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def make_hashable_key(dict_key):
def convert_value(value):
if isinstance(value, list):
return tuple(value)
elif isinstance(value, dict):
return tuple(sorted((k, convert_value(v)) for k, v in value.items()))
else:
return value
return tuple(sorted((k, convert_value(v)) for k, v in dict_key.items()))
DIFFUSERS_SCHEDULER_CONFIG = {
"_class_name": "FlowMatchEulerDiscreteScheduler",
"_diffusers_version": "0.32.0.dev0",
"base_image_seq_len": 1024,
"base_shift": 0.95,
"invert_sigmas": False,
"max_image_seq_len": 4096,
"max_shift": 2.05,
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": 0.1,
"use_beta_sigmas": False,
"use_dynamic_shifting": True,
"use_exponential_sigmas": False,
"use_karras_sigmas": False,
}
DIFFUSERS_TRANSFORMER_CONFIG = {
"_class_name": "LTXVideoTransformer3DModel",
"_diffusers_version": "0.32.0.dev0",
"activation_fn": "gelu-approximate",
"attention_bias": True,
"attention_head_dim": 64,
"attention_out_bias": True,
"caption_channels": 4096,
"cross_attention_dim": 2048,
"in_channels": 128,
"norm_elementwise_affine": False,
"norm_eps": 1e-06,
"num_attention_heads": 32,
"num_layers": 28,
"out_channels": 128,
"patch_size": 1,
"patch_size_t": 1,
"qk_norm": "rms_norm_across_heads",
}
DIFFUSERS_VAE_CONFIG = {
"_class_name": "AutoencoderKLLTXVideo",
"_diffusers_version": "0.32.0.dev0",
"block_out_channels": [128, 256, 512, 512],
"decoder_causal": False,
"encoder_causal": True,
"in_channels": 3,
"latent_channels": 128,
"layers_per_block": [4, 3, 3, 3, 4],
"out_channels": 3,
"patch_size": 4,
"patch_size_t": 1,
"resnet_norm_eps": 1e-06,
"scaling_factor": 1.0,
"spatio_temporal_scaling": [True, True, True, False],
}
OURS_SCHEDULER_CONFIG = {
"_class_name": "RectifiedFlowScheduler",
"_diffusers_version": "0.25.1",
"num_train_timesteps": 1000,
"shifting": "SD3",
"base_resolution": None,
"target_shift_terminal": 0.1,
}
OURS_TRANSFORMER_CONFIG = {
"_class_name": "Transformer3DModel",
"_diffusers_version": "0.25.1",
"_name_or_path": "PixArt-alpha/PixArt-XL-2-256x256",
"activation_fn": "gelu-approximate",
"attention_bias": True,
"attention_head_dim": 64,
"attention_type": "default",
"caption_channels": 4096,
"cross_attention_dim": 2048,
"double_self_attention": False,
"dropout": 0.0,
"in_channels": 128,
"norm_elementwise_affine": False,
"norm_eps": 1e-06,
"norm_num_groups": 32,
"num_attention_heads": 32,
"num_embeds_ada_norm": 1000,
"num_layers": 28,
"num_vector_embeds": None,
"only_cross_attention": False,
"out_channels": 128,
"project_to_2d_pos": True,
"upcast_attention": False,
"use_linear_projection": False,
"qk_norm": "rms_norm",
"standardization_norm": "rms_norm",
"positional_embedding_type": "rope",
"positional_embedding_theta": 10000.0,
"positional_embedding_max_pos": [20, 2048, 2048],
"timestep_scale_multiplier": 1000,
}
OURS_VAE_CONFIG = {
"_class_name": "CausalVideoAutoencoder",
"dims": 3,
"in_channels": 3,
"out_channels": 3,
"latent_channels": 128,
"blocks": [
["res_x", 4],
["compress_all", 1],
["res_x_y", 1],
["res_x", 3],
["compress_all", 1],
["res_x_y", 1],
["res_x", 3],
["compress_all", 1],
["res_x", 3],
["res_x", 4],
],
"scaling_factor": 1.0,
"norm_layer": "pixel_norm",
"patch_size": 4,
"latent_log_var": "uniform",
"use_quant_conv": False,
"causal_decoder": False,
}
diffusers_and_ours_config_mapping = {
make_hashable_key(DIFFUSERS_SCHEDULER_CONFIG): OURS_SCHEDULER_CONFIG,
make_hashable_key(DIFFUSERS_TRANSFORMER_CONFIG): OURS_TRANSFORMER_CONFIG,
make_hashable_key(DIFFUSERS_VAE_CONFIG): OURS_VAE_CONFIG,
}
TRANSFORMER_KEYS_RENAME_DICT = {
"proj_in": "patchify_proj",
"time_embed": "adaln_single",
"norm_q": "q_norm",
"norm_k": "k_norm",
}
VAE_KEYS_RENAME_DICT = {
"decoder.up_blocks.3.conv_in": "decoder.up_blocks.7",
"decoder.up_blocks.3.upsamplers.0": "decoder.up_blocks.8",
"decoder.up_blocks.3": "decoder.up_blocks.9",
"decoder.up_blocks.2.upsamplers.0": "decoder.up_blocks.5",
"decoder.up_blocks.2.conv_in": "decoder.up_blocks.4",
"decoder.up_blocks.2": "decoder.up_blocks.6",
"decoder.up_blocks.1.upsamplers.0": "decoder.up_blocks.2",
"decoder.up_blocks.1": "decoder.up_blocks.3",
"decoder.up_blocks.0": "decoder.up_blocks.1",
"decoder.mid_block": "decoder.up_blocks.0",
"encoder.down_blocks.3": "encoder.down_blocks.8",
"encoder.down_blocks.2.downsamplers.0": "encoder.down_blocks.7",
"encoder.down_blocks.2": "encoder.down_blocks.6",
"encoder.down_blocks.1.downsamplers.0": "encoder.down_blocks.4",
"encoder.down_blocks.1.conv_out": "encoder.down_blocks.5",
"encoder.down_blocks.1": "encoder.down_blocks.3",
"encoder.down_blocks.0.conv_out": "encoder.down_blocks.2",
"encoder.down_blocks.0.downsamplers.0": "encoder.down_blocks.1",
"encoder.down_blocks.0": "encoder.down_blocks.0",
"encoder.mid_block": "encoder.down_blocks.9",
"conv_shortcut.conv": "conv_shortcut",
"resnets": "res_blocks",
"norm3": "norm3.norm",
"latents_mean": "per_channel_statistics.mean-of-means",
"latents_std": "per_channel_statistics.std-of-means",
}
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