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adm-g_ddim25_8xb32_imagenet_256x256 源代码

# Copyright (c) OpenMMLab. All rights reserved.
from mmengine.config import read_base

with read_base():
    from .adm_ddim250_8xb32_imagenet_256x256 import *

from mmagic.evaluation.metrics import FrechetInceptionDistance
from mmagic.models.editors.guided_diffusion.classifier import EncoderUNetModel

model.update(
    dict(
        classifier=dict(
            type=EncoderUNetModel,
            image_size=256,
            in_channels=3,
            model_channels=128,
            out_channels=1000,
            num_res_blocks=2,
            attention_resolutions=(8, 16, 32),
            channel_mult=(1, 1, 2, 2, 4, 4),
            use_fp16=False,
            num_head_channels=64,
            use_scale_shift_norm=True,
            resblock_updown=True,
            pool='attention')))

[文档]metrics = [ dict( type=FrechetInceptionDistance, prefix='FID-Full-50k', fake_nums=50000, inception_style='StyleGAN', sample_model='orig', sample_kwargs=dict( num_inference_steps=250, show_progress=True, classifier_scale=1.))
]
[文档]val_evaluator = dict(metrics=metrics)
[文档]test_evaluator = dict(metrics=metrics)
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