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77 lines
2.5 KiB
77 lines
2.5 KiB
# -*- coding: utf-8 -*-
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import os
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import torch
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from huggingface_hub import hf_hub_url, cached_download
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from .model import DalleModel
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from .fp16 import FP16Module
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MODELS = {
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'Malevich': dict(
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description='◼️ Malevich is 1.3 billion params model from the family GPT3-like, '
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'that uses Russian language and text+image multi-modality.',
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model_params=dict(
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num_layers=24,
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hidden_size=2048,
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num_attention_heads=16,
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embedding_dropout_prob=0.1,
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output_dropout_prob=0.1,
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attention_dropout_prob=0.1,
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image_tokens_per_dim=32,
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text_seq_length=128,
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cogview_sandwich_layernorm=True,
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cogview_pb_relax=True,
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vocab_size=16384+128,
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image_vocab_size=8192,
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),
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repo_id='sberbank-ai/rudalle-Malevich',
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filename='pytorch_model_v2.bin',
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full_description='', # TODO
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),
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'small': dict(
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description='',
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model_params=dict(
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num_layers=12,
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hidden_size=768,
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num_attention_heads=12,
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embedding_dropout_prob=0.1,
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output_dropout_prob=0.1,
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attention_dropout_prob=0.1,
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image_tokens_per_dim=32,
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text_seq_length=128,
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cogview_sandwich_layernorm=True,
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cogview_pb_relax=True,
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vocab_size=16384+128,
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image_vocab_size=8192,
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),
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repo_id='',
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filename='',
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full_description='', # TODO
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),
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}
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def get_rudalle_model(name, pretrained=True, fp16=False, device='cpu', cache_dir='/tmp/rudalle'):
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# TODO docstring
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assert name in MODELS
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if fp16 and device == 'cpu':
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print('Warning! Using both fp16 and cpu doesnt support. You can use cuda device or turn off fp16.')
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config = MODELS[name]
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model = DalleModel(device=device, **config['model_params'])
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if pretrained:
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cache_dir = os.path.join(cache_dir, name)
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config_file_url = hf_hub_url(repo_id=config['repo_id'], filename=config['filename'])
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cached_download(config_file_url, cache_dir=cache_dir, force_filename=config['filename'])
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checkpoint = torch.load(os.path.join(cache_dir, config['filename']), map_location='cpu')
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model.load_state_dict(checkpoint)
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if fp16:
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model = FP16Module(model)
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model.eval()
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model = model.to(device)
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if config['description'] and pretrained:
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print(config['description'])
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return model
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