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simplified instructions to preload Bert and kornia prerequisites; fixed --grid and --batch handling; added timing information after image generation

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Lincoln Stein
2022-08-17 12:00:00 -04:00
parent fab1ae8685
commit a7532b386a
5 changed files with 105 additions and 68 deletions
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11
ldm/modules/encoders/modules.py
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@ -55,10 +55,12 @@ class BERTTokenizer(AbstractEncoder):
def __init__(self, device="cuda", vq_interface=True, max_length=77):
super().__init__()
from transformers import BertTokenizerFast # TODO: add to reuquirements
fn = 'models/bert'
print(f'Loading Bert tokenizer from "{fn}"')
# self.tokenizer = BertTokenizerFast.from_pretrained("bert-base-uncased")
self.tokenizer = BertTokenizerFast.from_pretrained(fn,local_files_only=True)
# Modified to allow to run on non-internet connected compute nodes.
# Model needs to be loaded into cache from an internet-connected machine
# by running:
# from transformers import BertTokenizerFast
# BertTokenizerFast.from_pretrained("bert-base-uncased")
self.tokenizer = BertTokenizerFast.from_pretrained("bert-base-uncased",local_files_only=True)
self.device = device
self.vq_interface = vq_interface
self.max_length = max_length
@ -235,4 +237,3 @@ if __name__ == "__main__":
from ldm.util import count_params
model = FrozenCLIPEmbedder()
count_params(model, verbose=True)