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Delete fifthmix

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  1. fifthmix/fifthMix_screwdriver.yaml +0 -98
fifthmix/fifthMix_screwdriver.yaml DELETED
@@ -1,98 +0,0 @@
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- model:
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- target: sgm.models.diffusion.DiffusionEngine
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- params:
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- scale_factor: 0.13025
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- disable_first_stage_autocast: True
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-
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- denoiser_config:
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- target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
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- params:
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- num_idx: 1000
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-
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- weighting_config:
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- target: sgm.modules.diffusionmodules.denoiser_weighting.VWeighting
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- scaling_config:
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- target: sgm.modules.diffusionmodules.denoiser_scaling.VScaling
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- discretization_config:
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- target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
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-
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- network_config:
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- target: sgm.modules.diffusionmodules.openaimodel.UNetModel
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- params:
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- adm_in_channels: 2816
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- num_classes: sequential
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- use_checkpoint: True
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- in_channels: 4
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- out_channels: 4
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- model_channels: 320
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- attention_resolutions: [4, 2]
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- num_res_blocks: 2
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- channel_mult: [1, 2, 4]
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- num_head_channels: 64
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- use_spatial_transformer: True
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- use_linear_in_transformer: True
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- transformer_depth: [1, 2, 10] # note: the first is unused (due to attn_res starting at 2) 32, 16, 8 --> 64, 32, 16
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- context_dim: 2048
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- spatial_transformer_attn_type: softmax-xformers
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- legacy: False
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-
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- conditioner_config:
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- target: sgm.modules.GeneralConditioner
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- params:
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- emb_models:
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- # crossattn cond
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- - is_trainable: False
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- input_key: txt
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- target: sgm.modules.encoders.modules.FrozenCLIPEmbedder
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- params:
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- layer: hidden
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- layer_idx: 11
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- # crossattn and vector cond
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- - is_trainable: False
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- input_key: txt
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- target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
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- params:
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- arch: ViT-bigG-14
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- version: laion2b_s39b_b160k
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- freeze: True
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- layer: penultimate
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- always_return_pooled: True
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- legacy: False
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- # vector cond
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- - is_trainable: False
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- input_key: original_size_as_tuple
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- target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
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- params:
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- outdim: 256 # multiplied by two
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- # vector cond
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- - is_trainable: False
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- input_key: crop_coords_top_left
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- target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
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- params:
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- outdim: 256 # multiplied by two
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- # vector cond
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- - is_trainable: False
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- input_key: target_size_as_tuple
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- target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
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- params:
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- outdim: 256 # multiplied by two
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-
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- first_stage_config:
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- target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper
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- params:
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- embed_dim: 4
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- monitor: val/rec_loss
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- ddconfig:
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- attn_type: vanilla-xformers
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- double_z: true
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- z_channels: 4
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- resolution: 256
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- in_channels: 3
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- out_ch: 3
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- ch: 128
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- ch_mult: [1, 2, 4, 4]
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- num_res_blocks: 2
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- attn_resolutions: []
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- dropout: 0.0
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- lossconfig:
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- target: torch.nn.Identity