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# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch
from nemo.collections.multimodal.models.text_to_image.stable_diffusion.ldm.ddpm import MegatronLatentDiffusion
from nemo.collections.multimodal.parts.stable_diffusion.pipeline import pipeline
from nemo.collections.multimodal.parts.utils import setup_trainer_and_model_for_inference
from nemo.core.config import hydra_runner
@hydra_runner(config_path='conf', config_name='sd_infer')
def main(cfg):
def model_cfg_modifier(model_cfg):
model_cfg.precision = cfg.trainer.precision
model_cfg.ckpt_path = None
model_cfg.inductor = False
model_cfg.unet_config.use_flash_attention = False
model_cfg.unet_config.from_pretrained = None
model_cfg.first_stage_config.from_pretrained = None
model_cfg.first_stage_config._target_ = (
'nemo.collections.multimodal.models.text_to_image.stable_diffusion.ldm.autoencoder.AutoencoderKL'
)
torch.backends.cuda.matmul.allow_tf32 = True
trainer, megatron_diffusion_model = setup_trainer_and_model_for_inference(
model_provider=MegatronLatentDiffusion, cfg=cfg, model_cfg_modifier=model_cfg_modifier
)
model = megatron_diffusion_model.model
model.cuda().eval()
rng = torch.Generator().manual_seed(cfg.infer.seed)
pipeline(model, cfg, rng=rng)
if __name__ == "__main__":
main()