf = model.GPTConfig(pretrain_dataset.vocab_size, pretrain_dataset.block_size,
n_layer=4, n_head=8, n_embd=256)
"""
Don't change above here; write your code below
"""
if args.variant == 'vanilla':
#pass # TODO [part c]: Make some model here
model = model.GPT(mconf, "vanilla")
elif args.variant == 'synthesizer':
#pass # TODO [part g]: Make some other model here
