Training

[selinkoles]

Hi, I used "python train_net.py --num-gpus 1 --config-file configs/diffinst.coco.res50.yaml" to train the model on COCO datataset. Under "/models" folder I have R-50.pkl file too. However after I got these warnings, it gave some error and stopped.

WARNING [04/01 21:51:28 fvcore.common.checkpoint]: Some model parameters or buffers are not found in the checkpoint: alphas_cumprod alphas_cumprod_prev backbone.fpn_lateral2.{bias, weight} backbone.fpn_lateral3.{bias, weight} backbone.fpn_lateral4.{bias, weight} backbone.fpn_lateral5.{bias, weight} backbone.fpn_output2.{bias, weight} backbone.fpn_output3.{bias, weight} backbone.fpn_output4.{bias, weight} backbone.fpn_output5.{bias, weight} betas head.head_series.0.bboxes_delta.{bias, weight} head.head_series.0.block_time_mlp.1.{bias, weight} head.head_series.0.class_logits.{bias, weight} head.head_series.0.cls_module.0.weight head.head_series.0.cls_module.1.{bias, weight} head.head_series.0.controller.{bias, weight} head.head_series.0.inst_interact.dynamic_layer.{bias, weight} head.head_series.0.inst_interact.norm1.{bias, weight} head.head_series.0.inst_interact.norm2.{bias, weight} head.head_series.0.inst_interact.norm3.{bias, weight} head.head_series.0.inst_interact.out_layer.{bias, weight} head.head_series.0.linear1.{bias, weight} head.head_series.0.linear2.{bias, weight} head.head_series.0.norm1.{bias, weight} head.head_series.0.norm2.{bias, weight} head.head_series.0.norm3.{bias, weight} head.head_series.0.reg_module.0.weight head.head_series.0.reg_module.1.{bias, weight} head.head_series.0.reg_module.3.weight head.head_series.0.reg_module.4.{bias, weight} head.head_series.0.reg_module.6.weight head.head_series.0.reg_module.7.{bias, weight} head.head_series.0.self_attn.out_proj.{bias, weight} head.head_series.0.self_attn.{in_proj_bias, in_proj_weight} head.head_series.1.bboxes_delta.{bias, weight} head.head_series.1.block_time_mlp.1.{bias, weight} head.head_series.1.class_logits.{bias, weight} head.head_series.1.cls_module.0.weight head.head_series.1.cls_module.1.{bias, weight} head.head_series.1.controller.{bias, weight} head.head_series.1.inst_interact.dynamic_layer.{bias, weight} head.head_series.1.inst_interact.norm1.{bias, weight} head.head_series.1.inst_interact.norm2.{bias, weight} head.head_series.1.inst_interact.norm3.{bias, weight} head.head_series.1.inst_interact.out_layer.{bias, weight} head.head_series.1.linear1.{bias, weight} head.head_series.1.linear2.{bias, weight} head.head_series.1.norm1.{bias, weight} head.head_series.1.norm2.{bias, weight} head.head_series.1.norm3.{bias, weight} head.head_series.1.reg_module.0.weight head.head_series.1.reg_module.1.{bias, weight} head.head_series.1.reg_module.3.weight head.head_series.1.reg_module.4.{bias, weight} head.head_series.1.reg_module.6.weight head.head_series.1.reg_module.7.{bias, weight} head.head_series.1.self_attn.out_proj.{bias, weight} head.head_series.1.self_attn.{in_proj_bias, in_proj_weight} head.head_series.2.bboxes_delta.{bias, weight} head.head_series.2.block_time_mlp.1.{bias, weight} head.head_series.2.class_logits.{bias, weight} head.head_series.2.cls_module.0.weight head.head_series.2.cls_module.1.{bias, weight} head.head_series.2.controller.{bias, weight} head.head_series.2.inst_interact.dynamic_layer.{bias, weight} head.head_series.2.inst_interact.norm1.{bias, weight} head.head_series.2.inst_interact.norm2.{bias, weight} head.head_series.2.inst_interact.norm3.{bias, weight} head.head_series.2.inst_interact.out_layer.{bias, weight} head.head_series.2.linear1.{bias, weight} head.head_series.2.linear2.{bias, weight} head.head_series.2.norm1.{bias, weight} head.head_series.2.norm2.{bias, weight} head.head_series.2.norm3.{bias, weight} head.head_series.2.reg_module.0.weight head.head_series.2.reg_module.1.{bias, weight} head.head_series.2.reg_module.3.weight head.head_series.2.reg_module.4.{bias, weight} head.head_series.2.reg_module.6.weight head.head_series.2.reg_module.7.{bias, weight} head.head_series.2.self_attn.out_proj.{bias, weight} head.head_series.2.self_attn.{in_proj_bias, in_proj_weight} head.head_series.3.bboxes_delta.{bias, weight} head.head_series.3.block_time_mlp.1.{bias, weight} head.head_series.3.class_logits.{bias, weight} head.head_series.3.cls_module.0.weight head.head_series.3.cls_module.1.{bias, weight} head.head_series.3.controller.{bias, weight} head.head_series.3.inst_interact.dynamic_layer.{bias, weight} head.head_series.3.inst_interact.norm1.{bias, weight} head.head_series.3.inst_interact.norm2.{bias, weight} head.head_series.3.inst_interact.norm3.{bias, weight} head.head_series.3.inst_interact.out_layer.{bias, weight} head.head_series.3.linear1.{bias, weight} head.head_series.3.linear2.{bias, weight} head.head_series.3.norm1.{bias, weight} head.head_series.3.norm2.{bias, weight} head.head_series.3.norm3.{bias, weight} head.head_series.3.reg_module.0.weight head.head_series.3.reg_module.1.{bias, weight} head.head_series.3.reg_module.3.weight head.head_series.3.reg_module.4.{bias, weight} head.head_series.3.reg_module.6.weight head.head_series.3.reg_module.7.{bias, weight} head.head_series.3.self_attn.out_proj.{bias, weight} head.head_series.3.self_attn.{in_proj_bias, in_proj_weight} head.head_series.4.bboxes_delta.{bias, weight} head.head_series.4.block_time_mlp.1.{bias, weight} head.head_series.4.class_logits.{bias, weight} head.head_series.4.cls_module.0.weight head.head_series.4.cls_module.1.{bias, weight} head.head_series.4.controller.{bias, weight} head.head_series.4.inst_interact.dynamic_layer.{bias, weight} head.head_series.4.inst_interact.norm1.{bias, weight} head.head_series.4.inst_interact.norm2.{bias, weight} head.head_series.4.inst_interact.norm3.{bias, weight} head.head_series.4.inst_interact.out_layer.{bias, weight} head.head_series.4.linear1.{bias, weight} head.head_series.4.linear2.{bias, weight} head.head_series.4.norm1.{bias, weight} head.head_series.4.norm2.{bias, weight} head.head_series.4.norm3.{bias, weight} head.head_series.4.reg_module.0.weight head.head_series.4.reg_module.1.{bias, weight} head.head_series.4.reg_module.3.weight head.head_series.4.reg_module.4.{bias, weight} head.head_series.4.reg_module.6.weight head.head_series.4.reg_module.7.{bias, weight} head.head_series.4.self_attn.out_proj.{bias, weight} head.head_series.4.self_attn.{in_proj_bias, in_proj_weight} head.head_series.5.bboxes_delta.{bias, weight} head.head_series.5.block_time_mlp.1.{bias, weight} head.head_series.5.class_logits.{bias, weight} head.head_series.5.cls_module.0.weight head.head_series.5.cls_module.1.{bias, weight} head.head_series.5.controller.{bias, weight} head.head_series.5.inst_interact.dynamic_layer.{bias, weight} head.head_series.5.inst_interact.norm1.{bias, weight} head.head_series.5.inst_interact.norm2.{bias, weight} head.head_series.5.inst_interact.norm3.{bias, weight} head.head_series.5.inst_interact.out_layer.{bias, weight} head.head_series.5.linear1.{bias, weight} head.head_series.5.linear2.{bias, weight} head.head_series.5.norm1.{bias, weight} head.head_series.5.norm2.{bias, weight} head.head_series.5.norm3.{bias, weight} head.head_series.5.reg_module.0.weight head.head_series.5.reg_module.1.{bias, weight} head.head_series.5.reg_module.3.weight head.head_series.5.reg_module.4.{bias, weight} head.head_series.5.reg_module.6.weight head.head_series.5.reg_module.7.{bias, weight} head.head_series.5.self_attn.out_proj.{bias, weight} head.head_series.5.self_attn.{in_proj_bias, in_proj_weight} head.mask_head.0.0.weight head.mask_head.0.1.{bias, running_mean, running_var, weight} head.mask_head.1.0.weight head.mask_head.1.1.{bias, running_mean, running_var, weight} head.mask_head.2.0.weight head.mask_head.2.1.{bias, running_mean, running_var, weight} head.mask_head.3.0.weight head.mask_head.3.1.{bias, running_mean, running_var, weight} head.mask_head.4.{bias, weight} head.mask_refine.0.0.weight head.mask_refine.0.1.{bias, running_mean, running_var, weight} head.mask_refine.1.0.weight head.mask_refine.1.1.{bias, running_mean, running_var, weight} head.mask_refine.2.0.weight head.mask_refine.2.1.{bias, running_mean, running_var, weight} head.time_mlp.1.{bias, weight} head.time_mlp.3.{bias, weight} log_one_minus_alphas_cumprod posterior_log_variance_clipped posterior_mean_coef1 posterior_mean_coef2 posterior_variance sqrt_alphas_cumprod sqrt_one_minus_alphas_cumprod sqrt_recip_alphas_cumprod sqrt_recipm1_alphas_cumprod WARNING [04/01 21:51:28 fvcore.common.checkpoint]: The checkpoint state_dict contains keys that are not used by the model: fc1000.{bias, weight} stem.conv1.bias

[zhangxgu]

This warning has nothing error to do with the training. Please show me the errors. The pretrained weights are obtained by training classification of 1k categories on ImageNet. Its classifier is not exists in the diffusioninst.

[selinkoles]

I thought those weights for the backbone initialization. While i was evaluating the trained model, even though it utilizes the same weights for the backbone I didn’t get this warning. I would like to know why during training i got these warnings? Thanks in advance