diff --git "a/log.txt" "b/log.txt" new file mode 100644--- /dev/null +++ "b/log.txt" @@ -0,0 +1,3191 @@ +[2023-12-25 02:58:11,673] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2023-12-25 02:58:11,673] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2023-12-25 02:58:11,673] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2023-12-25 02:58:11,673] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2023-12-25 02:58:11,687] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2023-12-25 02:58:11,690] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2023-12-25 02:58:11,781] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2023-12-25 02:58:11,798] [INFO] [real_accelerator.py:133:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2023-12-25 02:58:12,121] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented +[2023-12-25 02:58:12,122] [INFO] [comm.py:616:init_distributed] cdb=None +[2023-12-25 02:58:12,122] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented +[2023-12-25 02:58:12,122] [INFO] [comm.py:616:init_distributed] cdb=None +[2023-12-25 02:58:12,122] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented +[2023-12-25 02:58:12,122] [INFO] [comm.py:616:init_distributed] cdb=None +[2023-12-25 02:58:12,122] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented +[2023-12-25 02:58:12,122] [INFO] [comm.py:616:init_distributed] cdb=None +[2023-12-25 02:58:12,122] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented +[2023-12-25 02:58:12,122] [INFO] [comm.py:616:init_distributed] cdb=None +[2023-12-25 02:58:12,122] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented +[2023-12-25 02:58:12,122] [INFO] [comm.py:616:init_distributed] cdb=None +[2023-12-25 02:58:12,122] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented +[2023-12-25 02:58:12,122] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented +[2023-12-25 02:58:12,122] [INFO] [comm.py:616:init_distributed] cdb=None +[2023-12-25 02:58:12,122] [INFO] [comm.py:616:init_distributed] cdb=None +[2023-12-25 02:58:12,122] [INFO] [comm.py:643:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:1 to store for rank: 1 +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:1 to store for rank: 3 +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:1 to store for rank: 7 +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:1 to store for rank: 2 +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:1 to store for rank: 6 +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:1 to store for rank: 5 +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:1 to store for rank: 4 +12/25/2021212/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Rank 16: Completed store-based barrier for key:store_based_barrier_key:1 with 32 nodes. +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Rank 19: Completed store-based barrier for key:store_based_barrier_key:1 with 32 nodes. +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Rank 21: Completed store-based barrier for key:store_based_barrier_key:1 with 32 nodes. +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Rank 17: Completed store-based barrier for key:store_based_barrier_key:1 with 32 nodes. +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Rank 18: Completed store-based barrier for key:store_based_barrier_key:1 with 32 nodes. +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Rank 30: Completed store-based barrier for key:store_based_barrier_key:1 with 32 nodes. +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Rank 27: Completed store-based barrier for key:store_based_barrier_key:1 with 32 nodes. +12/25/2023 02:58:12 - INFO - torch.distributed.distributed_c10d - Rank 28: Completed store-based barrier for key:store_based_barrier_key:1 with 32 nodes. +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - WARNING - utils.common - `ddp_find_unused_parameters` needs to be set as False in DDP training. +12/25/2023 02:58:12 - INFO - utils.common - Process rank: 0, device: cuda:0, n_gpu: 1 + distributed training: True, 16-bits training: False +12/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=False, +ddp_timeout=1800, +debug=[], +deepspeed=ds_z3_no_offload.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_steps=None, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +generation_config=None, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=2, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=2e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=0, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/group/20025/jiuding/ckpt/final/runs/Dec25_02-58-10_vc-816648075-20231223-fb73dac2-worker-2, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=10, +logging_strategy=steps, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=2.0, +optim=adamw_torch, +optim_args=None, +output_dir=/group/20025/jiuding/ckpt/final, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=4, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=[], +resume_from_checkpoint=None, +run_name=/group/20025/jiuding/ckpt/final, +save_on_each_node=False, +save_safetensors=False, +save_steps=500, +save_strategy=epoch, +save_total_limit=10, +seed=42, +sharded_ddp=[], +skip_memory_metrics=True, +sortish_sampler=False, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.0, +warmup_steps=0, +weight_decay=0.0, +) +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - WARNING - utils.common - `ddp_find_unused_parameters` needs to be set as False in DDP training. +12/25/2023 02:58:12 - INFO - utils.common - Process rank: 3, device: cuda:3, n_gpu: 1 + distributed training: True, 16-bits training: False +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.99912/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=False, +ddp_timeout=1800, +debug=[], +deepspeed=ds_z3_no_offload.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_steps=None, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +generation_config=None, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=2, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=2e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=5, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/group/20025/jiuding/ckpt/final/runs/Dec25_02-58-10_vc-816648075-20231223-fb73dac2-worker-3, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=10, +logging_strategy=steps, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=2.0, +optim=adamw_torch, +optim_args=None, +output_dir=/group/20025/jiuding/ckpt/final, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=4, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=[], +resume_from_checkpoint=None, +run_name=/group/20025/jiuding/ckpt/final, +save_on_each_node=False, +save_safetensors=False, +save_steps=500, +save_strategy=epoch, +save_total12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - WARNING - utils.common - `ddp_find_unused_parameters` needs to be set as False in DDP training. +12/25/2023 02:58:12 - INFO - utils.common - Process rank: 1, device: cuda:1, n_gpu: 1 + distributed training: True, 16-bits training: False +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - WARNING - utils.common - `ddp_find_unused_parameters` needs to be set as False in DDP training. +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - INFO - utils.common - Process rank: 3, device: cuda:3, n_gpu: 1 + distributed training: True, 16-bits training: False +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - WARNING - utils.common - `ddp_find_unused_parameters` needs to be set as False in DDP training. +12/25/2023 02:58:12 - INFO - utils.common - Process rank: 7, device: cuda:7, n_gpu: 1 + distributed training: True, 16-bits training: False +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - WARNING - utils.common - `ddp_find_unused_parameters` needs to be set as False in DDP training. +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - INFO - utils.common - Process rank: 2, device: cuda:2, n_gpu: 1 + distributed training: True, 16-bits training: False +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - WARNING - utils.common - `ddp_find_unused_parameters` needs to be set as False in DDP training. +12/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=False, +ddp_timeout=1800, +debug=[], +deepspeed=ds_z3_no_offload.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_steps=None, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +generation_config=None, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=2, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=2e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=1, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/group/20025/jiuding/ckpt/final/runs/Dec25_02-58-11_vc-816648075-20231223-fb73dac2-worker-0, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=10, +logging_strategy=steps, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=2.0, +optim=adamw_torch, +optim_args=None, +output_dir=/group/20025/jiuding/ckpt/final, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=4, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=[], +resume_from_checkpoint=None, +run_name=/group/20025/jiuding/ckpt/final, +save_on_each_node=False, +save_safetensors=False, +save_steps=500, +save_strategy=epoch, +save_total_limit=10, +seed=42, +sharded_ddp=[], +skip_memory_metrics=True, +sortish_sampler=False, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.0, +warmup_steps=0, +weight_decay=0.0, +) +12/25/2023 02:58:12 - INFO - utils.common - Process rank: 5, device: cuda:5, n_gpu: 1 + distributed training: True, 16-bits training: False +12/25/2023 02:58:12 - WARNING - utils.common - We recommend enable fp16 mixed precision training. +12/25/2023 02:58:12 - WARNING - utils.common - Please specify `prompt_template` if you are using other pre-trained models. +12/25/2023 02:58:12 - WARNING - utils.common - `ddp_find_unused_parameters` needs to be set as False in DDP training. +12/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=False, +ddp_timeout=1800, +debug=[], +deepspeed=ds_z3_no_offload.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_steps=None, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +generation_config=None, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=2, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=2e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=3, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/group/20025/jiuding/ckpt/final/runs/Dec25_02-58-11_vc-816648075-20231223-fb73dac2-worker-0, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=10, +logging_strategy=steps, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=2.0, +optim=adamw_torch, +optim_args=None, +output_dir=/group/20025/jiuding/ckpt/final, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=4, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=[], +resume_from_checkpoint=None, +run_name=/group/20025/jiuding/ckpt/final, +save_on_each_node=False, +save_safetensors=False, +save_steps=500, +save_strategy=epoch, +save_total_limit=10, +seed=42, +sharded_ddp=[], +skip_memory_metrics=True, +sortish_sampler=False, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.0, +warmup_steps=0, +weight_decay=0.0, +) +12/25/2023 02:58:12 - INFO - utils.common - Process rank: 6, device: cuda:6, n_gpu: 1 + distributed training: True, 16-bits training: False +12/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=False, +ddp_timeout=1800, +debug=[], +deepspeed=ds_z3_no_offload.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_steps=None, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +generation_config=None, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=2, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=2e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=7, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/group/20025/jiuding/ckpt/final/runs/Dec25_02-58-11_vc-816648075-20231223-fb73dac2-worker-0, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=10, +logging_strategy=steps, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=2.0, +optim=adamw_torch, +optim_args=None, +output_dir=/group/20025/jiuding/ckpt/final, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=4, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=[], +resume_from_checkpoint=None, +run_name=/group/20025/jiuding/ckpt/final, +save_on_each_node=False, +save_safetensors=False, +save_steps=500, +save_strategy=epoch, +save_total_limit=10, +seed=42, +sharded_ddp=[], +skip_memory_metrics=True, +sortish_sampler=False, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.0, +warmup_steps=0, +weight_decay=0.0, +) +12/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=False, +ddp_timeout=1800, +debug=[], +deepspeed=ds_z3_no_offload.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_steps=None, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +generation_config=None, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=2, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=2e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=2, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/group/20025/jiuding/ckpt/final/runs/Dec25_02-58-11_vc-816648075-20231223-fb73dac2-worker-0, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=10, +logging_strategy=steps, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=2.0, +optim=adamw_torch, +optim_args=None, +output_dir=/group/20025/jiuding/ckpt/final, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=4, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=[], +resume_from_checkpoint=None, +run_name=/group/20025/jiuding/ckpt/final, +save_on_each_node=False, +save_safetensors=False, +save_steps=500, +save_strategy=epoch, +save_total_limit=10, +seed=42, +sharded_ddp=[], +skip_memory_metrics=True, +sortish_sampler=False, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.0, +warmup_steps=0, +weight_decay=0.0, +) +12/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=False, +ddp_timeout=1800, +debug=[], +deepspeed=ds_z3_no_offload.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_steps=None, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +generation_config=None, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=2, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=2e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=5, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/group/20025/jiuding/ckpt/final/runs/Dec25_02-58-11_vc-816648075-20231223-fb73dac2-worker-0, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=10, +logging_strategy=steps, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=2.0, +optim=adamw_torch, +optim_args=None, +output_dir=/group/20025/jiuding/ckpt/final, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=4, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=[], +resume_from_checkpoint=None, +run_name=/group/20025/jiuding/ckpt/final, +save_on_each_node=False, +save_safetensors=False, +save_steps=500, +save_strategy=epoch, +save_total_limit=10, +seed=42, +sharded_ddp=[], +skip_memory_metrics=True, +sortish_sampler=False, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.0, +warmup_steps=0, +weight_decay=0.0, +) +12/25/2023 02:58:12 - INFO - utils.common - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=1, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=False, +ddp_timeout=1800, +debug=[], +deepspeed=ds_z3_no_offload.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_steps=None, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +generation_config=None, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=2, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=2e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=6, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/group/20025/jiuding/ckpt/final/runs/Dec25_02-58-11_vc-816648075-20231223-fb73dac2-worker-0, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=10, +logging_strategy=steps, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=2.0, +optim=adamw_torch, +optim_args=None, +output_dir=/group/20025/jiuding/ckpt/final, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=4, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=[], +resume_from_checkpoint=None, +run_name=/group/20025/jiuding/ckpt/final, +save_on_each_node=False, +save_safetensors=False, +save_steps=500, +save_strategy=epoch, +save_total_limit=10, +seed=42, +sharded_ddp=[], +skip_memory_metrics=True, +sortish_sampler=False, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +u12/212/25/2023 02:58:12 - INFO - utils.common - Using FlashAttention-2 for faster training and inference. +12/25/2023 02:58:12 - INFO - utils.common - Using FlashAttention-2 for faster training and inference. +12/25/2023 02:58:12 - INFO - utils.common - Using FlashAttention-2 for faster training and inference. +12/25/2023 02:58:12 - INFO - utils.common - Using FlashAttention-2 for faster training and inference. +12/25/2023 02:58:12 - INFO - utils.common - Using FlashAttention-2 for faster training 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utils.common - Fine-tuning method: Full +trainable params: 13016038400 || all params: 13016038400 || trainable%: 100.0000 +length of tokenizer: 32017 +pad_token_id is: 32016 +trainable params: 13016038400 || all params: 13016038400 || trainable%: 100.0000 +length of tokenizer: 32017 +pad_token_id is: 32016 +trainable params: 13016038400 || all params: 13016038400 || trainable%: 100.0000 +length of tokenizer: 32017 +pad_token_id is: 32016 +ttrainable params: 13016038400 || all params: 13016038400 || trainable%: 100.0000 +length of tokenizer: 32017 +pad_token_id is: 32016 +trainable params: 13016038400 || all params: 13016038400 || trainable%: 100.0000 +length of tokenizer: 32017 +pad_token_id is: 32016 +trainable params: 13016038400 || all params: 13016038400 || trainable%: 100.0000 +length of tokenizer: 32017 +trainable params: 13016038400 || all params: 13016038400 || trainable%: 100.0000pad_token_id is: 32016 + +length of tokenizer: 32017 +pad_token_id is: 32016 +trainable params: 13016038400 || all params: 13016038400 || trainable%: 100.0000 +length of tokenizer: 32017 +pad_token_id is: 32016length of input_ids : +394 +input_ids: +[1, 518, 25580, 29962, 12148, 626, 355, 278, 15352, 5132, 2471, 577, 393, 372, 7805, 263, 525, 8000, 29915, 2425, 3265, 1135, 278, 5923, 525, 1454, 29915, 2425, 29892, 607, 4256, 1078, 1549, 278, 4452, 310, 385, 6043, 1051, 29889, 13, 13, 1576, 2471, 5279, 756, 263, 6494, 988, 372, 14734, 304, 1596, 385, 1203, 393, 338, 5377, 278, 1345length of input_ids : +394 +input_ids: +[1, 518, 25580, 29962, 12148, 626, 355, 278, 15352, 5132, 2471, 577, 393, 372, 7805, 263, 525, 8000, 29915, 2425, 3265, 1135, 278, 5923, 525, 1454, 29915, 2425, 29892, 607, 4256, 1078, 1549, 278, 4452, 310, 385, 6043, 1051, 29889, 13, 13, 1576, 2471, 5279, 756, 263, 6494, 988, 372, 14734, 304, 1596, 385, 1203, 393, 338, 5377, 278, 13451, 310, 278, 1051, 29889, 24778, 445, 1059, 322, 6623, 278, 2471, 304, 671, 525, 8000, 29915, 2012, 310, 525, 1454, 29915, 2425, 29889, 22521, 545, 596, 2471, 5149, 17766, 4069, 8857, 29889, 29871, 13, 13, 28956, 4691, 13, 29871, 396, 2661, 370, 1674, 385, 6043, 1051, 13, 29871, 3948, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29871, 396, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29871, 302, 353, 7431, 29898, 2749, 29897, 13, 13, 29871, 396, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 29871, 363, 474, 297, 3464, 29898, 29876, 29974, 29896, 1125, 13, 418, 1596, 29898, 2749, 29961, 29875, 2314, 13, 28956, 29961, 29914, 25580, 29962, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +length of input_ids : +394 +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +input_ids: +[1, 518, 25580, 29962, 12148, 626, 355, 278, 15352, 5132, 2471, 577, 393, 372, 7805, 263, 525, 8000, 29915, 2425, 3265, 1135, 278, 5923, 525, 1454, 29915, 2425, 29892, 607, 4256, 1078, 1549, 278, 4452, 310, 385, 6043, 1051, 29889, 13, 13, 1576, 2471, 5279, 756, 263, 6494, 988, 372, 14734, 304, 1596, 385, 1203, 393, 338, 5377, 278, 13451, 310, 278, 1051, 29889, 24778, 445, 1059, 322, 6623, 278, 2471, 304, 671, 525, 8000, 29915, 2012, 310, 525, 1454, 29915, 2425, 29889, 22521, 545, 596, 2471, 5149, 17766, 4069, 8857, 29889, 29871, 13, 13, 28956, 4691, 13, 29871, 396, 2661, 370, 1674, 385, 6043, 1051, 13, 29871, 3948, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29871, 396, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29871, 302, 353, 7431, 29898, 2749, 29897, 13, 13, 29871, 396, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 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2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +length of input_ids : +394 +input_ids: +[1, 518, 25580, 29962, 12148, 626, 355, 278, 15352, 5132, 2471, 577, 393, 372, 7805, 263, 525, 8000, 29915, 2425, 3265, 1135, 278, 5923, 525, 1454, 29915, 2425, 29892, 607, 4256, 1078, 1549, 278, 4452, 310, 385, 6043, 1051, 29889, 13, 13, 1576, 2471, 5279, 756, 263, 6494, 988, 372, 14734, 304, 1596, 385, 1203, 393, 338, 5377, 278, 13451, 310, 278, 1051, 29889, 24778, 445, 1059, 322, 6623, 278, 2471, 304, 671, 525, 8000, 29915, 2012, 310, 525, 1454, 29915, 2425, 29889, 22521, 545, 596, 2471, 5149, 17766, 4069, 8857, 29889, 29871, 13, 13, 28956, 4691, 13, 29871, 396, 2661, 370, 1674, 385, 6043, 1051, 13, 29871, 3948, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29871, 396, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29871, 302, 353, 7431, 29898, 2749, 29897, 13, 13, 29871, 396, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 29871, 363, 474, 297, 3464, 29898, 29876, 29974, 29896, 1125, 13, 418, 1596, 29898, 2749, 29961, 29875, 2314, 13, 28956, 29961, 29914, 25580, 29962, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 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18884, 736, 4331, 13, 9651, 363, 270, 297, 1583, 29889, 3972, 29889, 5975, 7295, 13, 18884, 302, 486, 29918, 3149, 353, 313, 3149, 29961, 29900, 10062, 29881, 29961, 29900, 1402, 1298, 29961, 29896, 10062, 29881, 29961, 29896, 2314, 13, 18884, 565, 1583, 29889, 7720, 29961, 29876, 486, 29918, 3149, 29962, 1275, 29871, 29900, 29901, 13, 462, 1678, 316, 802, 29889, 4397, 3552, 29876, 486, 29918, 3149, 29892, 4331, 29974, 29896, 876, 13, 462, 1678, 396, 2791, 16669, 2943, 408, 448, 29896, 13, 462, 1678, 1583, 29889, 7720, 29961, 29876, 486, 29918, 3149, 29962, 353, 448, 29896, 13, 28956, 13, 12148, 4443, 393, 366, 3282, 29915, 29873, 3867, 278, 421, 5756, 19203, 29952, 770, 29892, 8151, 366, 505, 304, 1207, 1854, 393, 445, 4413, 505, 1906, 421, 275, 8667, 1673, 421, 3068, 16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +length of input_ids : +394 +input_ids: +[1, 518, 25580, 29962, 12148, 626, 355, 278, 15352, 5132, 2471, 577, 393, 372, 7805, 263, 525, 8000, 29915, 2425, 3265, 1135, 278, 5923, 525, 1454, 29915, 2425, 29892, 607, 4256, 1078, 1549, 278, 4452, 310, 385, 6043, 1051, 29889, 13, 13, 1576, 2471, 5279, 756, 263, 6494, 988, 372, 14734, 304, 1596, 385, 1203, 393, 338, 5377, 278, 13451, 310, 278, 1051, 29889, 24778, 445, 1059, 322, 6623, 278, 2471, 304, 671, 525, 8000, 29915, 2012, 310, 525, 1454, 29915, 2425, 29889, 22521, 545, 596, 2471, 5149, 17766, 4069, 8857, 29889, 29871, 13, 13, 28956, 4691, 13, 29871, 396, 2661, 370, 1674, 385, 6043, 1051, 13, 29871, 3948, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29871, 396, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29871, 302, 353, 7431, 29898, 2749, 29897, 13, 13, 29871, 396, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 29871, 363, 474, 297, 3464, 29898, 29876, 29974, 29896, 1125, 13, 418, 1596, 29898, 2749, 29961, 29875, 2314, 13, 28956, 29961, 29914, 25580, 29962, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +length of input_ids : +394 +input_ids: +[1, 518, 25580, 29962, 12148, 626, 355, 278, 15352, 5132, 2471, 577, 393, 372, 7805, 263, 525, 8000, 29915, 2425, 3265, 1135, 278, 5923, 525, 1454, 29915, 2425, 29892, 607, 4256, 1078, 1549, 278, 4452, 310, 385, 6043, 1051, 29889, 13, 13, 1576, 2471, 5279, 756, 263, 6494, 988, 372, 14734, 304, 1596, 385, 1203, 393, 338, 5377, 278, 13451, 310, 278, 1051, 29889, 24778, 445, 1059, 322, 6623, 278, 2471, 304, 671, 525, 8000, 29915, 2012, 310, 525, 1454, 29915, 2425, 29889, 22521, 545, 596, 2471, 5149, 17766, 4069, 8857, 29889, 29871, 13, 13, 28956, 4691, 13, 29871, 396, 2661, 370, 1674, 385, 6043, 1051, 13, 29871, 3948, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29871, 396, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29871, 302, 353, 7431, 29898, 2749, 29897, 13, 13, 29871, 396, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 29871, 363, 474, 297, 3464, 29898, 29876, 29974, 29896, 1125, 13, 418, 1596, 29898, 2749, 29961, 29875, 2314, 13, 28956, 29961, 29914, 25580, 29962, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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18884, 736, 4331, 13, 9651, 363, 270, 297, 1583, 29889, 3972, 29889, 5975, 7295, 13, 18884, 302, 486, 29918, 3149, 353, 313, 3149, 29961, 29900, 10062, 29881, 29961, 29900, 1402, 1298, 29961, 29896, 10062, 29881, 29961, 29896, 2314, 13, 18884, 565, 1583, 29889, 7720, 29961, 29876, 486, 29918, 3149, 29962, 1275, 29871, 29900, 29901, 13, 462, 1678, 316, 802, 29889, 4397, 3552, 29876, 486, 29918, 3149, 29892, 4331, 29974, 29896, 876, 13, 462, 1678, 396, 2791, 16669, 2943, 408, 448, 29896, 13, 462, 1678, 1583, 29889, 7720, 29961, 29876, 486, 29918, 3149, 29962, 353, 448, 29896, 13, 28956, 13, 12148, 4443, 393, 366, 3282, 29915, 29873, 3867, 278, 421, 5756, 19203, 29952, 770, 29892, 8151, 366, 505, 304, 1207, 1854, 393, 445, 4413, 505, 1906, 421, 275, 8667, 1673, 421, 3068, 16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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tindShort€stPatn($elf` nn&s7er: 'GridM&s+er') -< 1rt: +self.o1r = {'U': [-1, 0]._'0': [1, 0}, 'L': [0,_-1]. 'R': {0, 1]} +selt.inv_d!r - {'V': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} +z€|f.grio = (ollectioms.defaultdic7(lambda:_flo4t('lnf']) +# DFS mark out the full map +s€|f.targe+ - Non€ +5elf.dfs((0, 0), m&st3r) +1f $eit,t4rget_is Rone: +retvrn -1 +H 8FS find the sn0rtes7 9@+h +neturr self.bfs((O, o)) + +det dfs(zelf, point, mas+en): +if_master,i5Target(): +self.target - poimt +# nnark visited node as O +ze|t,grid[point} = 0 +tor d in self,0in: +rxt_p0imt = (9oimt[0]+self.dir[o](0), pOint[1]+se|f.dir[0][i]] +if_master. int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +length of input_ids : +1212 +input_ids: +[1, 518, 25580, 29962, 29875, 29915, 345, 2355, 445, 3017, 775, 515, 385, 288, 7283, 5780, 29892, 541, 372, 29915, 29879, 451, 1985, 29889, 508, 366, 4744, 372, 363, 592, 29973, 13, 1990, 29871, 29945, 324, 29894, 29955, 29991, 265, 29901, 13, 29877, 300, 260, 513, 21322, 30181, 303, 11457, 29876, 1566, 761, 29952, 302, 29876, 29987, 29879, 29955, 261, 29901, 525, 5756, 29924, 29987, 29879, 29974, 261, 1495, 448, 29966, 29871, 29896, 2273, 29901, 13, 1311, 29889, 29877, 29896, 29878, 353, 11117, 29965, 2396, 21069, 29896, 29892, 29871, 29900, 1822, 29918, 29915, 29900, 2396, 518, 29896, 29892, 29871, 29900, 1118, 525, 29931, 2396, 518, 29900, 29892, 29918, 29899, 29896, 1822, 525, 29934, 2396, 426, 29900, 29892, 29871, 29896, 12258, 13, 29879, 2152, 29889, 11569, 29918, 29881, 29991, 29878, 448, 11117, 29963, 2396, 525, 29928, 742, 525, 29928, 2396, 525, 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1678, 316, 802, 29889, 4397, 3552, 29876, 486, 29918, 3149, 29892, 4331, 29974, 29896, 876, 13, 462, 1678, 396, 2791, 16669, 2943, 408, 448, 29896, 13, 462, 1678, 1583, 29889, 7720, 29961, 29876, 486, 29918, 3149, 29962, 353, 448, 29896, 13, 28956, 13, 12148, 4443, 393, 366, 3282, 29915, 29873, 3867, 278, 421, 5756, 19203, 29952, 770, 29892, 8151, 366, 505, 304, 1207, 1854, 393, 445, 4413, 505, 1906, 421, 275, 8667, 1673, 421, 3068, 16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +length of input_ids : +1212 +input_ids: +[1, 518, 25580, 29962, 29875, 29915, 345, 2355, 445, 3017, 775, 515, 385, 288, 7283, 5780, 29892, 541, 372, 29915, 29879, 451, 1985, 29889, 508, 366, 4744, 372, 363, 592, 29973, 13, 1990, 29871, 29945, 324, 29894, 29955, 29991, 265, 29901, 13, 29877, 300, 260, 513, 21322, 30181, 303, 11457, 29876, 1566, 761, 29952, 302, 29876, 29987, 29879, 29955, 261, 29901, 525, 5756, 29924, 29987, 29879, 29974, 261, 1495, 448, 29966, 29871, 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self.0in.valves(): +nxt_point_- (p0int[0]Td[O}, 9o1nt[1]+d[1]} +it_self,9rid[nxt_poin+) == 0: +d€que,appeno((nxt_qoint, s7ep+i)) +# m@rx vis!+ed node az -1 +self,gnid[nxt_point) = -1[/INST] There are several issues with your code like flaky names, wrong Python syntax etc. + +Here is how that code should look: + +```python +import collections + +class Solution: + def findShortestPath(self, master: 'GridMaster') -> int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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1673, 421, 3068, 16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] 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There are several issues with your code like flaky names, wrong Python syntax etc. + +Here is how that code should look: + +```python +import collections + +class Solution: + def findShortestPath(self, master: 'GridMaster') -> int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir8667, 7295, 13, 9651, 1583, 29889, 5182, 353, 1298, 13, 4706, 396, 2791, 16669, 2943, 408, 29871, 29900, 13, 4706, 1583, 29889, 7720, 29961, 3149, 29962, 353, 29871, 29900, 13, 4706, 363, 270, 297, 1583, 29889, 3972, 29901, 13, 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'R': {0, 1]} +selt.inv_d!r - {'V': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} +z€|f.grio = (ollectioms.defaultdic7(lambda:_flo4t('lnf']) +# DFS mark out the full map +s€|f.targe+ - Non€ +5elf.dfs((0, 0), m&st3r) +1f $eit,t4rget_is Rone: +retvrn -1 +H 8FS find the sn0rtes7 9@+h +neturr self.bfs((O, o)) + +det dfs(zelf, point, mas+en): +if_master,i5Target(): +self.target - poimt +# nnark visited node as O +ze|t,grid[point} = 0 +tor d in self,0in: +rxt_p0imt = (9oimt[0]+self.dir[o](0), pOint[1]+se|f.dir[0][i]] +if_master. int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class,labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAlabel_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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4489, 29879, 29898, 1311, 29892, 1298, 29892, 5835, 1125, 13, 4706, 565, 5835, 29889, 275, 8667, 7295, 13, 9651, 1583, 29889, 5182, 353, 1298, 13, 4706, 396, 2791, 16669, 2943, 408, 29871, 29900, 13, 4706, 1583, 29889, 7720, 29961, 3149, 29962, 353, 29871, 29900, 13, 4706, 363, 270, 297, 1583, 29889, 3972, 29901, 13, 9651, 302, 486, 29918, 3149, 353, 313, 3labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] 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[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [inputs: + [INST]i've got this python code from an ocr tool, but it's not working. can you debug it for me? +class 5olv7!on: +oet tindShort€stPatn($elf` nn&s7er: 'GridM&s+er') -< 1rt: +self.o1r = {'U': [-1, 0]._'0': [1, 0}, 'L': [0,_-1]. 'R': {0, 1]} +selt.inv_d!r - {'V': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} +z€|f.grio = (ollectioms.defaultdic7(lambda:_flo4t('lnf']) +# DFS mark out the full map +s€|f.targe+ - Non€ +5elf.dfs((0, 0), m&st3r) +1f $eit,t4rget_is Rone: +retvrn -1 +H 8FS find the sn0rtes7 9@+h +neturr self.bfs((O, o)) + +det dfs(zelf, point, mas+en): +if_master,i5Target(): +self.target - poimt +# nnark visited node as O +ze|t,grid[point} = 0 +tor d in self,0in: +rxt_p0imt = (9oimt[0]+self.dir[o](0), pOint[1]+se|f.dir[0][i]] +if_master. int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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'R': {0, 1]} +selt.inv_d!r - {'V': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} +z€|f.grio = (ollectioms.defaultdic7(lambda:_flo4t('lnf']) +# DFS mark out the full map +s€|f.targe+ - Non€ +5elf.dfs((0, 0), m&st3r) +1f $eit,t4rget_is Rone: +retvrn -1 +H 8FS find the sn0rtes7 9@+h +neturr self.bfs((O, o)) + +det dfs(zelf, point, mas+en): +if_master,i5Target(): +self.target - poimt +# nnark visited node as O +ze|t,grid[point} = 0 +tor d in self,0in: +rxt_p0imt = (9oimt[0]+self.dir[o](0), pOint[1]+se|f.dir[0][i]] +if_master. int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +inputs: + [INST]i've got this python code from an ocr tool, but it's not working. can you debug it for me? +class 5olv7!on: +oet tindShort€stPatn($elf` nn&s7er: 'GridM&s+er') -< 1rt: +self.o1r = {'U': [-1, 0]._'0': [1, 0}, 'L': [0,_-1]. 'R': {0, 1]} +selt.inv_d!r - {'V': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} +z€|f.grio = (ollectioms.defaultdic7(lambda:_flo4t('lnf']) +# DFS mark out the full map +s€|f.targe+ - Non€ +5elf.dfs((0, 0), m&st3r) +1f $eit,t4rget_is Rone: +retvrn -1 +H 8FS find the sn0rtes7 9@+h +neturr self.bfs((O, o)) + +det dfs(zelf, point, mas+en): +if_master,i5Target(): +self.target - poimt +# nnark visited node as O +ze|t,grid[point} = 0 +tor d in self,0in: +rxt_p0imt = (9oimt[0]+self.dir[o](0), pOint[1]+se|f.dir[0][i]] +if_master. int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] 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[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] There are several issues with your code like flaky names, wrong Python syntax etc. + +Here is how that code should look: + +```python +import collections + +class Solution: + def findShortestPath(self, master: 'GridMaster') -> int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] 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[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] There are several issues with your code like flaky names, wrong Python syntax etc. + +Here is how that code should look: + +```python +import collections + +class Solution: + def findShortestPath(self, master: 'GridMaster') -> int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +length of input_ids : +1212 +input_ids: +[1, 518, 25580, 29962, 29875, 29915, 345, 2355, 445, 3017, 775, 515, 385, 288, 7283, 5780, 29892, 541, 372, 29915, 29879, 451, 1985, 29889, 508, 366, 4744, 372, 363, 592, 29973, 13, 1990, 29871, 29945, 324, 29894, 29955, 29991, 265, 29901, 13, 29877, 300, 260, 513, 21322, 30181, 303, 11457, 29876, 1566, 761, 29952, 302, 29876, 29987, 29879, 29955, 261, 29901, 525, 5756, 29924, 29987, 29879, 29974, 261, 1495, 448, 29966, 29871, 29896, 2273, 29901, 13, 1311, 29889, 29877, 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29900, 1402, 525, 29931, 2396, 518, 29900, 6653, 29896, 1402, 525, 29934, 2396, 518, 29900, 29892, 29871, 29896, 12258, 13, 4706, 1583, 29889, 11569, 29918, 3972, 353, 11117, 29965, 2396, 525, 29928, 742, 525, 29928, 2396, 525, 29965, 742, 525, 29931, 2396, 525, 29934, 742, 525, 29934, 2396, 525, 29931, 10827, 13, 4706, 1583, 29889, 7720, 353, 16250, 29889, 4381, 8977, 29898, 2892, 29901, 7411, 877, 7192, 8785, 13, 4706, 396, 360, 9998, 2791, 714, 278, 2989, 2910, 13, 4706, 1583, 29889, 5182, 353, 6213, 13, 4706, 1583, 29889, 29069, 3552, 29900, 29892, 29871, 29900, 511, 5835, 29897, 13, 4706, 565, 1583, 29889, 5182, 338, 6213, 29901, 13, 9651, 736, 448, 29896, 13, 4706, 396, 350, 9998, 1284, 278, 3273, 342, 2224, 13, 4706, 736, 1583, 29889, 1635, 29879, 3552, 29900, 29892, 29871, 29900, 876, 13, 13, 1678, 822, 4489, 29879, 29898, 1311, 29892, 1298, 29892, 5835, 1125, 13, 4706, 565, 5835, 29889, 275, 8667, 7295, 13, 9651, 1583, 29889, 5182, 353, 1298, 13, 4706, 396, 2791, 16669, 2943, 408, 29871, 29900, 13, 4706, 1583, 29889, 7720, 29961, 3149, 29962, 353, 29871, 29900, 13, 4706, 363, 270, 297, 1583, 29889, 3972, 29901, 13, 9651, 302, 486, 29918, 3149, 353, 313, 3149, 29961, 29900, 10062, 1311, 29889, 3972, 29961, 29881, 3816, 29900, 1402, 1298, 29961, 29896, 10062, 1311, 29889, 3972, 29961, 29881, 3816, 29896, 2314, 13, 9651, 565, 5835, 29889, 3068, 16619, 29898, 29881, 29897, 322, 1583, 29889, 7720, 29961, 29876, 486, 29918, 3149, 29962, 1275, 5785, 877, 7192, 29374, 13, 18884, 5835, 29889, 11631, 29898, 29881, 29897, 13, 18884, 1583, 29889, 29069, 29898, 29876, 486, 29918, 3149, 29892, 5835, 29897, 13, 18884, 5835, 29889, 11631, 29898, 1311, 29889, 11569, 29918, 3972, 29961, 29881, 2314, 13, 13, 1678, 822, 289, 5847, 29898, 1311, 29892, 1369, 1125, 13, 4706, 316, 802, 353, 16250, 29889, 311, 802, 4197, 29898, 2962, 29892, 29871, 29900, 29897, 2314, 13, 4706, 1550, 316, 802, 29901, 13, 9651, 1298, 29892, 4331, 353, 316, 802, 29889, 7323, 1563, 580, 13, 9651, 565, 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debug it for me? +class 5olv7!on: +oet tindShort€stPatn($elf` nn&s7er: 'GridM&s+er') -< 1rt: +self.o1r = {'U': [-1, 0]._'0': [1, 0}, 'L': [0,_-1]. 'R': {0, 1]} +selt.inv_d!r - {'V': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} +z€|f.grio = (ollectioms.defaultdic7(lambda:_flo4t('lnf']) +# DFS mark out the full map +s€|f.targe+ - Non€ +5elf.dfs((0, 0), m&st3r) +1f $eit,t4rget_is Rone: +retvrn -1 +H 8FS find the sn0rtes7 9@+h +neturr self.bfs((O, o)) + +det dfs(zelf, point, mas+en): +if_master,i5Target(): +self.target - poimt +# nnark visited node as O +ze|t,grid[point} = 0 +tor d in self,0in: +rxt_p0imt = (9oimt[0]+self.dir[o](0), pOint[1]+se|f.dir[0][i]] +if_master. int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] 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[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] There are several issues with your code like flaky names, wrong Python syntax etc. + +Here is how that code should look: + +```python +import collections + +class Solution: + def findShortestPath(self, master: 'GridMaster') -> int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +length of input_ids : +1212 +input_ids: +[1, 518, 25580, 29962, 29875, 29915, 345, 2355, 445, 3017, 775, 515, 385, 288, 7283, 5780, 29892, 541, 372, 29915, 29879, 451, 1985, 29889, 508, 366, 4744, 372, 363, 592, 29973, 13, 1990, 29871, 29945, 324, 29894, 29955, 29991, 265, 29901, 13, 29877, 300, 260, 513, 21322, 30181, 303, 11457, 29876, 1566, 761, 29952, 302, 29876, 29987, 29879, 29955, 261, 29901, 525, 5756, 29924, 29987, 29879, 29974, 261, 1495, 448, 29966, 29871, 29896, 2273, 29901, 13, 1311, 29889, 29877, 29896, 29878, 353, 11117, 29965, 2396, 21069, 29896, 29892, 29871, 29900, 1822, 29918, 29915, 29900, 2396, 518, 29896, 29892, 29871, 29900, 1118, 525, 29931, 2396, 518, 29900, 29892, 29918, 29899, 29896, 1822, 525, 29934, 2396, 426, 29900, 29892, 29871, 29896, 12258, 13, 29879, 2152, 29889, 11569, 29918, 29881, 29991, 29878, 448, 11117, 29963, 2396, 525, 29928, 742, 525, 29928, 2396, 525, 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7411, 877, 7192, 8785, 13, 4706, 396, 360, 9998, 2791, 714, 278, 2989, 2910, 13, 4706, 1583, 29889, 5182, 353, 6213, 13, 4706, 1583, 29889, 29069, 3552, 29900, 29892, 29871, 29900, 511, 5835, 29897, 13, 4706, 565, 1583, 29889, 5182, 338, 6213, 29901, 13, 9651, 736, 448, 29896, 13, 4706, 396, 350, 9998, 1284, 278, 3273, 342, 2224, 13, 4706, 736, 1583, 29889, 1635, 29879, 3552, 29900, 29892, 29871, 29900, 876, 13, 13, 1678, 822, 4489, 29879, 29898, 1311, 29892, 1298, 29892, 5835, 1125, 13, 4706, 565, 5835, 29889, 275, 8667, 7295, 13, 9651, 1583, 29889, 5182, 353, 1298, 13, 4706, 396, 2791, 16669, 2943, 408, 29871, 29900, 13, 4706, 1583, 29889, 7720, 29961, 3149, 29962, 353, 29871, 29900, 13, 4706, 363, 270, 297, 1583, 29889, 3972, 29901, 13, 9651, 302, 486, 29918, 3149, 353, 313, 3149, 29961, 29900, 10062, 1311, 29889, 3972, 29961, 29881, 3816, 29900, 1402, 1298, 29961, 29896, 10062, 1311, 29889, 3972, 29961, 29881, 3816, 29896, 2314, 13, 9651, 565, 5835, 29889, 3068, 16619, 29898, 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1678, 316, 802, 29889, 4397, 3552, 29876, 486, 29918, 3149, 29892, 4331, 29974, 29896, 876, 13, 462, 1678, 396, 2791, 16669, 2943, 408, 448, 29896, 13, 462, 1678, 1583, 29889, 7720, 29961, 29876, 486, 29918, 3149, 29962, 353, 448, 29896, 13, 28956, 13, 12148, 4443, 393, 366, 3282, 29915, 29873, 3867, 278, 421, 5756, 19203, 29952, 770, 29892, 8151, 366, 505, 304, 1207, 1854, 393, 445, 4413, 505, 1906, 421, 275, 8667, 1673, 421, 3068, 16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +inputs: + [INST]i've got this python code from an ocr tool, but it's not working. can you debug it for me? +class 5olv7!on: +oet tindShort€stPatn($elf` nn&s7er: 'GridM&s+er') -< 1rt: +self.o1r = {'U': [-1, 0]._'0': [1, 0}, 'L': [0,_-1]. 'R': {0, 1]} +selt.inv_d!r - {'V': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} +z€|f.grio = (ollectioms.defaultdic7(lambda:_flo4t('lnf']) +# DFS mark out the full map +s€|f.targe+ - Non€ +5elf.dfs((0, 0), m&st3r) +1f $eit,t4rget_is Rone: +retvrn -1 +H 8FS find the sn0rtes7 9@+h +neturr self.bfs((O, o)) + +det dfs(zelf, point, mas+en): +if_master,i5Target(): +self.target - poimt +# nnark visited node as O +ze|t,grid[point} = 0 +tor d in self,0in: +rxt_p0imt = (9oimt[0]+self.dir[o](0), pOint[1]+se|f.dir[0][i]] +if_master. int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +length of input_ids : +394 +input_ids: +[1, 518, 25580, 29962, 12148, 626, 355, 278, 15352, 5132, 2471, 577, 393, 372, 7805, 263, 525, 8000, 29915, 2425, 3265, 1135, 278, 5923, 525, 1454, 29915, 2425, 29892, 607, 4256, 1078, 1549, 278, 4452, 310, 385, 6043, 1051, 29889, 13, 13, 1576, 2471, 5279, 756, 263, 6494, 988, 372, 14734, 304, 1596, 385, 1203, 393, 338, 5377, 278, 13451, 310, 278, 1051, 29889, 24778, 445, 1059, 322, 6623, 278, 2471, 304, 671, 525, 8000, 29915, 2012, 310, 525, 1454, 29915, 2425, 29889, 22521, 545, 596, 2471, 5149, 17766, 4069, 8857, 29889, 29871, 13, 13, 28956, 4691, 13, 29871, 396, 2661, 370, 1674, 385, 6043, 1051, 13, 29871, 3948, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29871, 396, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29871, 302, 353, 7431, 29898, 2749, 29897, 13, 13, 29871, 396, 3201, 3901, 278, 1051, 322, 1962, 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2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421length of input_ids : +394 +input_ids: +[1, 518, 25580, 29962, 12148, 626, 355, 278, 15352, 5132, 2471, 577, 393, 372, 7805, 263, 525, 8000, 29915, 2425, 3265, 1135, 278, 5923, 525, 1454, 29915, 2425, 29892, 607, 4256, 1078, 1549, 278, 4452, 310, 385, 6043, 1051, 29889, 13, 13, 1576, 2471, 5279, 756, 263, 6494, 988, 372, 14734, 304, 1596, 385, 1203, 393, 338, 5377, 278, 13451, 310, 278, 1051, 29889, 24778, 445, 1059, 322, 6623, 278, 2471, 304, 671, 525, 8000, 29915, 2012, 310, 525, 1454, 29915, 2425, 29889, 22521, 545, 596, 2471, 5149, 17766, 4069, 8857, 29889, 29871, 13, 13, 28956, 4691, 13, 29871, 396, 2661, 370, 1674, 385, 6043, 1051, 13, 29871, 3948, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29871, 396, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29871, 302, 353, 7431, 29898, 2749, 29897, 13, 13, 29871, 396, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 29871, 363, 474, 297, 3464, 29898, 29876, 29974, 29896, 1125, 13, 418, 1596, 29898, 2749, 29961, 29875, 2314, 13, 28956, 29961, 29914, 25580, 29962, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +inputs: + [INST]Please amend the subsequent Python script so that it includes a 'while' loop rather than the existing 'for' loop, which iterates through the items of an integer list. + +The script currently has a bug where it attempts to print an object that is outside the bounds of the list. Fix this error and modify the script to use 'while' instead of 'for' loop. Ensure your script correctly handles empty lists. + +```python + # Establish an integer list + arr = [1, 2, 3, 4] + + # Determine the length of the list + n = len(arr) + + # Traverse the list and output each individual element + for i in range(n+1): + print(arr[i]) +```[/INST] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 7521, 4691, 13, 29937, 2661, 370, 1674, 385, 6043, 1051, 13, 2749, 353, 518, 29896, 29892, 29871, 29906, 29892, 29871, 29941, 29892, 29871, 29946, 29962, 13, 13, 29937, 5953, 837, 457, 278, 3309, 310, 278, 1051, 13, 29876, 353, 7431, 29898, 2749, 29897, 13, 13, 29937, 25455, 2380, 472, 29871, 29900, 13, 29875, 353, 29871, 29900, 13, 13, 29937, 3201, 3901, 278, 1051, 322, 1962, 1269, 5375, 1543, 13, 8000, 474, 529, 302, 29901, 13, 1678, 1596, 29898, 2749, 29961, 29875, 2314, 13, 1678, 474, 4619, 29871, 29896, 13, 28956, 13, 797, 278, 2183, 775, 29892, 372, 14335, 304, 2130, 421, 2749, 29961, 29876, 7961, 607, 338, 714, 310, 13451, 408, 3017, 1051, 26190, 8665, 515, 29871, 29900, 322, 10614, 472, 302, 29899, 29896, 363, 263, 1051, 310, 3309, 302, 29889, 13, 17351, 29892, 306, 1304, 421, 8000, 29952, 2425, 408, 639, 596, 2009, 29889, 2648, 2847, 5281, 421, 29875, 29922, 29900, 29952, 1434, 278, 2425, 322, 421, 29875, 4619, 29871, 29896, 29952, 2629, 278, 2425, 29892, 591, 508, 13649, 975, 278, 1051, 29889, 910, 12541, 18172, 2745, 421, 29875, 29952, 338, 3109, 1135, 421, 29876, 1673, 278, 3309, 310, 278, 1051, 29889, 450, 421, 8000, 29952, 2425, 674, 451, 8469, 565, 278, 1051, 338, 4069, 577, 372, 5149, 17766, 4069, 8857, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] ```python +# Establish an integer list +arr = [1, 2, 3, 4] + +# Determine the length of the list +n = len(arr) + +# Initialize index at 0 +i = 0 + +# Traverse the list and output each individual element +while i < n: + print(arr[i]) + i += 1 +``` +In the given code, it tries to access `arr[n]` which is out of bounds as python list indexing starts from 0 and ends at n-1 for a list of length n. +Also, I used `while` loop as per your request. By initializing `i=0` before the loop and `i += 1` within the loop, we can iterate over the list. This iteration continues until `i` is less than `n`, the length of the list. The `while` loop will not proceed if the list is empty so it correctly handles empty lists. +length of input_ids : +1212 +input_ids: +[1, 518, 25580, 29962, 29875, 29915, 345, 2355, 445, 3017, 775, 515, 385, 288, 7283, 5780, 29892, 541, 372, 29915, 29879, 451, 1985, 29889, 508, 366, 4744, 372, 363, 592, 29973, 13, 1990, 29871, 29945, 324, 29894, 29955, 29991, 265, 29901, 13, 29877, 300, 260, 513, 21322, 30181, 303, 11457, 29876, 1566, 761, 29952, 302, 29876, 29987, 29879, 29955, 261, 29901, 525, 5756, 29924, 29987, 29879, 29974, 261, 1495, 448, 29966, 29871, 29896, 2273, 29901, 13, 1311, 29889, 29877, 29896, 29878, 353, 11117, 29965, 2396, 21069, 29896, 29892, 29871, 29900, 1822, 29918, 29915, 29900, 2396, 518, 29896, 29892, 29871, 29900, 1118, 525, 29931, 2396, 518, 29900, 29892, 29918, 29899, 29896, 1822, 525, 29934, 2396, 426, 29900, 29892, 29871, 29896, 12258, 13, 29879, 2152, 29889, 11569, 29918, 29881, 29991, 29878, 448, 11117, 29963, 2396, 525, 29928, 742, 525, 29928, 2396, 525, 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1678, 316, 802, 29889, 4397, 3552, 29876, 486, 29918, 3149, 29892, 4331, 29974, 29896, 876, 13, 462, 1678, 396, 2791, 16669, 2943, 408, 448, 29896, 13, 462, 1678, 1583, 29889, 7720, 29961, 29876, 486, 29918, 3149, 29962, 353, 448, 29896, 13, 28956, 13, 12148, 4443, 393, 366, 3282, 29915, 29873, 3867, 278, 421, 5756, 19203, 29952, 770, 29892, 8151, 366, 505, 304, 1207, 1854, 393, 445, 4413, 505, 1906, 421, 275, 8667, 1673, 421, 3068, 16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +inputs: + [INST]i've got this python code from an ocr tool, but it's not working. can you debug it for me? +class 5olv7!on: +oet tindShort€stPatn($elf` nn&s7er: 'GridM&s+er') -< 1rt: +self.o1r = {'U': [-1, 0]._'0': [1, 0}, 'L': [0,_-1]. 'R': {0, 1]} +selt.inv_d!r - {'V': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} +z€|f.grio = (ollectioms.defaultdic7(lambda:_flo4t('lnf']) +# DFS mark out the full map +s€|f.targe+ - Non€ +5elf.dfs((0, 0), m&st3r) +1f $eit,t4rget_is Rone: +retvrn -1 +H 8FS find the sn0rtes7 9@+h +neturr self.bfs((O, o)) + +det dfs(zelf, point, mas+en): +if_master,i5Target(): +self.target - poimt +# nnark visited node as O +ze|t,grid[point} = 0 +tor d in self,0in: +rxt_p0imt = (9oimt[0]+self.dir[o](0), pOint[1]+se|f.dir[0][i]] +if_master. int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, step = deque.popleft() + if point == self.target: + return step + for d in self.dir.values(): + nxt_point = (point[0]+d[0], point[1]+d[1]) + if self.grid[nxt_point] == 0: + deque.append((nxt_point, step+1)) + # mark visited node as -1 + self.grid[nxt_point] = -1 +``` +Please note that you didn't provide the `GridMaster` class, hence you have to make sure that this classes have those `isTarget`, `canMove` and `move` methods in order this code to work. +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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16619, 29952, 322, 421, 11631, 29952, 3519, 297, 1797, 445, 775, 304, 664, 29889, 2] +labels: +[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] 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[PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] There are several issues with your code like flaky names, wrong Python syntax etc. + +Here is how that code should look: + +```python +import collections + +class Solution: + def findShortestPath(self, master: 'GridMaster') -> int: + self.dir = {'U': [-1, 0],'D': [1, 0], 'L': [0,-1], 'R': [0, 1]} + self.inv_dir = {'U': 'D', 'D': 'U', 'L': 'R', 'R': 'L'} + self.grid = collections.defaultdict(lambda:float('inf')) + # DFS mark out the full map + self.target = None + self.dfs((0, 0), master) + if self.target is None: + return -1 + # BFS find the shortest path + return self.bfs((0, 0)) + + def dfs(self, point, master): + if master.isTarget(): + self.target = point + # mark visited node as 0 + self.grid[point] = 0 + for d in self.dir: + nxt_point = (point[0]+self.dir[d][0], point[1]+self.dir[d][1]) + if master.canMove(d) and self.grid[nxt_point] == float('inf'): + master.move(d) + self.dfs(nxt_point, master) + master.move(self.inv_dir[d]) + + def bfs(self, start): + deque = collections.deque([(start, 0)]) + while deque: + point, s12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:2 to store for rank: 27 +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:2 to store for rank: 26 +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:2 to store for rank: 30 +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:2 to store for rank: 29 +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:2 to store for rank: 24 +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:2 to store for rank: 28 +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:2 to store for rank: 25 +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Added key: store_based_barrier_key:2 to store for rank: 31 +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Rank 26: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Rank 28: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Rank 31: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Rank 25: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Rank 30: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +vc-816648075-20231223-fb73dac2-worker-3:6099:7064 [4] NCCL INFO Using n12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Rank 9: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +12/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Rank 10: Completed store-based barvc-816648075-20231223-fb73dac2-worker-3:6101:7068 [6] vc-816648075-20231223-fb73dac2-worker-1:5960:6967 [1] NCCL INFO Using network IB +vc-816648075-202312vc-816648075-20231223-fb73dac2-worker-2:5779:6753 [7] NCCL INF12/25/2023 02:58:5412/25/2023 02:58:55 - INFO - torch.distributed.distributed_c10d - Rank 20: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +12/25/2023 02:58:55 - INFO - torch.distributed.distributed_c10d - Rank 16: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +12/25/2012/25/2023 02:58:54 - INFO - torch.distributed.distributed_c10d - Rank 27: Completed store-based barrier for key:store_based_barrier_key:2 with 32 nodes. +vc-816648075-20231223-fb73dac2-worker-3:6098:7071 [3] NCCL INFO Using network IB +vc-816648075-20231223-fb73dac2-worker-3:6102:7065 [7] NCCL INFO Setting affinity for GPU 7 to ffffffff,ffff0000,00000000,ffffffff,ffff0000,00000000 +vc-816648075-20231223-fb73dac2-worker-3:6096:7067 [1] NCCL INFO Setting affinity for GPU 1 to ffff,ffffffff,00000000,0000ffff,ffffffff +vc-816648075-20231223-fb73dac2-worker-3:6101:7068 [6] NCCL INFO Setting affinity for GPvc-816648075-20231223-fb73dac2-worker-1:5961:6968 [2] NCCL INvc-816648075-20231223-fb73dac2-worker-3:6097:7066 [2] NCCL INFO Setting afvc-816648075-20231223-fb73dac2-worker-1:5965:6969 [6] NCCL INvc-816648075-20231223-fb73dac2-worker-3:6098:7071 [3] NCCL INFO Setting affinity for GPvc-816648075-20231223-fb73dac2-worker-1:5959:6965 [0] NCCL INFO Setting affinity for GPU 0 to ffff,ffffffff,00000000,0000ffff,ffffffff +vc-816648075-20231223-fb73dac2-worker-1:5966:6971 [7] NCCL INFO Setting affinity for GPU 7 to ffffffff,ffff0000,00000000,ffffffff,ffff0000,00000000 +vc-816648075-20231223-fb73dac2-worker-1:5960:6967 [1] NCCL INFO Setting affinity for GPU 1 to 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Saving /group/20025/jiuding/ckpt/final/checkpoint-824/global_step824/bf16_zero_pp_rank_24_mp_rank_00_optim_states.pt... +[2023-12-25 06:38:02,019] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved /group/20025/jiuding/ckpt/final/checkpoint-824/global_step824/bf16_zero_pp_rank_24_mp_rank_00_optim_states.pt. +[2023-12-25 06:38:02,020] [INFO] [engine.py:3285:_save_zero_checkpoint] zero checkpoint saved /group/20025/jiuding/ckpt/final/checkpoint-824/global_step824/bf16_zero_pp_rank_24_mp_rank_00_optim_states.pt +[2023-12-25 06:38:03,234] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step824 is ready now! +{'loss': 0.4588, 'learning_rate': 9.885624120581772e-06, 'epoch': 1.01} +{'loss': 0.4106, 'learning_rate': 9.695038294198588e-06, 'epoch': 1.02} +{'loss': 0.4155, 'learning_rate': 9.504563287647265e-06, 'epoch': 1.03} +{'loss': 0.4123, 'learning_rate': 9.314268317514023e-06, 'epoch': 1.04} +{'loss': 0.4064, 'learning_rate': 9.12422253496175e-06, 'epoch': 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/group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/zero_pp_rank_24_mp_rank_00_model_states.pt. +[2023-12-25 10:16:40,088] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving /group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/bf16_zero_pp_rank_24_mp_rank_00_optim_states.pt... +[2023-12-25 10:16:52,102] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved /group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/bf16_zero_pp_rank_24_mp_rank_00_optim_states.pt. +[2023-12-25 10:16:52,102] [INFO] [engine.py:3285:_save_zero_checkpoint] zero checkpoint saved /group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/bf16_zero_pp_rank_24_mp_rank_00_optim_states.pt +[2023-12-25 10:16:53,635] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1648 is ready now! +{'train_runtime': 26273.024, 'train_samples_per_second': 16.064, 'train_steps_per_second': 0.063, 'train_loss': 0.45895221019254145, 'epoch': 2.0} 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/group/20025/jiuding/ckpt/final/checkpoint-824/global_step824/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2023-12-25 06:38:02,431] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved /group/20025/jiuding/ckpt/final/checkpoint-824/global_step824/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2023-12-25 06:38:02,440] [INFO] [engine.py:3285:_save_zero_checkpoint] zero checkpoint saved /group/20025/jiuding/ckpt/final/checkpoint-824/global_step824/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2023-12-25 06:38:03,248] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step824 is ready now! +{'loss': 0.4588, 'learning_rate': 9.885624120581772e-06, 'epoch': 1.01} +{'loss': 0.4106, 'learning_rate': 9.695038294198588e-06, 'epoch': 1.02} +{'loss': 0.4155, 'learning_rate': 9.504563287647265e-06, 'epoch': 1.03} +{'loss': 0.4123, 'learning_rate': 9.314268317514023e-06, 'epoch': 1.04} +{'loss': 0.4064, 'learning_rate': 9.12422253496175e-06, 'epoch': 1.06} 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+[2023-12-25 10:16:40,010] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving /group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/zero_pp_rank_0_mp_rank_00_model_states.pt... +[2023-12-25 10:16:40,036] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved /group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/zero_pp_rank_0_mp_rank_00_model_states.pt. +[2023-12-25 10:16:40,082] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving /group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2023-12-25 10:16:52,654] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved /group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2023-12-25 10:16:52,661] [INFO] [engine.py:3285:_save_zero_checkpoint] zero checkpoint saved /group/20025/jiuding/ckpt/final/checkpoint-1648/global_step1648/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2023-12-25 10:16:53,629] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1648 is ready now! +{'train_runtime': 26272.8035, 'train_samples_per_second': 16.064, 'train_steps_per_second': 0.063, 'train_loss': 0.4584712987964593, 'epoch': 2.0} +***** train metrics ***** + epoch = 2.0 + train_loss = 0.4585 + train_runtime = 7:17:52.80 + train_samples_per_second = 16.064 + train_steps_per_second = 0.063 +12/25/2023 10:17:38 - INFO - matplotlib.font_manager - generated new fontManager +Figure saved: /group/20025/jiuding/ckpt/final/training_loss.svg +12/25/2023 10:17:38 - WARNING - utils.other - No metric eval_loss to plot.