I got no device found error when trying to run on a single gpu H100.
CUDA_VISIBLE_DEVICES=0 python test.py --img_dir '/opt/data/private/LV_Dataset/DiffGLV-Test-All/RealPhoto60/LQ' --save_dir ./results-Q --SUPIR_sign Q --upscale 2
`Namespace(SUPIR_sign='F', a_prompt='Cinematic, High Contrast, highly detailed, taken using a Canon EOS R camera, hyper detailed photo - realistic maximum detail, 32k, Color Grading, ultra HD, extreme meticulous detailing, skin pore detailing, hyper sharpness, perfect without deformations.', ae_dtype='bf16', color_fix_type='Wavelet', diff_dtype='fp16', edm_steps=50, img_dir='/workspace/SUPIR_data', linear_CFG=True, linear_s_stage2=False, min_size=1024, n_prompt='painting, oil painting, illustration, drawing, art, sketch, oil painting, cartoon, CG Style, 3D render, unreal engine, blurring, dirty, messy, worst quality, low quality, frames, watermark, signature, jpeg artifacts, deformed, lowres, over-smooth', no_llava=False, num_samples=1, s_cfg=4.0, s_churn=5, s_noise=1.003, s_stage1=-1, s_stage2=1.0, save_dir='./results-F', seed=1234, spt_linear_CFG=1.0, spt_linear_s_stage2=0.0, upscale=2)
Building a Downsample layer with 2 dims.
--> settings are:
in-chn: 320, out-chn: 320, kernel-size: 3, stride: 2, padding: 1
constructing SpatialTransformer of depth 2 w/ 640 channels and 10 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 2. Setting context_dim to [2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 2 w/ 640 channels and 10 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 2. Setting context_dim to [2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Building a Downsample layer with 2 dims.
--> settings are:
in-chn: 640, out-chn: 640, kernel-size: 3, stride: 2, padding: 1
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 2 w/ 640 channels and 10 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 2. Setting context_dim to [2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 2 w/ 640 channels and 10 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 2. Setting context_dim to [2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 2 w/ 640 channels and 10 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 2. Setting context_dim to [2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 640 and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 320 and using 10 heads with a dimension of 64.
Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPTextModel: ['vision_model.encoder.layers.10.self_attn.v_proj.bias', 'vision_model.encoder.layers.10.layer_norm1.bias', 'vision_model.encoder.layers.0.self_attn.k_proj.weight', 'vision_model.pre_layrnorm.weight', 'vision_model.pre_layrnorm.bias', 'vision_model.encoder.layers.10.layer_norm1.weight', 'vision_model.encoder.layers.20.self_attn.v_proj.weight', 'vision_model.encoder.layers.19.mlp.fc1.bias', 'vision_model.encoder.layers.5.layer_norm2.bias', 'vision_model.encoder.layers.1.self_attn.v_proj.weight', 'vision_model.encoder.layers.2.mlp.fc2.bias', 'vision_model.encoder.layers.16.self_attn.k_proj.weight', 'vision_model.encoder.layers.22.mlp.fc1.weight', 'vision_model.encoder.layers.21.self_attn.v_proj.weight', 'vision_model.encoder.layers.11.mlp.fc2.weight', 'vision_model.encoder.layers.9.mlp.fc1.weight', 'vision_model.encoder.layers.9.self_attn.out_proj.bias', 'vision_model.encoder.layers.6.self_attn.k_proj.weight', 'vision_model.encoder.layers.5.layer_norm1.bias', 'vision_model.encoder.layers.2.mlp.fc1.weight', 'vision_model.encoder.layers.16.self_attn.out_proj.bias', 'vision_model.encoder.layers.9.layer_norm1.weight', 'vision_model.encoder.layers.1.mlp.fc2.bias', 'vision_model.encoder.layers.10.layer_norm2.weight', 'vision_model.encoder.layers.12.self_attn.v_proj.bias', 'vision_model.encoder.layers.12.layer_norm2.bias', 'vision_model.encoder.layers.12.self_attn.q_proj.bias', 'vision_model.encoder.layers.15.mlp.fc1.weight', 'vision_model.encoder.layers.2.layer_norm2.bias', 'vision_model.encoder.layers.10.mlp.fc1.bias', 'vision_model.encoder.layers.17.mlp.fc2.bias', 'vision_model.encoder.layers.7.self_attn.k_proj.bias', 'vision_model.encoder.layers.11.layer_norm1.weight', 'vision_model.encoder.layers.2.self_attn.k_proj.weight', 'vision_model.encoder.layers.3.mlp.fc1.bias', 'vision_model.encoder.layers.1.layer_norm1.weight', 'vision_model.encoder.layers.9.self_attn.v_proj.bias', 'vision_model.encoder.layers.23.self_attn.out_proj.bias', 'vision_model.encoder.layers.7.self_attn.v_proj.bias', 'vision_model.encoder.layers.17.layer_norm2.bias', 'vision_model.encoder.layers.7.mlp.fc1.weight', 'vision_model.encoder.layers.17.mlp.fc1.weight', 'vision_model.encoder.layers.0.layer_norm2.weight', 'vision_model.encoder.layers.9.self_attn.q_proj.weight', 'vision_model.encoder.layers.14.mlp.fc1.bias', 'vision_model.encoder.layers.13.layer_norm1.bias', 'vision_model.encoder.layers.1.layer_norm2.bias', 'vision_model.encoder.layers.0.mlp.fc2.weight', 'vision_model.encoder.layers.3.self_attn.k_proj.weight', 'vision_model.encoder.layers.4.self_attn.out_proj.weight', 'vision_model.encoder.layers.19.self_attn.out_proj.weight', 'vision_model.encoder.layers.21.self_attn.k_proj.bias', 'vision_model.encoder.layers.6.self_attn.q_proj.bias', 'vision_model.encoder.layers.21.layer_norm1.weight', 'vision_model.encoder.layers.2.mlp.fc1.bias', 'vision_model.encoder.layers.13.mlp.fc2.bias', 'vision_model.encoder.layers.17.self_attn.q_proj.weight', 'vision_model.encoder.layers.0.layer_norm1.bias', 'vision_model.encoder.layers.1.mlp.fc1.weight', 'vision_model.encoder.layers.15.mlp.fc2.weight', 'vision_model.encoder.layers.21.mlp.fc2.bias', 'vision_model.encoder.layers.15.self_attn.k_proj.bias', 'vision_model.encoder.layers.0.self_attn.k_proj.bias', 'vision_model.encoder.layers.11.self_attn.k_proj.bias', 'vision_model.encoder.layers.14.self_attn.q_proj.weight', 'vision_model.encoder.layers.22.self_attn.k_proj.bias', 'vision_model.encoder.layers.22.self_attn.q_proj.weight', 'vision_model.encoder.layers.14.layer_norm2.weight', 'vision_model.encoder.layers.19.self_attn.out_proj.bias', 'vision_model.encoder.layers.17.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.mlp.fc1.weight', 'vision_model.encoder.layers.22.self_attn.out_proj.bias', 'vision_model.encoder.layers.1.self_attn.v_proj.bias', 'vision_model.encoder.layers.18.self_attn.v_proj.bias', 'vision_model.encoder.layers.4.layer_norm2.bias', 'vision_model.encoder.layers.3.mlp.fc2.bias', 'vision_model.encoder.layers.4.self_attn.v_proj.bias', 'vision_model.encoder.layers.14.self_attn.out_proj.bias', 'vision_model.encoder.layers.8.self_attn.q_proj.weight', 'vision_model.encoder.layers.20.self_attn.k_proj.weight', 'vision_model.encoder.layers.6.layer_norm1.bias', 'vision_model.encoder.layers.7.layer_norm2.weight', 'vision_model.encoder.layers.21.layer_norm1.bias', 'vision_model.encoder.layers.8.mlp.fc2.bias', 'vision_model.encoder.layers.11.layer_norm1.bias', 'vision_model.encoder.layers.19.self_attn.v_proj.weight', 'vision_model.encoder.layers.8.layer_norm2.bias', 'vision_model.encoder.layers.16.mlp.fc2.bias', 'vision_model.encoder.layers.19.mlp.fc2.bias', 'vision_model.post_layernorm.bias', 'vision_model.encoder.layers.11.mlp.fc2.bias', 'vision_model.encoder.layers.23.layer_norm2.weight', 'vision_model.encoder.layers.20.self_attn.v_proj.bias', 'vision_model.encoder.layers.8.self_attn.k_proj.bias', 'vision_model.encoder.layers.13.self_attn.out_proj.weight', 'vision_model.encoder.layers.3.self_attn.v_proj.bias', 'vision_model.encoder.layers.19.layer_norm2.weight', 'vision_model.encoder.layers.20.mlp.fc2.weight', 'vision_model.encoder.layers.1.self_attn.k_proj.weight', 'vision_model.encoder.layers.0.mlp.fc1.bias', 'vision_model.encoder.layers.5.self_attn.out_proj.weight', 'vision_model.encoder.layers.17.layer_norm2.weight', 'vision_model.encoder.layers.7.layer_norm2.bias', 'vision_model.encoder.layers.12.layer_norm1.bias', 'vision_model.encoder.layers.5.mlp.fc2.bias', 'vision_model.encoder.layers.9.self_attn.q_proj.bias', 'vision_model.encoder.layers.8.layer_norm1.weight', 'vision_model.encoder.layers.19.self_attn.q_proj.weight', 'vision_model.encoder.layers.16.self_attn.out_proj.weight', 'text_projection.weight', 'vision_model.encoder.layers.8.layer_norm2.weight', 'vision_model.encoder.layers.17.self_attn.k_proj.bias', 'vision_model.encoder.layers.19.self_attn.q_proj.bias', 'vision_model.encoder.layers.14.mlp.fc2.weight', 'vision_model.encoder.layers.11.layer_norm2.bias', 'vision_model.encoder.layers.8.mlp.fc1.weight', 'vision_model.encoder.layers.22.layer_norm1.bias', 'vision_model.encoder.layers.5.self_attn.k_proj.weight', 'vision_model.encoder.layers.5.self_attn.v_proj.weight', 'vision_model.encoder.layers.7.self_attn.out_proj.weight', 'vision_model.encoder.layers.20.self_attn.q_proj.weight', 'vision_model.encoder.layers.2.self_attn.q_proj.bias', 'vision_model.encoder.layers.7.self_attn.q_proj.weight', 'vision_model.encoder.layers.8.layer_norm1.bias', 'vision_model.encoder.layers.5.mlp.fc1.bias', 'vision_model.encoder.layers.1.self_attn.q_proj.weight', 'vision_model.encoder.layers.5.self_attn.v_proj.bias', 'vision_model.encoder.layers.3.self_attn.q_proj.weight', 'vision_model.encoder.layers.21.self_attn.k_proj.weight', 'vision_model.encoder.layers.5.layer_norm1.weight', 'vision_model.encoder.layers.15.mlp.fc2.bias', 'vision_model.encoder.layers.17.self_attn.q_proj.bias', 'vision_model.encoder.layers.1.self_attn.out_proj.bias', 'vision_model.encoder.layers.16.layer_norm2.bias', 'vision_model.encoder.layers.9.mlp.fc1.bias', 'vision_model.encoder.layers.10.self_attn.out_proj.weight', 'vision_model.encoder.layers.12.self_attn.k_proj.bias', 'vision_model.encoder.layers.8.self_attn.v_proj.weight', 'vision_model.encoder.layers.16.self_attn.v_proj.weight', 'vision_model.encoder.layers.18.self_attn.k_proj.bias', 'vision_model.encoder.layers.17.mlp.fc1.bias', 'vision_model.encoder.layers.20.self_attn.q_proj.bias', 'vision_model.encoder.layers.8.self_attn.out_proj.weight', 'vision_model.encoder.layers.0.self_attn.out_proj.bias', 'vision_model.encoder.layers.4.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.mlp.fc2.weight', 'vision_model.encoder.layers.10.self_attn.out_proj.bias', 'vision_model.encoder.layers.1.mlp.fc1.bias', 'vision_model.encoder.layers.15.self_attn.v_proj.weight', 'vision_model.encoder.layers.6.mlp.fc2.weight', 'vision_model.encoder.layers.18.self_attn.q_proj.weight', 'vision_model.encoder.layers.14.layer_norm1.weight', 'vision_model.encoder.layers.7.layer_norm1.weight', 'vision_model.encoder.layers.22.self_attn.out_proj.weight', 'vision_model.encoder.layers.9.layer_norm2.bias', 'vision_model.encoder.layers.2.self_attn.v_proj.weight', 'vision_model.encoder.layers.14.self_attn.v_proj.bias', 'vision_model.encoder.layers.23.layer_norm2.bias', 'vision_model.encoder.layers.11.self_attn.v_proj.weight', 'vision_model.encoder.layers.23.self_attn.q_proj.bias', 'vision_model.encoder.layers.9.self_attn.out_proj.weight', 'vision_model.encoder.layers.3.mlp.fc1.weight', 'vision_model.encoder.layers.18.mlp.fc2.weight', 'vision_model.encoder.layers.12.self_attn.q_proj.weight', 'vision_model.encoder.layers.1.self_attn.q_proj.bias', 'vision_model.encoder.layers.9.self_attn.k_proj.weight', 'vision_model.encoder.layers.9.mlp.fc2.weight', 'vision_model.encoder.layers.3.layer_norm1.bias', 'vision_model.embeddings.position_embedding.weight', 'vision_model.encoder.layers.1.mlp.fc2.weight', 'vision_model.encoder.layers.21.mlp.fc1.bias', 'vision_model.encoder.layers.12.self_attn.out_proj.bias', 'vision_model.encoder.layers.0.mlp.fc1.weight', 'vision_model.encoder.layers.13.layer_norm2.bias', 'vision_model.encoder.layers.2.self_attn.out_proj.bias', 'vision_model.encoder.layers.0.self_attn.q_proj.bias', 'vision_model.encoder.layers.10.mlp.fc2.weight', 'vision_model.encoder.layers.20.self_attn.out_proj.bias', 'vision_model.encoder.layers.23.mlp.fc2.weight', 'vision_model.encoder.layers.3.self_attn.k_proj.bias', 'vision_model.encoder.layers.4.self_attn.k_proj.bias', 'vision_model.encoder.layers.15.self_attn.out_proj.weight', 'vision_model.encoder.layers.4.mlp.fc2.bias', 'vision_model.encoder.layers.5.mlp.fc2.weight', 'vision_model.encoder.layers.14.self_attn.v_proj.weight', 'vision_model.encoder.layers.23.mlp.fc1.weight', 'vision_model.encoder.layers.3.self_attn.v_proj.weight', 'vision_model.encoder.layers.18.mlp.fc1.weight', 'vision_model.encoder.layers.12.self_attn.v_proj.weight', 'vision_model.encoder.layers.23.self_attn.k_proj.bias', 'vision_model.encoder.layers.23.mlp.fc2.bias', 'vision_model.encoder.layers.12.mlp.fc2.bias', 'vision_model.encoder.layers.2.layer_norm1.weight', 'vision_model.encoder.layers.23.layer_norm1.bias', 'vision_model.encoder.layers.16.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.mlp.fc2.weight', 'vision_model.encoder.layers.6.self_attn.q_proj.weight', 'vision_model.encoder.layers.4.self_attn.out_proj.bias', 'vision_model.encoder.layers.14.self_attn.k_proj.weight', 'vision_model.encoder.layers.21.mlp.fc2.weight', 'vision_model.encoder.layers.22.layer_norm2.weight', 'vision_model.embeddings.position_ids', 'vision_model.encoder.layers.19.self_attn.v_proj.bias', 'vision_model.encoder.layers.21.self_attn.q_proj.bias', 'vision_model.encoder.layers.19.self_attn.k_proj.weight', 'vision_model.encoder.layers.15.self_attn.q_proj.weight', 'vision_model.encoder.layers.19.mlp.fc1.weight', 'vision_model.encoder.layers.1.self_attn.out_proj.weight', 'vision_model.encoder.layers.20.layer_norm2.weight', 'vision_model.encoder.layers.16.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.self_attn.k_proj.weight', 'vision_model.encoder.layers.16.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.mlp.fc1.weight', 'vision_model.encoder.layers.0.mlp.fc2.bias', 'vision_model.encoder.layers.17.layer_norm1.weight', 'vision_model.encoder.layers.10.mlp.fc1.weight', 'vision_model.encoder.layers.10.self_attn.v_proj.weight', 'vision_model.encoder.layers.2.mlp.fc2.weight', 'vision_model.encoder.layers.20.mlp.fc1.bias', 'vision_model.encoder.layers.20.mlp.fc1.weight', 'vision_model.encoder.layers.16.layer_norm1.bias', 'vision_model.encoder.layers.13.self_attn.q_proj.weight', 'vision_model.encoder.layers.15.self_attn.v_proj.bias', 'vision_model.encoder.layers.6.layer_norm2.weight', 'vision_model.encoder.layers.14.layer_norm2.bias', 'vision_model.encoder.layers.5.self_attn.q_proj.bias', 'vision_model.encoder.layers.6.self_attn.out_proj.bias', 'vision_model.encoder.layers.6.self_attn.out_proj.weight', 'vision_model.encoder.layers.14.self_attn.out_proj.weight', 'vision_model.encoder.layers.2.self_attn.k_proj.bias', 'vision_model.encoder.layers.22.self_attn.k_proj.weight', 'vision_model.encoder.layers.7.self_attn.k_proj.weight', 'vision_model.encoder.layers.2.layer_norm2.weight', 'vision_model.encoder.layers.18.layer_norm1.weight', 'visual_projection.weight', 'vision_model.encoder.layers.18.self_attn.out_proj.bias', 'vision_model.encoder.layers.0.self_attn.out_proj.weight', 'vision_model.encoder.layers.13.mlp.fc1.bias', 'vision_model.encoder.layers.19.self_attn.k_proj.bias', 'vision_model.encoder.layers.18.self_attn.out_proj.weight', 'vision_model.encoder.layers.22.mlp.fc1.bias', 'vision_model.encoder.layers.11.self_attn.k_proj.weight', 'vision_model.encoder.layers.4.mlp.fc2.weight', 'vision_model.encoder.layers.22.mlp.fc2.bias', 'vision_model.encoder.layers.4.self_attn.q_proj.bias', 'vision_model.encoder.layers.11.self_attn.out_proj.weight', 'vision_model.encoder.layers.18.mlp.fc2.bias', 'vision_model.encoder.layers.10.self_attn.q_proj.weight', 'vision_model.encoder.layers.16.mlp.fc1.weight', 'vision_model.encoder.layers.12.mlp.fc1.weight', 'vision_model.encoder.layers.15.mlp.fc1.bias', 'vision_model.encoder.layers.0.self_attn.v_proj.bias', 'vision_model.encoder.layers.21.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.self_attn.q_proj.bias', 'vision_model.encoder.layers.13.self_attn.out_proj.bias', 'vision_model.encoder.layers.7.self_attn.out_proj.bias', 'vision_model.encoder.layers.10.self_attn.k_proj.bias', 'vision_model.encoder.layers.10.mlp.fc2.bias', 'vision_model.encoder.layers.13.self_attn.q_proj.bias', 'vision_model.encoder.layers.1.layer_norm1.bias', 'vision_model.encoder.layers.23.layer_norm1.weight', 'vision_model.encoder.layers.16.layer_norm2.weight', 'vision_model.encoder.layers.6.self_attn.k_proj.bias', 'vision_model.encoder.layers.14.self_attn.k_proj.bias', 'vision_model.encoder.layers.3.layer_norm1.weight', 'vision_model.encoder.layers.20.self_attn.out_proj.weight', 'vision_model.encoder.layers.17.self_attn.v_proj.weight', 'vision_model.encoder.layers.3.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.self_attn.k_proj.bias', 'vision_model.encoder.layers.18.self_attn.k_proj.weight', 'vision_model.encoder.layers.12.layer_norm2.weight', 'vision_model.encoder.layers.15.self_attn.out_proj.bias', 'vision_model.encoder.layers.8.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.layer_norm1.weight', 'vision_model.encoder.layers.0.self_attn.q_proj.weight', 'vision_model.encoder.layers.3.mlp.fc2.weight', 'vision_model.encoder.layers.7.mlp.fc1.bias', 'vision_model.encoder.layers.4.self_attn.v_proj.weight', 'vision_model.encoder.layers.4.mlp.fc1.weight', 'vision_model.encoder.layers.23.self_attn.v_proj.bias', 'vision_model.encoder.layers.6.mlp.fc1.weight', 'vision_model.encoder.layers.22.layer_norm2.bias', 'vision_model.encoder.layers.9.layer_norm1.bias', 'vision_model.encoder.layers.11.self_attn.q_proj.bias', 'vision_model.embeddings.class_embedding', 'vision_model.encoder.layers.15.layer_norm2.bias', 'vision_model.encoder.layers.17.layer_norm1.bias', 'vision_model.encoder.layers.5.self_attn.out_proj.bias', 'vision_model.encoder.layers.21.layer_norm2.weight', 'vision_model.encoder.layers.21.self_attn.out_proj.bias', 'vision_model.encoder.layers.15.layer_norm2.weight', 'vision_model.encoder.layers.21.self_attn.v_proj.bias', 'vision_model.encoder.layers.13.layer_norm2.weight', 'vision_model.encoder.layers.2.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.self_attn.k_proj.bias', 'vision_model.encoder.layers.7.self_attn.v_proj.weight', 'vision_model.encoder.layers.4.mlp.fc1.bias', 'vision_model.encoder.layers.16.mlp.fc2.weight', 'vision_model.encoder.layers.18.layer_norm2.weight', 'vision_model.encoder.layers.1.self_attn.k_proj.bias', 'vision_model.post_layernorm.weight', 'vision_model.encoder.layers.6.mlp.fc2.bias', 'vision_model.encoder.layers.20.layer_norm1.bias', 'vision_model.encoder.layers.12.mlp.fc1.bias', 'vision_model.encoder.layers.23.self_attn.out_proj.weight', 'vision_model.encoder.layers.0.layer_norm1.weight', 'vision_model.encoder.layers.17.mlp.fc2.weight', 'vision_model.encoder.layers.2.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.layer_norm1.bias', 'vision_model.encoder.layers.16.self_attn.k_proj.bias', 'vision_model.encoder.layers.4.layer_norm1.weight', 'vision_model.encoder.layers.6.self_attn.v_proj.bias', 'vision_model.encoder.layers.5.self_attn.q_proj.weight', 'vision_model.encoder.layers.6.self_attn.v_proj.weight', 'vision_model.encoder.layers.15.layer_norm1.bias', 'vision_model.encoder.layers.16.layer_norm1.weight', 'vision_model.encoder.layers.7.mlp.fc2.weight', 'vision_model.encoder.layers.11.self_attn.out_proj.bias', 'vision_model.encoder.layers.6.layer_norm2.bias', 'vision_model.encoder.layers.6.mlp.fc1.bias', 'vision_model.encoder.layers.15.layer_norm1.weight', 'vision_model.encoder.layers.3.self_attn.out_proj.bias', 'vision_model.encoder.layers.10.layer_norm2.bias', 'vision_model.encoder.layers.7.mlp.fc2.bias', 'vision_model.encoder.layers.8.self_attn.v_proj.bias', 'vision_model.encoder.layers.14.self_attn.q_proj.bias', 'vision_model.encoder.layers.0.layer_norm2.bias', 'vision_model.encoder.layers.7.layer_norm1.bias', 'vision_model.encoder.layers.14.mlp.fc1.weight', 'vision_model.encoder.layers.20.mlp.fc2.bias', 'vision_model.encoder.layers.5.layer_norm2.weight', 'vision_model.encoder.layers.6.layer_norm1.weight', 'vision_model.encoder.layers.12.self_attn.out_proj.weight', 'vision_model.encoder.layers.21.self_attn.out_proj.weight', 'vision_model.encoder.layers.16.mlp.fc1.bias', 'vision_model.encoder.layers.3.layer_norm2.bias', 'vision_model.encoder.layers.17.self_attn.out_proj.bias', 'vision_model.encoder.layers.4.layer_norm1.bias', 'vision_model.encoder.layers.9.self_attn.k_proj.bias', 'vision_model.encoder.layers.21.mlp.fc1.weight', 'vision_model.encoder.layers.13.mlp.fc1.weight', 'vision_model.encoder.layers.22.self_attn.v_proj.weight', 'vision_model.encoder.layers.4.layer_norm2.weight', 'vision_model.encoder.layers.12.layer_norm1.weight', 'vision_model.encoder.layers.18.layer_norm2.bias', 'vision_model.encoder.layers.19.layer_norm1.weight', 'vision_model.encoder.layers.22.self_attn.v_proj.bias', 'vision_model.encoder.layers.18.mlp.fc1.bias', 'vision_model.encoder.layers.15.self_attn.q_proj.bias', 'vision_model.encoder.layers.22.layer_norm1.weight', 'vision_model.encoder.layers.4.self_attn.k_proj.weight', 'vision_model.encoder.layers.19.layer_norm1.bias', 'vision_model.encoder.layers.13.self_attn.k_proj.weight', 'vision_model.encoder.layers.11.mlp.fc1.bias', 'vision_model.encoder.layers.3.layer_norm2.weight', 'vision_model.encoder.layers.10.self_attn.q_proj.bias', 'vision_model.encoder.layers.14.layer_norm1.bias', 'vision_model.encoder.layers.23.self_attn.v_proj.weight', 'vision_model.encoder.layers.23.self_attn.q_proj.weight', 'vision_model.encoder.layers.19.mlp.fc2.weight', 'vision_model.encoder.layers.8.self_attn.out_proj.bias', 'vision_model.encoder.layers.19.layer_norm2.bias', 'vision_model.encoder.layers.18.layer_norm1.bias', 'vision_model.encoder.layers.11.self_attn.v_proj.bias', 'vision_model.encoder.layers.0.self_attn.v_proj.weight', 'vision_model.encoder.layers.8.mlp.fc1.bias', 'vision_model.encoder.layers.17.self_attn.v_proj.bias', 'vision_model.encoder.layers.18.self_attn.v_proj.weight', 'vision_model.encoder.layers.1.layer_norm2.weight', 'vision_model.encoder.layers.20.layer_norm2.bias', 'vision_model.encoder.layers.18.self_attn.q_proj.bias', 'vision_model.encoder.layers.11.self_attn.q_proj.weight', 'vision_model.encoder.layers.9.layer_norm2.weight', 'vision_model.embeddings.patch_embedding.weight', 'vision_model.encoder.layers.10.self_attn.k_proj.weight', 'vision_model.encoder.layers.23.self_attn.k_proj.weight', 'vision_model.encoder.layers.20.layer_norm1.weight', 'vision_model.encoder.layers.8.mlp.fc2.weight', 'logit_scale', 'vision_model.encoder.layers.7.self_attn.q_proj.bias', 'vision_model.encoder.layers.13.mlp.fc2.weight', 'vision_model.encoder.layers.21.layer_norm2.bias', 'vision_model.encoder.layers.14.mlp.fc2.bias', 'vision_model.encoder.layers.13.self_attn.v_proj.weight', 'vision_model.encoder.layers.17.self_attn.k_proj.weight', 'vision_model.encoder.layers.2.self_attn.out_proj.weight', 'vision_model.encoder.layers.9.mlp.fc2.bias', 'vision_model.encoder.layers.11.layer_norm2.weight', 'vision_model.encoder.layers.23.mlp.fc1.bias', 'vision_model.encoder.layers.20.self_attn.k_proj.bias', 'vision_model.encoder.layers.15.self_attn.k_proj.weight', 'vision_model.encoder.layers.8.self_attn.q_proj.bias', 'vision_model.encoder.layers.9.self_attn.v_proj.weight', 'vision_model.encoder.layers.3.self_attn.out_proj.weight']
- This IS expected if you are initializing CLIPTextModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing CLIPTextModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Initialized embedder #0: FrozenCLIPEmbedder with 123060480 params. Trainable: False
Initialized embedder #1: FrozenOpenCLIPEmbedder2 with 694659841 params. Trainable: False
Initialized embedder #2: ConcatTimestepEmbedderND with 0 params. Trainable: False
Initialized embedder #3: ConcatTimestepEmbedderND with 0 params. Trainable: False
Initialized embedder #4: ConcatTimestepEmbedderND with 0 params. Trainable: False
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
Building a Downsample layer with 2 dims.
--> settings are:
in-chn: 320, out-chn: 320, kernel-size: 3, stride: 2, padding: 1
constructing SpatialTransformer of depth 2 w/ 640 channels and 10 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 2. Setting context_dim to [2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 2 w/ 640 channels and 10 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 2. Setting context_dim to [2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 2048 and using 10 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Building a Downsample layer with 2 dims.
--> settings are:
in-chn: 640, out-chn: 640, kernel-size: 3, stride: 2, padding: 1
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
constructing SpatialTransformer of depth 10 w/ 1280 channels and 20 heads
WARNING: SpatialTransformer: Found context dims [2048] of depth 1, which does not match the specified 'depth' of 10. Setting context_dim to [2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048, 2048] now.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads with a dimension of 64.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 2048 and using 20 heads with a dimension of 64.
BasicTransformerBlock is using checkpointing
Loaded model config from [options/SUPIR_v0.yaml]
โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Traceback (most recent call last) โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ
โ /workspace/SUPIR/test.py:55 in โ
โ โ
โ 52 use_llava = not args.no_llava โ
โ 53 โ
โ 54 # load SUPIR โ
โ โฑ 55 model = create_SUPIR_model('options/SUPIR_v0.yaml', SUPIR_sign=args.SUPIR_sign).to(SUPIR โ
โ 56 model.ae_dtype = convert_dtype(args.ae_dtype) โ
โ 57 model.model.dtype = convert_dtype(args.diff_dtype) โ
โ 58 # load LLaVA โ
โ โ
โ /workspace/SUPIR/SUPIR/util.py:39 in create_SUPIR_model โ
โ โ
โ 36 โ model = instantiate_from_config(config.model).cpu() โ
โ 37 โ print(f'Loaded model config from [{config_path}]') โ
โ 38 โ if config.SDXL_CKPT is not None: โ
โ โฑ 39 โ โ model.load_state_dict(load_state_dict(config.SDXL_CKPT), strict=False) โ
โ 40 โ if config.SUPIR_CKPT is not None: โ
โ 41 โ โ model.load_state_dict(load_state_dict(config.SUPIR_CKPT), strict=False) โ
โ 42 โ if SUPIR_sign is not None: โ
โ โ
โ /workspace/SUPIR/SUPIR/util.py:19 in load_state_dict โ
โ โ
โ 16 โ _, extension = os.path.splitext(ckpt_path) โ
โ 17 โ if extension.lower() == ".safetensors": โ
โ 18 โ โ import safetensors.torch โ
โ โฑ 19 โ โ state_dict = safetensors.torch.load_file(ckpt_path, device=location) โ
โ 20 โ else: โ
โ 21 โ โ state_dict = get_state_dict(torch.load(ckpt_path, map_location=torch.device(loca โ
โ 22 โ state_dict = get_state_dict(state_dict) โ
โ โ
โ /root/miniconda3/envs/SUPIR/lib/python3.8/site-packages/safetensors/torch.py:308 in load_file โ
โ โ
โ 305 โ ``` โ
โ 306 โ """ โ
โ 307 โ result = {} โ
โ โฑ 308 โ with safe_open(filename, framework="pt", device=device) as f: โ
โ 309 โ โ for k in f.keys(): โ
โ 310 โ โ โ result[k] = f.get_tensor(k) โ
โ 311 โ return result โ
โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ
OSError: No such device (os error 19)`
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent