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Starting rank=0, seed=0, world_size=1.
CDiT(
(x_embedder): PatchEmbed(
(proj): Conv2d(4, 1152, kernel_size=(2, 2), stride=(2, 2))
(norm): Identity()
)
(t_embedder): TimestepEmbedder(
(mlp): Sequential(
(0): Linear(in_features=256, out_features=1152, bias=True)
(1): SiLU()
(2): Linear(in_features=1152, out_features=1152, bias=True)
)
)
(y_embedder): ActionEmbedder(
(x_emb): TimestepEmbedder(
(mlp): Sequential(
(0): Linear(in_features=256, out_features=384, bias=True)
(1): SiLU()
(2): Linear(in_features=384, out_features=384, bias=True)
)
)
(y_emb): TimestepEmbedder(
(mlp): Sequential(
(0): Linear(in_features=256, out_features=384, bias=True)
(1): SiLU()
(2): Linear(in_features=384, out_features=384, bias=True)
)
)
(angle_emb): TimestepEmbedder(
(mlp): Sequential(
(0): Linear(in_features=256, out_features=384, bias=True)
(1): SiLU()
(2): Linear(in_features=384, out_features=384, bias=True)
)
)
)
(blocks): ModuleList(
(0-27): 28 x CDiTBlock(
(norm1): LayerNorm((1152,), eps=1e-06, elementwise_affine=False)
(attn): Attention(
(qkv): Linear(in_features=1152, out_features=3456, bias=True)
(q_norm): Identity()
(k_norm): Identity()
(attn_drop): Dropout(p=0.0, inplace=False)
(proj): Linear(in_features=1152, out_features=1152, bias=True)
(proj_drop): Dropout(p=0.0, inplace=False)
)
(norm2): LayerNorm((1152,), eps=1e-06, elementwise_affine=False)
(norm_cond): LayerNorm((1152,), eps=1e-06, elementwise_affine=False)
(cttn): MultiheadAttention(
(out_proj): NonDynamicallyQuantizableLinear(in_features=1152, out_features=1152, bias=True)
)
(adaLN_modulation): Sequential(
(0): SiLU()
(1): Linear(in_features=1152, out_features=12672, bias=True)
)
(norm3): LayerNorm((1152,), eps=1e-06, elementwise_affine=False)
(mlp): Mlp(
(fc1): Linear(in_features=1152, out_features=4608, bias=True)
(act): GELU(approximate='tanh')
(drop1): Dropout(p=0, inplace=False)
(norm): Identity()
(fc2): Linear(in_features=4608, out_features=1152, bias=True)
(drop2): Dropout(p=0, inplace=False)
)
)
)
(final_layer): FinalLayer(
(norm_final): LayerNorm((1152,), eps=1e-06, elementwise_affine=False)
(linear): Linear(in_features=1152, out_features=32, bias=True)
(adaLN_modulation): Sequential(
(0): SiLU()
(1): Linear(in_features=1152, out_features=2304, bias=True)
)
)
(time_embedder): TimestepEmbedder(
(mlp): Sequential(
(0): Linear(in_features=256, out_features=1152, bias=True)
(1): SiLU()
(2): Linear(in_features=1152, out_features=1152, bias=True)
)
)
)
Searching for model from logs/cdit_debug/checkpoints
****** Evaluating from NON PREDEFINED index... ******
Dataset: wuhan (train), size: 18652
****** Evaluating from NON PREDEFINED index... ******
Dataset: wuhan (test), size: 4502
****** Evaluating from NON PREDEFINED index... ******
Dataset: wuhan_auto (train), size: 17706
****** Evaluating from NON PREDEFINED index... ******
Dataset: wuhan_auto (test), size: 4235
Combining 2 datasets.
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