forked from mrq/DL-Art-School
Formatting issue with gdi
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@ -16,7 +16,8 @@ class GaussianDiffusionInjector(Injector):
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self.output_variational_bounds_key = opt['out_key_vb_loss']
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self.output_x_start_key = opt['out_key_x_start']
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opt['diffusion_args']['betas'] = get_named_beta_schedule(**opt['beta_schedule'])
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opt['diffusion_args']['use_timesteps'] = space_timesteps(opt['beta_schedule']['num_diffusion_timesteps'], [opt['beta_schedule']['num_diffusion_timesteps']]) # TODO: Figure out how these work and specify them differently.
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opt['diffusion_args']['use_timesteps'] = space_timesteps(opt['beta_schedule']['num_diffusion_timesteps'],
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[opt['beta_schedule']['num_diffusion_timesteps']])
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self.diffusion = SpacedDiffusion(**opt['diffusion_args'])
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self.schedule_sampler = create_named_schedule_sampler(opt['sampler_type'], self.diffusion)
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self.model_input_keys = opt_get(opt, ['model_input_keys'], [])
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@ -41,7 +42,8 @@ class GaussianDiffusionInferenceInjector(Injector):
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self.generator = opt['generator']
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self.output_shape = opt['output_shape']
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opt['diffusion_args']['betas'] = get_named_beta_schedule(**opt['beta_schedule'])
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opt['diffusion_args']['use_timesteps'] = space_timesteps(opt['beta_schedule']['num_diffusion_timesteps'], [opt_get(opt, ['respaced_timestep_spacing'], opt['beta_schedule']['num_diffusion_timesteps'])]) # TODO: Figure out how these work and specify them differently.
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opt['diffusion_args']['use_timesteps'] = space_timesteps(opt['beta_schedule']['num_diffusion_timesteps'],
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[opt_get(opt, ['respaced_timestep_spacing'], opt['beta_schedule']['num_diffusion_timesteps'])])
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self.diffusion = SpacedDiffusion(**opt['diffusion_args'])
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self.model_input_keys = opt_get(opt, ['model_input_keys'], [])
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