DeepSpeed
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Published
20 hours ago •
microsoft
microsoft
RuntimeError: Error(s) in loading state_dict
Describe the bug
i can only use pytorch to training model with Qwen1.5-7B.
but when i use deepSpeed i got a problem with CUDA out of memory
my config with zeRo2 is:
{
"fp16": {
"enabled": "auto",
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"bf16": {
"enabled": "auto"
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"betas": "auto",
"eps": "auto",
"weight_decay": "auto"
}
},
"scheduler": {
"type": "WarmupLR",
"params": {
"warmup_min_lr": "auto",
"warmup_max_lr": "auto",
"warmup_num_steps": "auto"
}
},
"zero_optimization": {
"stage": 2,
"offload_optimizer": {
"device": "none",
"pin_memory": true
},
"allgather_partitions": true,
"allgather_bucket_size": 2e8,
"overlap_comm": true,
"reduce_scatter": true,
"reduce_bucket_size": 2e8,
"contiguous_gradients": true
},
"gradient_accumulation_steps": "auto",
"gradient_clipping": "auto",
"steps_per_print": 100,
"train_batch_size": "auto",
"train_micro_batch_size_per_gpu": "auto",
"wall_clock_breakdown": false
} then i had change param with "offload_optimizer": { "device": "cpu", "pin_memory": true }, then it has an other problem like this:
[rank1]: Traceback (most recent call last):
[rank1]: File "/home/ai/mydata/models/Qwen1.5-main/examples/sft/finetune.py", line 378, in <module>
[rank1]: train()
[rank1]: File "/home/ai/mydata/models/Qwen1.5-main/examples/sft/finetune.py", line 367, in train
[rank1]: trainer.train(resume_from_checkpoint=True)
[rank1]: File "/opt/conda/lib/python3.10/site-packages/transformers/trainer.py", line 1885, in train
[rank1]: return inner_training_loop(
[rank1]: File "/opt/conda/lib/python3.10/site-packages/transformers/trainer.py", line 2063, in _inner_training_loop
[rank1]: deepspeed_load_checkpoint(
[rank1]: File "/opt/conda/lib/python3.10/site-packages/transformers/integrations/deepspeed.py", line 432, in deepspeed_load_checkpoint
[rank1]: load_path, _ = deepspeed_engine.load_checkpoint(
[rank1]: File "/opt/conda/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 2764, in load_checkpoint
[rank1]: load_path, client_states = self._load_checkpoint(load_dir,
[rank1]: File "/opt/conda/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 2847, in _load_checkpoint
[rank1]: self.load_module_state_dict(checkpoint=checkpoint,
[rank1]: File "/opt/conda/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 2627, in load_module_state_dict
[rank1]: self.module.load_state_dict(
[rank1]: File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 2189, in load_state_dict
[rank1]: raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
[rank1]: RuntimeError: Error(s) in loading state_dict for Qwen2ForCausalLM:
[rank1]: Missing key(s) in state_dict: "model.layers.24.self_attn.q_proj.weight", "model.layers.24.self_attn.q_proj.bias", "model.layers.24.self_attn.k_proj.weight", "model.layers.24.self_attn.k_proj.bias", "model.layers.24.self_attn.v_proj.weight", "model.layers.24.self_attn.v_proj.bias", "model.layers.24.self_attn.o_proj.weight", "model.layers.24.mlp.gate_proj.weight", "model.layers.24.mlp.up_proj.weight", "model.layers.24.mlp.down_proj.weight", "model.layers.24.input_layernorm.weight", "model.layers.24.post_attention_layernorm.weight", "model.layers.25.self_attn.q_proj.weight", "model.layers.25.self_attn.q_proj.bias", "model.layers.25.self_attn.k_proj.weight", "model.layers.25.self_attn.k_proj.bias", "model.layers.25.self_attn.v_proj.weight", "model.layers.25.self_attn.v_proj.bias", "model.layers.25.self_attn.o_proj.weight", "model.layers.25.mlp.gate_proj.weight", "model.layers.25.mlp.up_proj.weight", "model.layers.25.mlp.down_proj.weight", "model.layers.25.input_layernorm.weight", "model.layers.25.post_attention_layernorm.weight", "model.layers.26.self_attn.q_proj.weight", "model.layers.26.self_attn.q_proj.bias", "model.layers.26.self_attn.k_proj.weight", "model.layers.26.self_attn.k_proj.bias", "model.layers.26.self_attn.v_proj.weight", "model.layers.26.self_attn.v_proj.bias", "model.layers.26.self_attn.o_proj.weight", "model.layers.26.mlp.gate_proj.weight", "model.layers.26.mlp.up_proj.weight", "model.layers.26.mlp.down_proj.weight", "model.layers.26.input_layernorm.weight", "model.layers.26.post_attention_layernorm.weight", "model.layers.27.self_attn.q_proj.weight", "model.layers.27.self_attn.q_proj.bias", "model.layers.27.self_attn.k_proj.weight", "model.layers.27.self_attn.k_proj.bias", "model.layers.27.self_attn.v_proj.weight", "model.layers.27.self_attn.v_proj.bias", "model.layers.27.self_attn.o_proj.weight", "model.layers.27.mlp.gate_proj.weight", "model.layers.27.mlp.up_proj.weight", "model.layers.27.mlp.down_proj.weight", "model.layers.27.input_layernorm.weight", "model.layers.27.post_attention_layernorm.weight", "model.layers.28.self_attn.q_proj.weight", "model.layers.28.self_attn.q_proj.bias", "model.layers.28.self_attn.k_proj.weight", "model.layers.28.self_attn.k_proj.bias", "model.layers.28.self_attn.v_proj.weight", "model.layers.28.self_attn.v_proj.bias", "model.layers.28.self_attn.o_proj.weight", "model.layers.28.mlp.gate_proj.weight", "model.layers.28.mlp.up_proj.weight", "model.layers.28.mlp.down_proj.weight", "model.layers.28.input_layernorm.weight", "model.layers.28.post_attention_layernorm.weight", "model.layers.29.self_attn.q_proj.weight", "model.layers.29.self_attn.q_proj.bias", "model.layers.29.self_attn.k_proj.weight", "model.layers.29.self_attn.k_proj.bias", "model.layers.29.self_attn.v_proj.weight", "model.layers.29.self_attn.v_proj.bias", "model.layers.29.self_attn.o_proj.weight", "model.layers.29.mlp.gate_proj.weight", "model.layers.29.mlp.up_proj.weight", "model.layers.29.mlp.down_proj.weight", "model.layers.29.input_layernorm.weight", "model.layers.29.post_attention_layernorm.weight", "model.layers.30.self_attn.q_proj.weight", "model.layers.30.self_attn.q_proj.bias", "model.layers.30.self_attn.k_proj.weight", "model.layers.30.self_attn.k_proj.bias", "model.layers.30.self_attn.v_proj.weight", "model.layers.30.self_attn.v_proj.bias", "model.layers.30.self_attn.o_proj.weight", "model.layers.30.mlp.gate_proj.weight", "model.layers.30.mlp.up_proj.weight", "model.layers.30.mlp.down_proj.weight", "model.layers.30.input_layernorm.weight", "model.layers.30.post_attention_layernorm.weight", "model.layers.31.self_attn.q_proj.weight", "model.layers.31.self_attn.q_proj.bias", "model.layers.31.self_attn.k_proj.weight", "model.layers.31.self_attn.k_proj.bias", "model.layers.31.self_attn.v_proj.weight", "model.layers.31.self_attn.v_proj.bias", "model.layers.31.self_attn.o_proj.weight", "model.layers.31.mlp.gate_proj.weight", "model.layers.31.mlp.up_proj.weight", "model.layers.31.mlp.down_proj.weight", "model.layers.31.input_layernorm.weight", "model.layers.31.post_attention_layernorm.weight".
[rank1]: size mismatch for model.embed_tokens.weight: copying a param with shape torch.Size([151936, 1024]) from checkpoint, the shape in current model is torch.Size([151936, 4096]).
[rank1]: size mismatch for model.layers.0.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.0.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.0.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.0.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.0.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.0.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.0.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.0.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.0.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.0.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.0.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.0.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.1.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.1.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.1.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.1.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.1.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.1.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.1.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.1.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.1.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.1.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.1.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.1.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.2.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.2.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.2.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.2.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.2.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.2.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.2.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.2.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.2.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.2.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.2.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.2.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.3.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.3.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.3.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.3.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.3.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.3.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.3.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.3.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.3.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.3.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.3.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.3.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.4.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.4.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.4.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.4.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.4.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.4.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.4.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.4.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.4.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.4.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.4.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.4.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.5.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.5.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.5.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.5.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.5.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.5.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.5.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.5.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.5.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.5.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.5.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.5.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.6.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.6.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.6.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.6.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.6.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.6.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.6.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.6.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.6.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.6.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.6.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.6.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.7.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.7.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.7.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.7.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.7.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.7.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.7.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.7.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.7.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.7.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.7.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.7.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.8.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.8.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.8.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.8.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.8.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.8.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.8.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.8.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.8.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.8.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.8.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.8.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.9.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.9.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.9.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.9.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.9.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.9.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.9.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.9.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.9.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.9.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.9.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.9.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.10.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.10.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.10.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.10.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.10.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.10.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.10.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.10.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.10.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.10.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.10.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.10.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.11.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.11.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.11.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.11.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.11.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.11.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.11.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.11.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.11.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.11.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.11.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.11.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.12.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.12.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.12.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.12.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.12.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.12.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.12.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.12.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.12.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.12.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.12.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.12.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.13.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.13.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.13.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.13.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.13.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.13.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.13.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.13.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.13.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.13.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.13.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.13.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.14.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.14.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.14.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.14.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.14.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.14.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.14.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.14.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.14.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.14.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.14.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.14.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.15.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.15.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.15.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.15.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.15.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.15.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.15.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.15.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.15.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.15.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.15.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.15.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.16.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.16.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.16.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.16.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.16.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.16.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.16.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.16.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.16.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.16.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.16.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.16.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.17.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.17.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.17.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.17.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.17.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.17.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.17.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.17.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.17.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.17.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.17.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.17.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.18.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.18.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.18.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.18.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.18.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.18.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.18.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.18.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.18.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.18.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.18.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.18.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.19.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.19.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.19.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.19.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.19.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.19.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.19.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.19.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.19.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.19.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.19.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.19.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.20.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.20.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.20.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.20.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.20.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.20.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.20.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.20.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.20.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.20.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.20.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.20.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.21.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.21.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.21.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.21.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.21.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.21.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.21.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.21.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.21.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.21.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.21.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.21.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.22.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.22.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.22.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.22.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.22.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.22.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.22.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.22.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.22.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.22.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.22.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.22.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.23.self_attn.q_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.23.self_attn.q_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.23.self_attn.k_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.23.self_attn.k_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.23.self_attn.v_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.23.self_attn.v_proj.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.23.self_attn.o_proj.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
[rank1]: size mismatch for model.layers.23.mlp.gate_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.23.mlp.up_proj.weight: copying a param with shape torch.Size([2816, 1024]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
[rank1]: size mismatch for model.layers.23.mlp.down_proj.weight: copying a param with shape torch.Size([1024, 2816]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
[rank1]: size mismatch for model.layers.23.input_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.layers.23.post_attention_layernorm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for model.norm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([4096]).
[rank1]: size mismatch for lm_head.weight: copying a param with shape torch.Size([151936, 1024]) from checkpoint, the shape in current model is torch.Size([151936, 4096]).
W0527 01:21:26.844000 140472356030272 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1056309 closing signal SIGTERM
W0527 01:21:26.844000 140472356030272 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1056310 closing signal SIGTERM
I have the same question in deepspeed stage3 but for the shape in current model is torch.Size([0]), please someone help us. T_T
@lxd551326, it seems you seeing two different issues.
- CUDA OOM using DeepSpeed for a model that works with pure pytorch is very strange and should be investigated. Can you provide more repro details for that?
- The checkpoint loading problem seems to be due to a mismatch between checkpoint and model definition. Can you check that it works with pytorch only?
For both above cases, it would be very helpful if you provide repro steps?
- DeepSpeed for a model that works with pure pytorch is very stran
Have you solved the problem? I meet it too. The shape is correct in my program without using deepspeed.
@lhyscau, @DavidYanAnDe, and @lxd551326 are you able to provide repro steps?
@lhyscau, @DavidYanAnDe, and @lxd551326 are you able to provide repro steps?
I comment the zero_optimizer param in the ds.config file, then the error doesn't happen.
@lhyscau, @DavidYanAnDe, and @lxd551326 are you able to provide repro steps?
I comment the zero_optimizer param in the ds.config file, then the error doesn't happen.
May I see your ds.config file? Thx
