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	Using devices [TpuDevice(id=0, process_index=0, coords=(0,0,0), core_on_chip=0), TpuDevice(id=1, process_index=0, coords=(1,0,0), core_on_chip=0), TpuDevice(id=2, process_index=0, coords=(0,1,0), core_on_chip=0), TpuDevice(id=3, process_index=0, coords=(1,1,0), core_on_chip=0)]
	Device count 4
	Global device count 4
	Global Batch: 512
	Node Batch: 512
	Device Batch: 128
	/tmp/tmp57xxkh9z
	Loading dataset
	Loading dataset
	creating model
	beta1: 0.9
	beta2: 0.999
	bootstrap_cfg: 1
	bootstrap_dt_bias: 0
	bootstrap_ema: 1
	bootstrap_every: 8
	cfg_scale: 1.5
	class_dropout_prob: 0.1
	denoise_timesteps: 128
	depth: 12
	dropout: 0.0
	dt_sampling: uniform
	hidden_size: 768
	lr: 0.0001
	mlp_ratio: 4
	num_classes: 1000
	num_heads: 12
	patch_size: 2
	sharding: dp
	t_sampling: discrete-dt
	target_update_rate: 0.999
	train_type: naive
	use_cosine: 0
	use_ema: 0
	use_stable_vae: 1
	warmup: 0
	weight_decay: 0.1

	Total devices TPU_0(process=0,(0,0,0,0))
	Initializing encoder.
	Incoming encoder shape (1, 256, 256, 3)
	Encoder layer (1, 256, 256, 128)
	doing downsample
	Encoder layer (1, 128, 128, 128)
	doing downsample
	Encoder layer (1, 64, 64, 256)
	doing downsample
	Encoder layer (1, 32, 32, 512)
	Encoder layer (1, 32, 32, 512)
	Encoder layer final (1, 32, 32, 512)
	Encoder layer final (1, 32, 32, 512)
	Final embeddings are size (1, 32, 32, 8)
	After quant (1, 32, 32, 4)
	encode finished
	Decoder incoming shape (1, 32, 32, 4)
	Decoder input (1, 32, 32, 512)
	Mid Block Decoder layer (1, 32, 32, 512)
	Mid Block Decoder layer (1, 32, 32, 512)
	Decoder layer (1, 64, 64, 512)
	Decoder layer (1, 128, 128, 512)
	Decoder layer (1, 256, 256, 256)
	Decoder layer (1, 256, 256, 128)
	Total num of VQVAE parameters: 67565323
	Disc shape (1, 128, 128, 128)
	Disc shape (1, 64, 64, 256)
	Disc shape (1, 32, 32, 512)
	Disc shape (1, 16, 16, 512)
	Disc shape (1, 8, 8, 512)
	Disc shape (1, 4, 4, 512)
	Total num of Discriminator parameters: 23998017
	Loaded checkpoint from 17943743 seconds ago.
	Loaded model with step 323001
	┌──────────────────────────────────────────────────────────────────────────────┐
	│ TPU 0 │
	├──────────────────────────────────────────────────────────────────────────────┤
	│ TPU 1 │
	├──────────────────────────────────────────────────────────────────────────────┤
	│ TPU 2 │
	├──────────────────────────────────────────────────────────────────────────────┤
	│ TPU 3 │
	└──────────────────────────────────────────────────────────────────────────────┘
	returning model
	model done
	Input to vae (4, 1, 256, 256, 3)
	encode image shape (1, 256, 256, 3)
	Initializing encoder.
	Incoming encoder shape (1, 256, 256, 3)
	Encoder layer (1, 256, 256, 128)
	doing downsample
	Encoder layer (1, 128, 128, 128)
	doing downsample
	Encoder layer (1, 64, 64, 256)
	doing downsample
	Encoder layer (1, 32, 32, 512)
	Encoder layer (1, 32, 32, 512)
	Encoder layer final (1, 32, 32, 512)
	Encoder layer final (1, 32, 32, 512)
	Final embeddings are size (1, 32, 32, 8)
	After quant (1, 32, 32, 4)
	output example shape (4, 1, 32, 32, 4)
	Test data shape (4, 256, 256, 3)
	x shape (4, 1, 256, 256, 3)
	encoded shape (4, 1, 32, 32, 4)
	z_vectors shape (1, 32, 32, 4)
	Decoder incoming shape (1, 32, 32, 4)
	Decoder input (1, 32, 32, 512)
	Mid Block Decoder layer (1, 32, 32, 512)
	Mid Block Decoder layer (1, 32, 32, 512)
	Decoder layer (1, 64, 64, 512)
	Decoder layer (1, 128, 128, 512)
	Decoder layer (1, 256, 256, 256)
	Decoder layer (1, 256, 256, 128)
	image shape (4, 1, 256, 256, 3)
	decoded img shape (256, 256, 3)
	obs shape (4, 32, 32, 4)
	DiT: Input of shape (4, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (4, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (4, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (1, 768) dtype float32

	[3m DiT Summary [0m
	┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
	┃[1m [0m[1mpath [0m[1m [0m┃[1m [0m[1mmodule [0m[1m [0m┃[1m [0m[1minputs [0m[1m [0m┃[1m [0m[1moutputs [0m[1m [0m┃[1m [0m[1mparams [0m[1m [0m┃
	┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
	│ │ DiT │ - [2mfloat32[0m[4,32,32,4] │ [2mbfloat16[0m[4,32,32,4] │ │
	│ │ │ - [2mfloat32[0m[1] │ │ │
	│ │ │ - [2mfloat32[0m[1] │ │ │
	│ │ │ - [2mint32[0m[1] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ PatchEmbed_0 │ PatchEmbed │ [2mfloat32[0m[4,32,32,4] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ PatchEmbed_0/Conv_0 │ Conv │ [2mfloat32[0m[4,32,32,4] │ [2mbfloat16[0m[4,16,16,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[2,2,4,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m13,056 [0m[1;2m(52.2 KB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ TimestepEmbedder_0 │ TimestepEmbedder │ [2mfloat32[0m[1] │ [2mfloat32[0m[1,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ TimestepEmbedder_0/Dense_0 │ Dense │ [2mbfloat16[0m[1,256] │ [2mbfloat16[0m[1,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[256,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m197,376 [0m[1;2m(789.5 KB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ TimestepEmbedder_0/Dense_1 │ Dense │ [2mbfloat16[0m[1,768] │ [2mfloat32[0m[1,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ TimestepEmbedder_1 │ TimestepEmbedder │ [2mfloat32[0m[1] │ [2mfloat32[0m[1,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ TimestepEmbedder_1/Dense_0 │ Dense │ [2mbfloat16[0m[1,256] │ [2mbfloat16[0m[1,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[256,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m197,376 [0m[1;2m(789.5 KB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ TimestepEmbedder_1/Dense_1 │ Dense │ [2mbfloat16[0m[1,768] │ [2mfloat32[0m[1,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ LabelEmbedder_0 │ LabelEmbedder │ [2mint32[0m[1] │ [2mbfloat16[0m[1,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ LabelEmbedder_0/Embed_0 │ Embed │ [2mint32[0m[1] │ [2mbfloat16[0m[1,768] │ embedding: [2mfloat32[0m[1001,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m768,768 [0m[1;2m(3.1 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_0/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_1/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_2/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_3/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_4/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_5/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_6/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_7/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_8/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_9/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_10/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11 │ DiTBlock │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,4608] │ bias: [2mfloat32[0m[4608] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,4608] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m3,543,552 [0m[1;2m(14.2 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/Dense_2 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/Dense_3 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/Dense_4 │ Dense │ [2mfloat32[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m590,592 [0m[1;2m(2.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/LayerNorm_1 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/MlpBlock_0 │ MlpBlock │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/MlpBlock_0/Dense_0 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,3072] │ bias: [2mfloat32[0m[3072] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,3072] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,362,368 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/MlpBlock_0/Dropout_0 │ Dropout │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,3072] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/MlpBlock_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,3072] │ [2mbfloat16[0m[4,256,768] │ bias: [2mfloat32[0m[768] │
	│ │ │ │ │ kernel: [2mfloat32[0m[3072,768] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m2,360,064 [0m[1;2m(9.4 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ DiTBlock_11/MlpBlock_0/Dropout_1 │ Dropout │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ FinalLayer_0 │ FinalLayer │ - [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,16] │ │
	│ │ │ - [2mfloat32[0m[1,768] │ │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ FinalLayer_0/Dense_0 │ Dense │ [2mfloat32[0m[1,768] │ [2mbfloat16[0m[1,1536] │ bias: [2mfloat32[0m[1536] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,1536] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m1,181,184 [0m[1;2m(4.7 MB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ FinalLayer_0/LayerNorm_0 │ LayerNorm │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,768] │ │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ FinalLayer_0/Dense_1 │ Dense │ [2mbfloat16[0m[4,256,768] │ [2mbfloat16[0m[4,256,16] │ bias: [2mfloat32[0m[16] │
	│ │ │ │ │ kernel: [2mfloat32[0m[768,16] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m12,304 [0m[1;2m(49.2 KB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│ Embed_0 │ Embed │ [2mint32[0m[1] │ [2mfloat32[0m[1,1] │ embedding: [2mfloat32[0m[256,1] │
	│ │ │ │ │ │
	│ │ │ │ │ [1m256 [0m[1;2m(1.0 KB)[0m │
	├──────────────────────────────────┼──────────────────┼───────────────────────┼───────────────────────┼──────────────────────────────┤
	│[1m [0m[1m [0m[1m [0m│[1m [0m[1m [0m[1m [0m│[1m [0m[1m [0m[1m [0m│[1m [0m[1m Total[0m[1m [0m│[1m [0m[1m131,091,728 [0m[1;2m(524.4 MB)[0m[1m [0m[1m [0m│
	└──────────────────────────────────┴──────────────────┴───────────────────────┴───────────────────────┴──────────────────────────────┘
	[1m [0m
	[1m Total Parameters: 131,091,728 [0m[1;2m(524.4 MB)[0m[1m [0m


	DiT: Input of shape (4, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (4, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (4, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (1, 768) dtype float32
	Loaded checkpoint from 3912 seconds ago.

	parameter shapes:
	('PatchEmbed_0', 'Conv_0', 'kernel'): (2, 2, 4, 768)
	('PatchEmbed_0', 'Conv_0', 'bias'): (768,)
	('TimestepEmbedder_0', 'Dense_0', 'kernel'): (256, 768)
	('TimestepEmbedder_0', 'Dense_0', 'bias'): (768,)
	('TimestepEmbedder_0', 'Dense_1', 'kernel'): (768, 768)
	('TimestepEmbedder_0', 'Dense_1', 'bias'): (768,)
	('TimestepEmbedder_1', 'Dense_0', 'kernel'): (256, 768)
	('TimestepEmbedder_1', 'Dense_0', 'bias'): (768,)
	('TimestepEmbedder_1', 'Dense_1', 'kernel'): (768, 768)
	('TimestepEmbedder_1', 'Dense_1', 'bias'): (768,)
	('LabelEmbedder_0', 'Embed_0', 'embedding'): (1001, 768)
	('DiTBlock_0', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_0', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_0', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_0', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_0', 'Dense_2', 'bias'): (768,)
	('DiTBlock_0', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_0', 'Dense_3', 'bias'): (768,)
	('DiTBlock_0', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_0', 'Dense_4', 'bias'): (768,)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_1', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_1', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_1', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_1', 'Dense_1', 'bias'): (768,)
	('DiTBlock_1', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_1', 'Dense_2', 'bias'): (768,)
	('DiTBlock_1', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_1', 'Dense_3', 'bias'): (768,)
	('DiTBlock_1', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_1', 'Dense_4', 'bias'): (768,)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_2', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_2', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_2', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_2', 'Dense_1', 'bias'): (768,)
	('DiTBlock_2', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_2', 'Dense_2', 'bias'): (768,)
	('DiTBlock_2', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_2', 'Dense_3', 'bias'): (768,)
	('DiTBlock_2', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_2', 'Dense_4', 'bias'): (768,)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_3', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_3', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_3', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_3', 'Dense_1', 'bias'): (768,)
	('DiTBlock_3', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_3', 'Dense_2', 'bias'): (768,)
	('DiTBlock_3', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_3', 'Dense_3', 'bias'): (768,)
	('DiTBlock_3', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_3', 'Dense_4', 'bias'): (768,)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_4', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_4', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_4', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_4', 'Dense_1', 'bias'): (768,)
	('DiTBlock_4', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_4', 'Dense_2', 'bias'): (768,)
	('DiTBlock_4', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_4', 'Dense_3', 'bias'): (768,)
	('DiTBlock_4', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_4', 'Dense_4', 'bias'): (768,)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_5', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_5', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_5', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_5', 'Dense_1', 'bias'): (768,)
	('DiTBlock_5', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_5', 'Dense_2', 'bias'): (768,)
	('DiTBlock_5', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_5', 'Dense_3', 'bias'): (768,)
	('DiTBlock_5', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_5', 'Dense_4', 'bias'): (768,)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_6', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_6', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_6', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_6', 'Dense_1', 'bias'): (768,)
	('DiTBlock_6', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_6', 'Dense_2', 'bias'): (768,)
	('DiTBlock_6', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_6', 'Dense_3', 'bias'): (768,)
	('DiTBlock_6', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_6', 'Dense_4', 'bias'): (768,)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_7', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_7', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_7', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_7', 'Dense_1', 'bias'): (768,)
	('DiTBlock_7', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_7', 'Dense_2', 'bias'): (768,)
	('DiTBlock_7', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_7', 'Dense_3', 'bias'): (768,)
	('DiTBlock_7', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_7', 'Dense_4', 'bias'): (768,)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_8', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_8', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_8', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_8', 'Dense_1', 'bias'): (768,)
	('DiTBlock_8', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_8', 'Dense_2', 'bias'): (768,)
	('DiTBlock_8', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_8', 'Dense_3', 'bias'): (768,)
	('DiTBlock_8', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_8', 'Dense_4', 'bias'): (768,)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_9', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_9', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_9', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_9', 'Dense_1', 'bias'): (768,)
	('DiTBlock_9', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_9', 'Dense_2', 'bias'): (768,)
	('DiTBlock_9', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_9', 'Dense_3', 'bias'): (768,)
	('DiTBlock_9', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_9', 'Dense_4', 'bias'): (768,)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_10', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_10', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_10', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_10', 'Dense_1', 'bias'): (768,)
	('DiTBlock_10', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_10', 'Dense_2', 'bias'): (768,)
	('DiTBlock_10', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_10', 'Dense_3', 'bias'): (768,)
	('DiTBlock_10', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_10', 'Dense_4', 'bias'): (768,)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_11', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_11', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_11', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_11', 'Dense_1', 'bias'): (768,)
	('DiTBlock_11', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_11', 'Dense_2', 'bias'): (768,)
	('DiTBlock_11', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_11', 'Dense_3', 'bias'): (768,)
	('DiTBlock_11', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_11', 'Dense_4', 'bias'): (768,)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('FinalLayer_0', 'Dense_0', 'kernel'): (768, 1536)
	('FinalLayer_0', 'Dense_0', 'bias'): (1536,)
	('FinalLayer_0', 'Dense_1', 'kernel'): (768, 16)
	('FinalLayer_0', 'Dense_1', 'bias'): (16,)
	('Embed_0', 'embedding'): (256, 1)

	parameter shapes:
	('DiTBlock_0', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_0', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_1', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_1', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_1', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_10', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_10', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_10', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_11', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_11', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_11', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_2', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_2', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_2', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_3', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_3', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_3', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_4', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_4', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_4', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_5', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_5', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_5', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_6', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_6', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_6', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_7', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_7', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_7', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_8', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_8', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_8', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_9', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_9', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_9', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('Embed_0', 'embedding'): (1, 256, 1)
	('FinalLayer_0', 'Dense_0', 'bias'): (1, 1536)
	('FinalLayer_0', 'Dense_0', 'kernel'): (1, 768, 1536)
	('FinalLayer_0', 'Dense_1', 'bias'): (1, 16)
	('FinalLayer_0', 'Dense_1', 'kernel'): (1, 768, 16)
	('LabelEmbedder_0', 'Embed_0', 'embedding'): (1, 1001, 768)
	('PatchEmbed_0', 'Conv_0', 'bias'): (1, 768)
	('PatchEmbed_0', 'Conv_0', 'kernel'): (1, 2, 2, 4, 768)
	('TimestepEmbedder_0', 'Dense_0', 'bias'): (1, 768)
	('TimestepEmbedder_0', 'Dense_0', 'kernel'): (1, 256, 768)
	('TimestepEmbedder_0', 'Dense_1', 'bias'): (1, 768)
	('TimestepEmbedder_0', 'Dense_1', 'kernel'): (1, 768, 768)
	('TimestepEmbedder_1', 'Dense_0', 'bias'): (1, 768)
	('TimestepEmbedder_1', 'Dense_0', 'kernel'): (1, 256, 768)
	('TimestepEmbedder_1', 'Dense_1', 'bias'): (1, 768)
	('TimestepEmbedder_1', 'Dense_1', 'kernel'): (1, 768, 768)

	parameter shapes:
	('DiTBlock_0', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_0', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_1', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_1', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_1', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_10', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_10', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_10', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_11', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_11', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_11', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_2', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_2', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_2', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_3', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_3', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_3', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_4', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_4', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_4', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_5', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_5', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_5', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_6', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_6', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_6', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_7', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_7', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_7', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_8', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_8', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_8', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_9', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_9', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_9', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('Embed_0', 'embedding'): (1, 256, 1)
	('FinalLayer_0', 'Dense_0', 'bias'): (1, 1536)
	('FinalLayer_0', 'Dense_0', 'kernel'): (1, 768, 1536)
	('FinalLayer_0', 'Dense_1', 'bias'): (1, 16)
	('FinalLayer_0', 'Dense_1', 'kernel'): (1, 768, 16)
	('LabelEmbedder_0', 'Embed_0', 'embedding'): (1, 1001, 768)
	('PatchEmbed_0', 'Conv_0', 'bias'): (1, 768)
	('PatchEmbed_0', 'Conv_0', 'kernel'): (1, 2, 2, 4, 768)
	('TimestepEmbedder_0', 'Dense_0', 'bias'): (1, 768)
	('TimestepEmbedder_0', 'Dense_0', 'kernel'): (1, 256, 768)
	('TimestepEmbedder_0', 'Dense_1', 'bias'): (1, 768)
	('TimestepEmbedder_0', 'Dense_1', 'kernel'): (1, 768, 768)
	('TimestepEmbedder_1', 'Dense_0', 'bias'): (1, 768)
	('TimestepEmbedder_1', 'Dense_0', 'kernel'): (1, 256, 768)
	('TimestepEmbedder_1', 'Dense_1', 'bias'): (1, 768)
	('TimestepEmbedder_1', 'Dense_1', 'kernel'): (1, 768, 768)

	parameter shapes:
	('DiTBlock_0', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_0', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_1', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_1', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_1', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_10', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_10', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_10', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_11', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_11', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_11', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_2', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_2', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_2', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_3', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_3', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_3', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_4', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_4', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_4', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_5', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_5', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_5', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_6', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_6', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_6', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_7', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_7', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_7', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_8', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_8', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_8', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_9', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_9', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_9', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('Embed_0', 'embedding'): (1, 256, 1)
	('FinalLayer_0', 'Dense_0', 'bias'): (1, 1536)
	('FinalLayer_0', 'Dense_0', 'kernel'): (1, 768, 1536)
	('FinalLayer_0', 'Dense_1', 'bias'): (1, 16)
	('FinalLayer_0', 'Dense_1', 'kernel'): (1, 768, 16)
	('LabelEmbedder_0', 'Embed_0', 'embedding'): (1, 1001, 768)
	('PatchEmbed_0', 'Conv_0', 'bias'): (1, 768)
	('PatchEmbed_0', 'Conv_0', 'kernel'): (1, 2, 2, 4, 768)
	('TimestepEmbedder_0', 'Dense_0', 'bias'): (1, 768)
	('TimestepEmbedder_0', 'Dense_0', 'kernel'): (1, 256, 768)
	('TimestepEmbedder_0', 'Dense_1', 'bias'): (1, 768)
	('TimestepEmbedder_0', 'Dense_1', 'kernel'): (1, 768, 768)
	('TimestepEmbedder_1', 'Dense_0', 'bias'): (1, 768)
	('TimestepEmbedder_1', 'Dense_0', 'kernel'): (1, 256, 768)
	('TimestepEmbedder_1', 'Dense_1', 'bias'): (1, 768)
	('TimestepEmbedder_1', 'Dense_1', 'kernel'): (1, 768, 768)

	parameter shapes:
	('DiTBlock_0', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_0', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_0', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_1', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_1', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_1', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_1', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_10', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_10', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_10', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_10', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_11', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_11', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_11', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_11', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_2', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_2', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_2', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_2', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_3', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_3', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_3', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_3', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_4', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_4', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_4', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_4', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_5', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_5', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_5', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_5', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_6', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_6', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_6', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_6', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_7', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_7', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_7', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_7', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_8', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_8', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_8', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_8', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('DiTBlock_9', 'Dense_0', 'bias'): (1, 4608)
	('DiTBlock_9', 'Dense_0', 'kernel'): (1, 768, 4608)
	('DiTBlock_9', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_1', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_2', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_2', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_3', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_3', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'Dense_4', 'bias'): (1, 768)
	('DiTBlock_9', 'Dense_4', 'kernel'): (1, 768, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'bias'): (1, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'kernel'): (1, 768, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'bias'): (1, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'kernel'): (1, 3072, 768)
	('Embed_0', 'embedding'): (1, 256, 1)
	('FinalLayer_0', 'Dense_0', 'bias'): (1, 1536)
	('FinalLayer_0', 'Dense_0', 'kernel'): (1, 768, 1536)
	('FinalLayer_0', 'Dense_1', 'bias'): (1, 16)
	('FinalLayer_0', 'Dense_1', 'kernel'): (1, 768, 16)
	('LabelEmbedder_0', 'Embed_0', 'embedding'): (1, 1001, 768)
	('PatchEmbed_0', 'Conv_0', 'bias'): (1, 768)
	('PatchEmbed_0', 'Conv_0', 'kernel'): (1, 2, 2, 4, 768)
	('TimestepEmbedder_0', 'Dense_0', 'bias'): (1, 768)
	('TimestepEmbedder_0', 'Dense_0', 'kernel'): (1, 256, 768)
	('TimestepEmbedder_0', 'Dense_1', 'bias'): (1, 768)
	('TimestepEmbedder_0', 'Dense_1', 'kernel'): (1, 768, 768)
	('TimestepEmbedder_1', 'Dense_0', 'bias'): (1, 768)
	('TimestepEmbedder_1', 'Dense_0', 'kernel'): (1, 256, 768)
	('TimestepEmbedder_1', 'Dense_1', 'bias'): (1, 768)
	('TimestepEmbedder_1', 'Dense_1', 'kernel'): (1, 768, 768)

	parameter shapes:
	('DiTBlock_0', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_0', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_0', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_0', 'Dense_2', 'bias'): (768,)
	('DiTBlock_0', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_0', 'Dense_3', 'bias'): (768,)
	('DiTBlock_0', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_0', 'Dense_4', 'bias'): (768,)
	('DiTBlock_0', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_0', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_1', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_1', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_1', 'Dense_1', 'bias'): (768,)
	('DiTBlock_1', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_1', 'Dense_2', 'bias'): (768,)
	('DiTBlock_1', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_1', 'Dense_3', 'bias'): (768,)
	('DiTBlock_1', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_1', 'Dense_4', 'bias'): (768,)
	('DiTBlock_1', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_1', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_10', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_10', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_10', 'Dense_1', 'bias'): (768,)
	('DiTBlock_10', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_10', 'Dense_2', 'bias'): (768,)
	('DiTBlock_10', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_10', 'Dense_3', 'bias'): (768,)
	('DiTBlock_10', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_10', 'Dense_4', 'bias'): (768,)
	('DiTBlock_10', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_10', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_11', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_11', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_11', 'Dense_1', 'bias'): (768,)
	('DiTBlock_11', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_11', 'Dense_2', 'bias'): (768,)
	('DiTBlock_11', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_11', 'Dense_3', 'bias'): (768,)
	('DiTBlock_11', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_11', 'Dense_4', 'bias'): (768,)
	('DiTBlock_11', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_11', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_2', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_2', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_2', 'Dense_1', 'bias'): (768,)
	('DiTBlock_2', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_2', 'Dense_2', 'bias'): (768,)
	('DiTBlock_2', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_2', 'Dense_3', 'bias'): (768,)
	('DiTBlock_2', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_2', 'Dense_4', 'bias'): (768,)
	('DiTBlock_2', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_2', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_3', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_3', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_3', 'Dense_1', 'bias'): (768,)
	('DiTBlock_3', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_3', 'Dense_2', 'bias'): (768,)
	('DiTBlock_3', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_3', 'Dense_3', 'bias'): (768,)
	('DiTBlock_3', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_3', 'Dense_4', 'bias'): (768,)
	('DiTBlock_3', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_3', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_4', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_4', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_4', 'Dense_1', 'bias'): (768,)
	('DiTBlock_4', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_4', 'Dense_2', 'bias'): (768,)
	('DiTBlock_4', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_4', 'Dense_3', 'bias'): (768,)
	('DiTBlock_4', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_4', 'Dense_4', 'bias'): (768,)
	('DiTBlock_4', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_4', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_5', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_5', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_5', 'Dense_1', 'bias'): (768,)
	('DiTBlock_5', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_5', 'Dense_2', 'bias'): (768,)
	('DiTBlock_5', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_5', 'Dense_3', 'bias'): (768,)
	('DiTBlock_5', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_5', 'Dense_4', 'bias'): (768,)
	('DiTBlock_5', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_5', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_6', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_6', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_6', 'Dense_1', 'bias'): (768,)
	('DiTBlock_6', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_6', 'Dense_2', 'bias'): (768,)
	('DiTBlock_6', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_6', 'Dense_3', 'bias'): (768,)
	('DiTBlock_6', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_6', 'Dense_4', 'bias'): (768,)
	('DiTBlock_6', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_6', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_7', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_7', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_7', 'Dense_1', 'bias'): (768,)
	('DiTBlock_7', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_7', 'Dense_2', 'bias'): (768,)
	('DiTBlock_7', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_7', 'Dense_3', 'bias'): (768,)
	('DiTBlock_7', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_7', 'Dense_4', 'bias'): (768,)
	('DiTBlock_7', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_7', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_8', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_8', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_8', 'Dense_1', 'bias'): (768,)
	('DiTBlock_8', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_8', 'Dense_2', 'bias'): (768,)
	('DiTBlock_8', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_8', 'Dense_3', 'bias'): (768,)
	('DiTBlock_8', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_8', 'Dense_4', 'bias'): (768,)
	('DiTBlock_8', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_8', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('DiTBlock_9', 'Dense_0', 'bias'): (4608,)
	('DiTBlock_9', 'Dense_0', 'kernel'): (768, 4608)
	('DiTBlock_9', 'Dense_1', 'bias'): (768,)
	('DiTBlock_9', 'Dense_1', 'kernel'): (768, 768)
	('DiTBlock_9', 'Dense_2', 'bias'): (768,)
	('DiTBlock_9', 'Dense_2', 'kernel'): (768, 768)
	('DiTBlock_9', 'Dense_3', 'bias'): (768,)
	('DiTBlock_9', 'Dense_3', 'kernel'): (768, 768)
	('DiTBlock_9', 'Dense_4', 'bias'): (768,)
	('DiTBlock_9', 'Dense_4', 'kernel'): (768, 768)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'bias'): (3072,)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_0', 'kernel'): (768, 3072)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'bias'): (768,)
	('DiTBlock_9', 'MlpBlock_0', 'Dense_1', 'kernel'): (3072, 768)
	('Embed_0', 'embedding'): (256, 1)
	('FinalLayer_0', 'Dense_0', 'bias'): (1536,)
	('FinalLayer_0', 'Dense_0', 'kernel'): (768, 1536)
	('FinalLayer_0', 'Dense_1', 'bias'): (16,)
	('FinalLayer_0', 'Dense_1', 'kernel'): (768, 16)
	('LabelEmbedder_0', 'Embed_0', 'embedding'): (1001, 768)
	('PatchEmbed_0', 'Conv_0', 'bias'): (768,)
	('PatchEmbed_0', 'Conv_0', 'kernel'): (2, 2, 4, 768)
	('TimestepEmbedder_0', 'Dense_0', 'bias'): (768,)
	('TimestepEmbedder_0', 'Dense_0', 'kernel'): (256, 768)
	('TimestepEmbedder_0', 'Dense_1', 'bias'): (768,)
	('TimestepEmbedder_0', 'Dense_1', 'kernel'): (768, 768)
	('TimestepEmbedder_1', 'Dense_0', 'bias'): (768,)
	('TimestepEmbedder_1', 'Dense_0', 'kernel'): (256, 768)
	('TimestepEmbedder_1', 'Dense_1', 'bias'): (768,)
	('TimestepEmbedder_1', 'Dense_1', 'kernel'): (768, 768)
	┌────────────────────────────────────────────────┐
	│ │
	│ │
	│ │
	│ │
	│ TPU 0,1,2,3 │
	│ │
	│ │
	│ │
	│ │
	└────────────────────────────────────────────────┘
	┌─────────────────────────────────────────────────────────────────────────┐
	│ │
	│ │
	│ │
	│ │
	│ TPU 0,1,2,3 │
	│ │
	│ │
	│ │
	│ │
	└─────────────────────────────────────────────────────────────────────────┘
	doing the else
	(512, 256, 256, 3)
	encode image shape (128, 256, 256, 3)
	Initializing encoder.
	Incoming encoder shape (128, 256, 256, 3)
	Encoder layer (128, 256, 256, 128)
	doing downsample
	Encoder layer (128, 128, 128, 128)
	doing downsample
	Encoder layer (128, 64, 64, 256)
	doing downsample
	Encoder layer (128, 32, 32, 512)
	Encoder layer (128, 32, 32, 512)
	Encoder layer final (128, 32, 32, 512)
	Encoder layer final (128, 32, 32, 512)
	Final embeddings are size (128, 32, 32, 8)
	After quant (128, 32, 32, 4)
	Calc FID for CFG 1.0 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	z_vectors shape (128, 32, 32, 4)
	Decoder incoming shape (128, 32, 32, 4)
	Decoder input (128, 32, 32, 512)
	Mid Block Decoder layer (128, 32, 32, 512)
	Mid Block Decoder layer (128, 32, 32, 512)
	Decoder layer (128, 64, 64, 512)
	Decoder layer (128, 128, 128, 512)
	Decoder layer (128, 256, 256, 256)
	Decoder layer (128, 256, 256, 128)
	FID is 35.31022644042969
	(512, 256, 256, 3)
	Calc FID for CFG 1.0 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 36.25322723388672
	(512, 256, 256, 3)
	Calc FID for CFG 1.0 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 39.04065704345703
	(512, 256, 256, 3)
	Calc FID for CFG 1.0 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 47.8662109375
	(512, 256, 256, 3)
	Calc FID for CFG 1.0 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 79.06202697753906
	(512, 256, 256, 3)
	Calc FID for CFG 1.0 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 205.282470703125
	(512, 256, 256, 3)
	Calc FID for CFG 1.0 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 366.40966796875
	(512, 256, 256, 3)
	Calc FID for CFG 1.0 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 260.6976013183594
	(512, 256, 256, 3)
	Calc FID for CFG 1.25 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 21.369884490966797
	(512, 256, 256, 3)
	Calc FID for CFG 1.25 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 22.148216247558594
	(512, 256, 256, 3)
	Calc FID for CFG 1.25 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 24.354700088500977
	(512, 256, 256, 3)
	Calc FID for CFG 1.25 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 31.724349975585938
	(512, 256, 256, 3)
	Calc FID for CFG 1.25 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 58.99041748046875
	(512, 256, 256, 3)
	Calc FID for CFG 1.25 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 170.36500549316406
	(512, 256, 256, 3)
	Calc FID for CFG 1.25 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 345.7372131347656
	(512, 256, 256, 3)
	Calc FID for CFG 1.25 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 250.92877197265625
	(512, 256, 256, 3)
	Calc FID for CFG 1.5 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 13.394742965698242
	(512, 256, 256, 3)
	Calc FID for CFG 1.5 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 13.958024978637695
	(512, 256, 256, 3)
	Calc FID for CFG 1.5 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 15.560650825500488
	(512, 256, 256, 3)
	Calc FID for CFG 1.5 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 21.029720306396484
	(512, 256, 256, 3)
	Calc FID for CFG 1.5 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 42.93667221069336
	(512, 256, 256, 3)
	Calc FID for CFG 1.5 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 140.39520263671875
	(512, 256, 256, 3)
	Calc FID for CFG 1.5 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 326.5361633300781
	(512, 256, 256, 3)
	Calc FID for CFG 1.5 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 244.94207763671875
	(512, 256, 256, 3)
	Calc FID for CFG 1.75 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.423892974853516
	(512, 256, 256, 3)
	Calc FID for CFG 1.75 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.777412414550781
	(512, 256, 256, 3)
	Calc FID for CFG 1.75 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 10.83847713470459
	(512, 256, 256, 3)
	Calc FID for CFG 1.75 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 14.639281272888184
	(512, 256, 256, 3)
	Calc FID for CFG 1.75 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 31.432449340820312
	(512, 256, 256, 3)
	Calc FID for CFG 1.75 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 115.02278900146484
	(512, 256, 256, 3)
	Calc FID for CFG 1.75 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 309.41192626953125
	(512, 256, 256, 3)
	Calc FID for CFG 1.75 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 241.01193237304688
	(512, 256, 256, 3)
	Calc FID for CFG 2.0 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 7.828547954559326
	(512, 256, 256, 3)
	Calc FID for CFG 2.0 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 8.003972053527832
	(512, 256, 256, 3)
	Calc FID for CFG 2.0 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 8.634432792663574
	(512, 256, 256, 3)
	Calc FID for CFG 2.0 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 11.16789722442627
	(512, 256, 256, 3)
	Calc FID for CFG 2.0 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 23.635202407836914
	(512, 256, 256, 3)
	Calc FID for CFG 2.0 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 94.17955017089844
	(512, 256, 256, 3)
	Calc FID for CFG 2.0 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 294.5157775878906
	(512, 256, 256, 3)
	Calc FID for CFG 2.0 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 238.18911743164062
	(512, 256, 256, 3)
	Calc FID for CFG 2.25 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 7.5738983154296875
	(512, 256, 256, 3)
	Calc FID for CFG 2.25 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 7.647280216217041
	(512, 256, 256, 3)
	Calc FID for CFG 2.25 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 7.974250316619873
	(512, 256, 256, 3)
	Calc FID for CFG 2.25 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.564567565917969
	(512, 256, 256, 3)
	Calc FID for CFG 2.25 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 18.56076431274414
	(512, 256, 256, 3)
	Calc FID for CFG 2.25 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 77.56942749023438
	(512, 256, 256, 3)
	Calc FID for CFG 2.25 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 281.5552978515625
	(512, 256, 256, 3)
	Calc FID for CFG 2.25 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 235.73397827148438
	(512, 256, 256, 3)
	Calc FID for CFG 2.5 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 8.044367790222168
	(512, 256, 256, 3)
	Calc FID for CFG 2.5 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 8.0531644821167
	(512, 256, 256, 3)
	Calc FID for CFG 2.5 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 8.165743827819824
	(512, 256, 256, 3)
	Calc FID for CFG 2.5 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.1002197265625
	(512, 256, 256, 3)
	Calc FID for CFG 2.5 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 15.491735458374023
	(512, 256, 256, 3)
	Calc FID for CFG 2.5 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 64.42039489746094
	(512, 256, 256, 3)
	Calc FID for CFG 2.5 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 270.5625915527344
	(512, 256, 256, 3)
	Calc FID for CFG 2.5 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 233.64608764648438
	(512, 256, 256, 3)
	Calc FID for CFG 2.75 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 8.906791687011719
	(512, 256, 256, 3)
	Calc FID for CFG 2.75 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 8.859354972839355
	(512, 256, 256, 3)
	Calc FID for CFG 2.75 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 8.847463607788086
	(512, 256, 256, 3)
	Calc FID for CFG 2.75 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.30807876586914
	(512, 256, 256, 3)
	Calc FID for CFG 2.75 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 13.719435691833496
	(512, 256, 256, 3)
	Calc FID for CFG 2.75 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 54.147682189941406
	(512, 256, 256, 3)
	Calc FID for CFG 2.75 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 261.23638916015625
	(512, 256, 256, 3)
	Calc FID for CFG 2.75 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 232.02645874023438
	(512, 256, 256, 3)
	Calc FID for CFG 3.0 and denoise_timesteps 128
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.92387580871582
	(512, 256, 256, 3)
	Calc FID for CFG 3.0 and denoise_timesteps 64
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.84957504272461
	(512, 256, 256, 3)
	Calc FID for CFG 3.0 and denoise_timesteps 32
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.755224227905273
	(512, 256, 256, 3)
	Calc FID for CFG 3.0 and denoise_timesteps 16
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 9.908406257629395
	(512, 256, 256, 3)
	Calc FID for CFG 3.0 and denoise_timesteps 8
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 12.787176132202148
	(512, 256, 256, 3)
	Calc FID for CFG 3.0 and denoise_timesteps 4
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 46.10810470581055
	(512, 256, 256, 3)
	Calc FID for CFG 3.0 and denoise_timesteps 2
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 253.41326904296875
	(512, 256, 256, 3)
	Calc FID for CFG 3.0 and denoise_timesteps 1
	DiT: Input of shape (512, 32, 32, 4) dtype float32
	DiT: After patch embed, shape is (512, 256, 768) dtype bfloat16
	DiT: Patch Embed of shape (512, 256, 768) dtype bfloat16
	DiT: Conditioning of shape (512, 768) dtype float32
	FID is 230.6085205078125
	[1;34mwandb[0m:
	[1;34mwandb[0m: 🚀 View run [33mshortcut_imagenet256[0m at: [34mhttps://wandb.ai/daniel-z-kaplan/shortcut/runs/shortcut_imagenet256_20250814_122245_345353_10[0m
	[1;34mwandb[0m: Find logs at: [1;35m../../../tmp/tmp57xxkh9z/wandb/run-20250814_122245-shortcut_imagenet256_20250814_122245_345353_10/logs[0m