diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/8k-100.sh b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/8k-100.sh new file mode 100644 index 0000000000000000000000000000000000000000..8d9b97b199e7c142854d19591c9f17b7c6903d33 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/8k-100.sh @@ -0,0 +1,65 @@ +FLAME_PATH=/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame +DATASET_ROOT=/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset +TOKENIZER=/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer + +cd $FLAME_PATH +source .venv/bin/activate + +# =========== train config =========== +CONFIG=${1:-transformer_340M.json} +SEQ_LEN=8192 +WARMUP_STEPS=100 +STEPS=95366 +LR=3e-4 +BATCH_SIZE=16 +DECAY_TYPE=linear +DECAY_RATIO=1 + +NNODE=1 +NGPU=8 +LOG_RANK=0 +# ==================================== + +# if jq command is not found, install it +if ! command -v jq &> /dev/null; then + echo "jq could not be found, installing it..." + sudo yum install -y jq +fi + +EXP_NAME=$(basename $CONFIG | sed 's/\.config//')-ctx${SEQ_LEN}-steps${STEPS}-lr${LR}-decay_type${DECAY_TYPE}-decay_ratio${DECAY_RATIO}-bs${BATCH_SIZE}-nn${NNODE} + +bash train.sh \ + --job.config_file flame/models/fla.toml \ + --job.dump_folder $FLAME_PATH/exp/$EXP_NAME \ + --model.config $FLAME_PATH/configs/$CONFIG \ + --model.tokenizer_path $TOKENIZER \ + --optimizer.name AdamW \ + --optimizer.eps 1e-8 \ + --optimizer.lr $LR \ + --lr_scheduler.warmup_steps $WARMUP_STEPS \ + --lr_scheduler.lr_min 0.01 \ + --lr_scheduler.decay_type $DECAY_TYPE \ + --lr_scheduler.decay_ratio $DECAY_RATIO \ + --training.batch_size $BATCH_SIZE \ + --training.seq_len $SEQ_LEN \ + --training.context_len $SEQ_LEN \ + --training.gradient_accumulation_steps 1 \ + --training.steps $STEPS \ + --training.max_norm 1.0 \ + --training.skip_nan_inf \ + --training.dataset $DATASET_ROOT/fineweb-edu-sample,$DATASET_ROOT/small_repos_20B_sample_merged,$DATASET_ROOT/megamath-web-pro \ + --training.data_probs 0.55,0.3,0.15 \ + --training.dataset_split train,train,train \ + --training.dataset_name default,default,default \ + --training.streaming \ + --training.num_workers 32 \ + --training.prefetch_factor 2 \ + --training.seed 42 \ + --training.compile \ + --checkpoint.interval 8192 \ + --checkpoint.load_step -1 \ + --checkpoint.keep_latest_k 100 \ + --metrics.log_freq 1 \ + --metrics.enable_tensorboard \ + --training.streaming + diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/config.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/config.json new file mode 100644 index 0000000000000000000000000000000000000000..9e176938e9469adde683c575255c0a940894331f --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/config.json @@ -0,0 +1,53 @@ +{ + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/delta_net_1B.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/delta_net_1B.json new file mode 100644 index 0000000000000000000000000000000000000000..97726ff8c42fe0c32cad027fa3bd419e195bc68a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/delta_net_1B.json @@ -0,0 +1,29 @@ +{ + "attn": null, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 2048, + "initializer_range": 0.02, + "intermediate_size": null, + "model_type": "delta_net", + "norm_eps": 1e-06, + "num_heads": 16, + "num_hidden_layers": 24, + "pad_token_id": 2, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "use_beta": true, + "use_cache": true, + "use_gate": false, + "use_output_norm": true, + "use_short_conv": true +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/delta_net_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/delta_net_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..2eb566c873b179893174edfd816706a22cf4d53a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/delta_net_340M.json @@ -0,0 +1,26 @@ +{ + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "model_type": "delta_net", + "norm_eps": 1e-06, + "num_heads": 8, + "num_hidden_layers": 24, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "use_beta": true, + "use_cache": true, + "use_gate": false, + "use_output_norm": true, + "use_short_conv": true +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gated_deltanet_1B.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gated_deltanet_1B.json new file mode 100644 index 0000000000000000000000000000000000000000..f10793ea778aa039138a8821c2a6eda1c3f76cef --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gated_deltanet_1B.json @@ -0,0 +1,22 @@ +{ + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_v": 2, + "fuse_cross_entropy": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 2048, + "initializer_range": 0.02, + "intermediate_size": null, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "num_heads": 6, + "num_hidden_layers": 21, + "tie_word_embeddings": false, + "use_cache": true, + "use_gate": true, + "use_short_conv": true +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gated_deltanet_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gated_deltanet_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..0c592213c2013465f36b394eaae49f54f484936a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gated_deltanet_340M.json @@ -0,0 +1,22 @@ +{ + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_v": 2, + "fuse_cross_entropy": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "num_heads": 6, + "num_hidden_layers": 21, + "tie_word_embeddings": false, + "use_cache": true, + "use_gate": true, + "use_short_conv": true +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gdn_6_1_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gdn_6_1_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..8b17fd826dd82b406a0d575a42edb5e8efbe4bf7 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gdn_6_1_340M.json @@ -0,0 +1,50 @@ +{ + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.51.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gla_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gla_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..7190f4fd6b1abb5ee0af83f108bd4100cc6cd038 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gla_340M.json @@ -0,0 +1,24 @@ +{ + "attn_mode": "chunk", + "bos_token_id": 1, + "clamp_min": null, + "eos_token_id": 2, + "expand_k": 0.5, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "model_type": "gla", + "num_heads": 4, + "num_hidden_layers": 24, + "norm_eps": 1e-06, + "tie_word_embeddings": false, + "use_cache": true, + "use_gk": true, + "use_gv": false, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gla_7B.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gla_7B.json new file mode 100644 index 0000000000000000000000000000000000000000..16d373247ce3c3f96a804f8e41014e162c17b9d8 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gla_7B.json @@ -0,0 +1,25 @@ +{ + "attn": null, + "attn_mode": "chunk", + "bos_token_id": 1, + "eos_token_id": 2, + "expand_k": 0.5, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 4096, + "initializer_range": 0.02, + "intermediate_size": 11008, + "model_type": "gla", + "norm_eps": 1e-06, + "num_heads": 16, + "num_hidden_layers": 32, + "tie_word_embeddings": false, + "use_cache": true, + "use_gk": true, + "use_gv": false, + "use_output_gate": true, + "use_short_conv": false +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gsa_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gsa_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..8b4f4ec77ac1b3978dac071e91e26ced4ae58342 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/gsa_340M.json @@ -0,0 +1,29 @@ +{ + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "elementwise_affine": false, + "feature_map": "swish", + "fuse_cross_entropy": true, + "fuse_norm": true, + "gate_logit_normalizer": 4, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "model_type": "gsa", + "num_heads": 4, + "num_hidden_layers": 24, + "num_slots": 64, + "norm_eps": 1e-06, + "share_conv_kernel": true, + "tie_word_embeddings": false, + "use_cache": true, + "use_norm": true, + "use_output_gate": true, + "use_rope": false, + "use_short_conv": false +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/hgrn2_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/hgrn2_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..9f8ab2e06998cb0c2c42bee50e6a0b43833cb440 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/hgrn2_340M.json @@ -0,0 +1,20 @@ +{ + "attn_mode": "chunk", + "bos_token_id": 1, + "eos_token_id": 2, + "expand_ratio": 128, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "model_type": "hgrn2", + "num_heads": 8, + "num_hidden_layers": 24, + "norm_eps": 1e-06, + "tie_word_embeddings": false, + "use_cache": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba2_1B.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba2_1B.json new file mode 100644 index 0000000000000000000000000000000000000000..7469f2819a2bc60796e9a76d5e1ead16f4039d68 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba2_1B.json @@ -0,0 +1,32 @@ +{ + "bos_token_id": 1, + "chunk_size": 256, + "conv_kernel": 4, + "eos_token_id": 2, + "expand": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 2048, + "initializer_range": 0.02, + "norm_eps": 1e-05, + "model_type": "mamba2", + "n_groups": 1, + "num_hidden_layers": 48, + "pad_token_id": 0, + "rescale_prenorm_residual": true, + "residual_in_fp32": true, + "rms_norm": true, + "state_size": 128, + "tie_word_embeddings": false, + "time_step_floor": 0.0001, + "time_step_max": 0.1, + "time_step_min": 0.001, + "time_step_rank": 128, + "transformers_version": "4.50.1", + "use_bias": false, + "use_cache": true, + "use_conv_bias": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba2_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba2_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..0f9c34d4ef6280cb1b3f813f7bac9de907a7ebed --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba2_340M.json @@ -0,0 +1,32 @@ +{ + "bos_token_id": 1, + "chunk_size": 256, + "conv_kernel": 4, + "eos_token_id": 2, + "expand": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "norm_eps": 1e-05, + "model_type": "mamba2", + "n_groups": 1, + "num_hidden_layers": 48, + "pad_token_id": 0, + "rescale_prenorm_residual": true, + "residual_in_fp32": true, + "rms_norm": true, + "state_size": 128, + "tie_word_embeddings": false, + "time_step_floor": 0.0001, + "time_step_max": 0.1, + "time_step_min": 0.001, + "time_step_rank": 128, + "transformers_version": "4.50.1", + "use_bias": false, + "use_cache": true, + "use_conv_bias": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba_1B.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba_1B.json new file mode 100644 index 0000000000000000000000000000000000000000..8ab111e041711a082aef0e9cac5ca750a2f59c91 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba_1B.json @@ -0,0 +1,30 @@ +{ + "bos_token_id": 1, + "conv_kernel": 4, + "eos_token_id": 2, + "expand": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "silu", + "hidden_size": 2048, + "initializer_range": 0.02, + "model_type": "mamba", + "norm_eps": 1e-05, + "num_hidden_layers": 48, + "pad_token_id": 0, + "rescale_prenorm_residual": false, + "residual_in_fp32": false, + "state_size": 16, + "tie_word_embeddings": false, + "time_step_floor": 0.0001, + "time_step_init_scheme": "random", + "time_step_max": 0.1, + "time_step_min": 0.001, + "time_step_rank": 128, + "time_step_scale": 1.0, + "transformers_version": "4.50.1", + "use_bias": false, + "use_cache": true, + "use_conv_bias": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..a316b792619d6a871a3f561f477fc2ab044cf5bd --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/mamba_340M.json @@ -0,0 +1,30 @@ +{ + "bos_token_id": 1, + "conv_kernel": 4, + "eos_token_id": 2, + "expand": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "model_type": "mamba", + "norm_eps": 1e-05, + "num_hidden_layers": 48, + "pad_token_id": 0, + "rescale_prenorm_residual": false, + "residual_in_fp32": false, + "state_size": 16, + "tie_word_embeddings": false, + "time_step_floor": 0.0001, + "time_step_init_scheme": "random", + "time_step_max": 0.1, + "time_step_min": 0.001, + "time_step_rank": 128, + "time_step_scale": 1.0, + "transformers_version": "4.50.1", + "use_bias": false, + "use_cache": true, + "use_conv_bias": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/samba_1B.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/samba_1B.json new file mode 100644 index 0000000000000000000000000000000000000000..58f91099417bf59574da7188624fe51c49bfe441 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/samba_1B.json @@ -0,0 +1,52 @@ +{ + "attn": { + "layers": [ + 1, + 3, + 5, + 7, + 9, + 11, + 13, + 15, + 17 + ], + "num_heads": 18, + "num_kv_heads": 18, + "qkv_bias": false, + "rope_theta": 10000.0, + "window_size": 2048 + }, + "bos_token_id": 1, + "conv_kernel": 4, + "eos_token_id": 2, + "expand": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 2304, + "initializer_range": 0.02, + "intermediate_size": 4608, + "max_position_embeddings": 2048, + "model_type": "samba", + "norm_eps": 1e-05, + "num_hidden_layers": 18, + "pad_token_id": 0, + "rescale_prenorm_residual": false, + "residual_in_fp32": false, + "state_size": 16, + "tie_word_embeddings": false, + "time_step_floor": 0.0001, + "time_step_init_scheme": "random", + "time_step_max": 0.1, + "time_step_min": 0.001, + "time_step_rank": 144, + "time_step_scale": 1.0, + "transformers_version": "4.50.1", + "use_bias": false, + "use_cache": true, + "use_conv_bias": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/sba_340m.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/sba_340m.json new file mode 100644 index 0000000000000000000000000000000000000000..97c98de03c9c1f8ea8062d1f30147856cd036df6 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/sba_340m.json @@ -0,0 +1,18 @@ +{ + "attention_bias": false, + "bos_token_id": 1, + "eos_token_id": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "swish", + "hidden_size": 1024, + "initializer_range": 0.006, + "max_position_embeddings": 8192, + "model_type": "sba", + "num_heads": 16, + "num_hidden_layers": 24, + "norm_eps": 1e-06, + "tie_word_embeddings": false, + "use_cache": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_1B.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_1B.json new file mode 100644 index 0000000000000000000000000000000000000000..042dd38334d708c6d0e21aba0e791f0e995af605 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_1B.json @@ -0,0 +1,22 @@ +{ + "bos_token_id": 1, + "elementwise_affine": true, + "eos_token_id": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 2048, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "transformer", + "norm_eps": 1e-06, + "num_heads": 32, + "num_hidden_layers": 24, + "num_kv_heads": null, + "pad_token_id": 2, + "rope_theta": 10000.0, + "tie_word_embeddings": false +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_340M.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_340M.json new file mode 100644 index 0000000000000000000000000000000000000000..696bc5cbeee41ec89f6c1cb06399b2189b627a93 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_340M.json @@ -0,0 +1,18 @@ +{ + "attention_bias": false, + "bos_token_id": 1, + "eos_token_id": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "swish", + "hidden_size": 1024, + "initializer_range": 0.02, + "max_position_embeddings": 8192, + "model_type": "transformer", + "num_heads": 16, + "num_hidden_layers": 24, + "norm_eps": 1e-06, + "tie_word_embeddings": false, + "use_cache": true, + "vocab_size": 32000 +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_7B.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_7B.json new file mode 100644 index 0000000000000000000000000000000000000000..a2a3c2c81d0aecf83e4ccdd97851192f0e16939e --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/configs/transformer_7B.json @@ -0,0 +1,21 @@ +{ + "attention_bias": false, + "bos_token_id": 1, + "eos_token_id": 2, + "fuse_cross_entropy": true, + "fuse_norm": true, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 4096, + "initializer_range": 0.02, + "intermediate_size": 14336, + "model_type": "transformer", + "norm_eps": 1e-06, + "num_heads": 32, + "num_hidden_layers": 32, + "num_kv_heads": 8, + "rope_theta": 10000.0, + "tie_word_embeddings": false, + "use_cache": true, + "window_size": null +} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/0/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/0/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..1c06acbb27edebfeb1b9d8078813cfee731679af --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/0/stderr.log @@ -0,0 +1,6 @@ +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 17, in + from torchtitan.components.checkpoint import CheckpointManager +ModuleNotFoundError: No module named 'torchtitan' diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/0/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/0/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/1/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/1/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..1c06acbb27edebfeb1b9d8078813cfee731679af --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/1/stderr.log @@ -0,0 +1,6 @@ +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 17, in + from torchtitan.components.checkpoint import CheckpointManager +ModuleNotFoundError: No module named 'torchtitan' diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/1/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/1/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/2/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/2/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..1c06acbb27edebfeb1b9d8078813cfee731679af --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/2/stderr.log @@ -0,0 +1,6 @@ +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 17, in + from torchtitan.components.checkpoint import CheckpointManager +ModuleNotFoundError: No module named 'torchtitan' diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/2/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/2/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/3/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/3/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..1c06acbb27edebfeb1b9d8078813cfee731679af --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/3/stderr.log @@ -0,0 +1,6 @@ +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 17, in + from torchtitan.components.checkpoint import CheckpointManager +ModuleNotFoundError: No module named 'torchtitan' diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/3/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/3/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/4/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/4/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..1c06acbb27edebfeb1b9d8078813cfee731679af --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/4/stderr.log @@ -0,0 +1,6 @@ +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 17, in + from torchtitan.components.checkpoint import CheckpointManager +ModuleNotFoundError: No module named 'torchtitan' diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/4/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/4/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/5/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/5/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..1c06acbb27edebfeb1b9d8078813cfee731679af --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/5/stderr.log @@ -0,0 +1,6 @@ +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 17, in + from torchtitan.components.checkpoint import CheckpointManager +ModuleNotFoundError: No module named 'torchtitan' diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/5/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/5/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/6/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/6/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..1c06acbb27edebfeb1b9d8078813cfee731679af --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/6/stderr.log @@ -0,0 +1,6 @@ +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 17, in + from torchtitan.components.checkpoint import CheckpointManager +ModuleNotFoundError: No module named 'torchtitan' diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/6/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/6/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/7/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/7/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..1c06acbb27edebfeb1b9d8078813cfee731679af --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/7/stderr.log @@ -0,0 +1,6 @@ +Traceback (most recent call last): + File "", line 198, in _run_module_as_main + File "", line 88, in _run_code + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 17, in + from torchtitan.components.checkpoint import CheckpointManager +ModuleNotFoundError: No module named 'torchtitan' diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/7/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_0hlbuzgb/attempt_0/7/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/0/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/0/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..57b1b4df7d25f30c735db007a9fcc21379f8992d --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/0/stderr.log @@ -0,0 +1,217 @@ +[titan] 2025-07-22 22:47:41,883 - root - INFO - Starting job: default job +[titan] 2025-07-22 22:47:41,883 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 22:47:41,885 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 22:47:41,885 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 22:47:41,901 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 22:47:41,963 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 22:47:41,963 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 22:47:41,963 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 22:47:43,109 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 22:47:43,210 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 22:47:43,211 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,211 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,666 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 22:47:43,666 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 22:47:43,667 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,667 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. + Generating train split: 0 examples [00:00, ? 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recent call last): +Traceback (most recent call last): + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/process.py", line 314, in _bootstrap + self.run() + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/process.py", line 108, in run + self._target(*self._args, **self._kwargs) + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/process.py", line 314, in _bootstrap + self.run() + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/pool.py", line 114, in worker + task = get() + ^^^^^ + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/process.py", line 108, in run + self._target(*self._args, **self._kwargs) + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/queues.py", line 367, in get + with self._rlock: + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/pool.py", line 114, in worker + task = get() + ^^^^^ + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/synchronize.py", line 101, in __enter__ + return self._semlock.__enter__() + ^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/queues.py", line 367, in get + with self._rlock: + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/synchronize.py", line 101, in __enter__ + return self._semlock.__enter__() + ^^^^^^^^^^^^^^^^^^^^^^^^^ +KeyboardInterrupt +Traceback (most recent call last): +KeyboardInterrupt + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/process.py", line 314, in _bootstrap + self.run() + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/process.py", line 108, in run + self._target(*self._args, **self._kwargs) + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/pool.py", line 114, in worker + task = get() + ^^^^^ + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/queues.py", line 368, in get + res = self._reader.recv_bytes() + ^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/connection.py", line 219, in recv_bytes + buf = self._recv_bytes(maxlength) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/connection.py", line 433, in _recv_bytes + buf = self._recv(4) + ^^^^^^^^^^^^^ + File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/multiprocess/connection.py", line 398, in _recv + chunk = read(handle, remaining) + ^^^^^^^^^^^^^^^^^^^^^^^ +KeyboardInterrupt diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/0/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/0/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/1/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/1/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..28682c5b3fb80ecca2244724f4ffe9cbbc3d0ebd --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/1/stderr.log @@ -0,0 +1,187 @@ +[titan] 2025-07-22 22:47:41,941 - root - INFO - Starting job: default job +[titan] 2025-07-22 22:47:41,941 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 22:47:41,942 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 22:47:43,062 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 22:47:43,064 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 22:47:43,187 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 22:47:43,187 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 22:47:43,187 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 22:47:43,207 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 22:47:43,370 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 22:47:43,371 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,371 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,666 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 22:47:43,667 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 22:47:43,667 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,667 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[rank1]: Traceback (most recent call last): +[rank1]: File "", line 198, in _run_module_as_main +[rank1]: File "", line 88, in _run_code +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank1]: main(config) +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank1]: return f(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 155, in main +[rank1]: dataset = build_dataset( +[rank1]: ^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/data.py", line 689, in build_dataset +[rank1]: subset = load_dataset( +[rank1]: ^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/load.py", line 1412, in load_dataset +[rank1]: builder_instance.download_and_prepare( +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/builder.py", line 829, in download_and_prepare +[rank1]: with FileLock(lock_path) if is_local else contextlib.nullcontext(): +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 376, in __enter__ +[rank1]: self.acquire() +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 344, in acquire +[rank1]: time.sleep(poll_interval) +[rank1]: KeyboardInterrupt diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/1/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/1/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/2/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/2/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..f619d1cc8198e9afbd060721edd9c70ea0528044 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/2/stderr.log @@ -0,0 +1,187 @@ +[titan] 2025-07-22 22:47:42,036 - root - INFO - Starting job: default job +[titan] 2025-07-22 22:47:42,037 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 22:47:42,038 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 22:47:43,075 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 22:47:43,078 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 22:47:43,210 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 22:47:43,210 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 22:47:43,210 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 22:47:43,219 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 22:47:43,387 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 22:47:43,387 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,387 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,666 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 22:47:43,667 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 22:47:43,667 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,668 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[rank2]: Traceback (most recent call last): +[rank2]: File "", line 198, in _run_module_as_main +[rank2]: File "", line 88, in _run_code +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank2]: main(config) +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank2]: return f(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 155, in main +[rank2]: dataset = build_dataset( +[rank2]: ^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/data.py", line 689, in build_dataset +[rank2]: subset = load_dataset( +[rank2]: ^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/load.py", line 1412, in load_dataset +[rank2]: builder_instance.download_and_prepare( +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/builder.py", line 829, in download_and_prepare +[rank2]: with FileLock(lock_path) if is_local else contextlib.nullcontext(): +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 376, in __enter__ +[rank2]: self.acquire() +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 344, in acquire +[rank2]: time.sleep(poll_interval) +[rank2]: KeyboardInterrupt diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/2/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/2/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/3/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/3/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..a1c9d7681aca134776b84e0dae1043ca3a968114 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/3/stderr.log @@ -0,0 +1,187 @@ +[titan] 2025-07-22 22:47:41,964 - root - INFO - Starting job: default job +[titan] 2025-07-22 22:47:41,965 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 22:47:41,966 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 22:47:43,050 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 22:47:43,053 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 22:47:43,165 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 22:47:43,165 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 22:47:43,165 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 22:47:43,192 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 22:47:43,304 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 22:47:43,304 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,304 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,666 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 22:47:43,666 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 22:47:43,667 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,667 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[rank3]: Traceback (most recent call last): +[rank3]: File "", line 198, in _run_module_as_main +[rank3]: File "", line 88, in _run_code +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank3]: main(config) +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank3]: return f(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 155, in main +[rank3]: dataset = build_dataset( +[rank3]: ^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/data.py", line 689, in build_dataset +[rank3]: subset = load_dataset( +[rank3]: ^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/load.py", line 1412, in load_dataset +[rank3]: builder_instance.download_and_prepare( +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/builder.py", line 829, in download_and_prepare +[rank3]: with FileLock(lock_path) if is_local else contextlib.nullcontext(): +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 376, in __enter__ +[rank3]: self.acquire() +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 344, in acquire +[rank3]: time.sleep(poll_interval) +[rank3]: KeyboardInterrupt diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/3/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/3/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/4/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/4/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..496250c83a5ab3dc5d47ebbbbbefe9c1766c78da --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/4/stderr.log @@ -0,0 +1,187 @@ +[titan] 2025-07-22 22:47:41,988 - root - INFO - Starting job: default job +[titan] 2025-07-22 22:47:41,988 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 22:47:41,990 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 22:47:43,095 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 22:47:43,097 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 22:47:43,213 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 22:47:43,213 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 22:47:43,214 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 22:47:43,222 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 22:47:43,405 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 22:47:43,405 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,405 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,666 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 22:47:43,667 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 22:47:43,667 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,667 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[rank4]: Traceback (most recent call last): +[rank4]: File "", line 198, in _run_module_as_main +[rank4]: File "", line 88, in _run_code +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank4]: main(config) +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank4]: return f(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 155, in main +[rank4]: dataset = build_dataset( +[rank4]: ^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/data.py", line 689, in build_dataset +[rank4]: subset = load_dataset( +[rank4]: ^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/load.py", line 1412, in load_dataset +[rank4]: builder_instance.download_and_prepare( +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/builder.py", line 829, in download_and_prepare +[rank4]: with FileLock(lock_path) if is_local else contextlib.nullcontext(): +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 376, in __enter__ +[rank4]: self.acquire() +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 344, in acquire +[rank4]: time.sleep(poll_interval) +[rank4]: KeyboardInterrupt diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/4/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/4/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/5/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/5/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..c7a816ddc1f1e921e57903f36b239eb4921d3ddb --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/5/stderr.log @@ -0,0 +1,187 @@ +[titan] 2025-07-22 22:47:41,984 - root - INFO - Starting job: default job +[titan] 2025-07-22 22:47:41,984 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 22:47:41,986 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 22:47:43,062 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 22:47:43,064 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 22:47:43,202 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 22:47:43,202 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 22:47:43,202 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 22:47:43,209 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 22:47:43,394 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 22:47:43,395 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,395 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,666 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 22:47:43,666 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 22:47:43,667 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,667 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[rank5]: Traceback (most recent call last): +[rank5]: File "", line 198, in _run_module_as_main +[rank5]: File "", line 88, in _run_code +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank5]: main(config) +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank5]: return f(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 155, in main +[rank5]: dataset = build_dataset( +[rank5]: ^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/data.py", line 689, in build_dataset +[rank5]: subset = load_dataset( +[rank5]: ^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/load.py", line 1412, in load_dataset +[rank5]: builder_instance.download_and_prepare( +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/builder.py", line 829, in download_and_prepare +[rank5]: with FileLock(lock_path) if is_local else contextlib.nullcontext(): +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 376, in __enter__ +[rank5]: self.acquire() +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 344, in acquire +[rank5]: time.sleep(poll_interval) +[rank5]: KeyboardInterrupt diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/5/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/5/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/6/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/6/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..971063234a1f549ed8a702366c8d2fef077e3ce7 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/6/stderr.log @@ -0,0 +1,187 @@ +[titan] 2025-07-22 22:47:41,727 - root - INFO - Starting job: default job +[titan] 2025-07-22 22:47:41,727 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 22:47:41,729 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 22:47:42,344 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 22:47:42,347 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 22:47:42,391 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 22:47:42,391 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 22:47:42,391 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 22:47:42,708 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 22:47:43,145 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 22:47:43,145 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,146 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,667 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 22:47:43,667 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 22:47:43,667 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,668 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[rank6]: Traceback (most recent call last): +[rank6]: File "", line 198, in _run_module_as_main +[rank6]: File "", line 88, in _run_code +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank6]: main(config) +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank6]: return f(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 155, in main +[rank6]: dataset = build_dataset( +[rank6]: ^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/data.py", line 689, in build_dataset +[rank6]: subset = load_dataset( +[rank6]: ^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/load.py", line 1412, in load_dataset +[rank6]: builder_instance.download_and_prepare( +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/builder.py", line 829, in download_and_prepare +[rank6]: with FileLock(lock_path) if is_local else contextlib.nullcontext(): +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 376, in __enter__ +[rank6]: self.acquire() +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 344, in acquire +[rank6]: time.sleep(poll_interval) +[rank6]: KeyboardInterrupt diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/6/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/6/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/7/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/7/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..57b167ea5cefde1dcbfc11e684cbc9eb5dac0fce --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/7/stderr.log @@ -0,0 +1,187 @@ +[titan] 2025-07-22 22:47:41,993 - root - INFO - Starting job: default job +[titan] 2025-07-22 22:47:41,993 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 22:47:41,995 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 22:47:43,056 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 22:47:43,058 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 22:47:43,185 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 22:47:43,185 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 22:47:43,185 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 22:47:43,207 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 22:47:43,352 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 22:47:43,352 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/MegaMath/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,352 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,666 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 22:47:43,666 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 22:47:43,667 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 22:47:43,667 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[rank7]: Traceback (most recent call last): +[rank7]: File "", line 198, in _run_module_as_main +[rank7]: File "", line 88, in _run_code +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank7]: main(config) +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank7]: return f(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 155, in main +[rank7]: dataset = build_dataset( +[rank7]: ^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/data.py", line 689, in build_dataset +[rank7]: subset = load_dataset( +[rank7]: ^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/load.py", line 1412, in load_dataset +[rank7]: builder_instance.download_and_prepare( +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/datasets/builder.py", line 829, in download_and_prepare +[rank7]: with FileLock(lock_path) if is_local else contextlib.nullcontext(): +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 376, in __enter__ +[rank7]: self.acquire() +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/filelock/_api.py", line 344, in acquire +[rank7]: time.sleep(poll_interval) +[rank7]: KeyboardInterrupt diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/7/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_ff62l9rt/attempt_0/7/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/0/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/0/error.json new file mode 100644 index 0000000000000000000000000000000000000000..5370a022b335c193809f9e91820db98a35a3a21a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/0/error.json @@ -0,0 +1 @@ +{"message": {"message": "ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 214, in main\n model = AutoModelForCausalLM.from_config(model_config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 456, in from_config\n return model_class._from_config(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 311, in _wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2208, in _from_config\n model = cls(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 312, in __init__\n self.model = GatedDeltaNetModel(config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in __init__\n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in \n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 48, in __init__\n self.attn = Attention(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py\", line 67, in __init__\n raise ImportError(\"Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\")\nImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\n", "timestamp": "1753197420"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/0/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/0/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..6f56c919c88e5becf47f2e5a7a91e1617ba96b8d --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/0/stderr.log @@ -0,0 +1,302 @@ +[titan] 2025-07-22 23:06:21,670 - root - INFO - Starting job: default job +[titan] 2025-07-22 23:06:21,670 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 23:06:21,671 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 23:06:21,672 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 23:06:21,674 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 23:06:21,739 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 23:06:21,740 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 23:06:21,740 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 23:06:21,974 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 23:06:22,084 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 23:06:22,084 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:22,084 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:22,210 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 23:06:22,211 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:06:22,212 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:22,213 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,778 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,812 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-22 23:12:08,812 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:08,812 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,812 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,100 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,573 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-22 23:12:36,573 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:36,574 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,574 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:16:42,853 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-22 23:16:43,528 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-22 23:16:43,649 - root - INFO - Building dataloader... +[titan] 2025-07-22 23:16:43,651 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-22 23:16:43,653 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[rank0]: Traceback (most recent call last): +[rank0]: File "", line 198, in _run_module_as_main +[rank0]: File "", line 88, in _run_code +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank0]: main(config) +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank0]: return f(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 214, in main +[rank0]: model = AutoModelForCausalLM.from_config(model_config) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 456, in from_config +[rank0]: return model_class._from_config(config, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 311, in _wrapper +[rank0]: return func(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 2208, in _from_config +[rank0]: model = cls(config, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 312, in __init__ +[rank0]: self.model = GatedDeltaNetModel(config) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in __init__ +[rank0]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in +[rank0]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 48, in __init__ +[rank0]: self.attn = Attention( +[rank0]: ^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py", line 67, in __init__ +[rank0]: raise ImportError("Please install Flash Attention via `pip install flash-attn --no-build-isolation` first") +[rank0]: ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first +[rank0]:[W722 23:17:11.702401472 ProcessGroupNCCL.cpp:1479] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/0/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/0/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/1/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/1/error.json new file mode 100644 index 0000000000000000000000000000000000000000..5370a022b335c193809f9e91820db98a35a3a21a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/1/error.json @@ -0,0 +1 @@ +{"message": {"message": "ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 214, in main\n model = AutoModelForCausalLM.from_config(model_config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 456, in from_config\n return model_class._from_config(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 311, in _wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2208, in _from_config\n model = cls(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 312, in __init__\n self.model = GatedDeltaNetModel(config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in __init__\n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in \n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 48, in __init__\n self.attn = Attention(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py\", line 67, in __init__\n raise ImportError(\"Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\")\nImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\n", "timestamp": "1753197420"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/1/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/1/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..ea386bf0e6c577c10f05ead35209e8b6aec29c84 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/1/stderr.log @@ -0,0 +1,304 @@ +[titan] 2025-07-22 23:06:24,497 - root - INFO - Starting job: default job +[titan] 2025-07-22 23:06:24,498 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 23:06:24,500 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 23:06:24,902 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 23:06:24,904 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 23:06:24,992 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 23:06:24,992 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 23:06:24,993 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 23:06:25,001 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 23:06:25,141 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 23:06:25,141 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:25,141 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:25,269 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 23:06:25,269 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:06:25,269 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:25,269 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:06,096 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:06,209 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-22 23:12:06,209 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:06,209 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:06,209 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +Setting num_proc from 32 back to 1 for the train split to disable multiprocessing as it only contains one shard. +[titan] 2025-07-22 23:12:06,301 - datasets.builder - WARNING - Setting num_proc from 32 back to 1 for the train split to disable multiprocessing as it only contains one shard. + Generating train split: 0 examples [00:00, ? examples/s] Generating train split: 80099 examples [00:26, 3062.05 examples/s] Generating train split: 160549 examples [00:26, 7210.30 examples/s] Generating train split: 238364 examples [00:27, 12503.71 examples/s] Generating train split: 317719 examples [00:28, 19454.52 examples/s] Generating train split: 398626 examples [00:28, 27945.57 examples/s] Generating train split: 465855 examples [00:29, 36443.59 examples/s] Generating train split: 465855 examples [00:29, 15820.52 examples/s] +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,063 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,573 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-22 23:12:36,574 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:36,574 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,575 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:16:42,914 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-22 23:16:43,595 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-22 23:16:43,713 - root - INFO - Building dataloader... +[titan] 2025-07-22 23:16:43,716 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-22 23:16:43,718 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[rank1]: Traceback (most recent call last): +[rank1]: File "", line 198, in _run_module_as_main +[rank1]: File "", line 88, in _run_code +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank1]: main(config) +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank1]: return f(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 214, in main +[rank1]: model = AutoModelForCausalLM.from_config(model_config) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 456, in from_config +[rank1]: return model_class._from_config(config, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 311, in _wrapper +[rank1]: return func(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 2208, in _from_config +[rank1]: model = cls(config, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 312, in __init__ +[rank1]: self.model = GatedDeltaNetModel(config) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in __init__ +[rank1]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in +[rank1]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 48, in __init__ +[rank1]: self.attn = Attention( +[rank1]: ^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py", line 67, in __init__ +[rank1]: raise ImportError("Please install Flash Attention via `pip install flash-attn --no-build-isolation` first") +[rank1]: ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/1/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/1/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/2/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/2/error.json new file mode 100644 index 0000000000000000000000000000000000000000..5370a022b335c193809f9e91820db98a35a3a21a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/2/error.json @@ -0,0 +1 @@ +{"message": {"message": "ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 214, in main\n model = AutoModelForCausalLM.from_config(model_config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 456, in from_config\n return model_class._from_config(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 311, in _wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2208, in _from_config\n model = cls(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 312, in __init__\n self.model = GatedDeltaNetModel(config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in __init__\n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in \n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 48, in __init__\n self.attn = Attention(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py\", line 67, in __init__\n raise ImportError(\"Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\")\nImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\n", "timestamp": "1753197420"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/2/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/2/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..bca83fe0b02e8e6ce59710d8e623c8e051a97e5d --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/2/stderr.log @@ -0,0 +1,302 @@ +[titan] 2025-07-22 23:06:21,126 - root - INFO - Starting job: default job +[titan] 2025-07-22 23:06:21,127 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 23:06:21,128 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 23:06:21,341 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 23:06:21,343 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 23:06:21,392 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 23:06:21,392 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 23:06:21,392 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 23:06:21,399 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 23:06:21,506 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 23:06:21,506 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:21,506 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:21,635 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 23:06:21,635 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:06:21,635 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:21,635 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. + Generating train split: 0 examples [00:00, ? 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'/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,107 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,144 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-22 23:12:08,144 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:08,144 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,144 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,096 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,573 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-22 23:12:36,573 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:36,573 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,574 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:16:42,962 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-22 23:16:43,660 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-22 23:16:43,784 - root - INFO - Building dataloader... +[titan] 2025-07-22 23:16:43,787 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-22 23:16:43,788 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[rank2]: Traceback (most recent call last): +[rank2]: File "", line 198, in _run_module_as_main +[rank2]: File "", line 88, in _run_code +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank2]: main(config) +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank2]: return f(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 214, in main +[rank2]: model = AutoModelForCausalLM.from_config(model_config) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 456, in from_config +[rank2]: return model_class._from_config(config, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 311, in _wrapper +[rank2]: return func(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 2208, in _from_config +[rank2]: model = cls(config, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 312, in __init__ +[rank2]: self.model = GatedDeltaNetModel(config) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in __init__ +[rank2]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in +[rank2]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 48, in __init__ +[rank2]: self.attn = Attention( +[rank2]: ^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py", line 67, in __init__ +[rank2]: raise ImportError("Please install Flash Attention via `pip install flash-attn --no-build-isolation` first") +[rank2]: ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/2/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/2/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/3/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/3/error.json new file mode 100644 index 0000000000000000000000000000000000000000..5370a022b335c193809f9e91820db98a35a3a21a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/3/error.json @@ -0,0 +1 @@ +{"message": {"message": "ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 214, in main\n model = AutoModelForCausalLM.from_config(model_config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 456, in from_config\n return model_class._from_config(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 311, in _wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2208, in _from_config\n model = cls(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 312, in __init__\n self.model = GatedDeltaNetModel(config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in __init__\n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in \n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 48, in __init__\n self.attn = Attention(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py\", line 67, in __init__\n raise ImportError(\"Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\")\nImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\n", "timestamp": "1753197420"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/3/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/3/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..6314d37d8bdc34468545130c230280881dd61e2c --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/3/stderr.log @@ -0,0 +1,302 @@ +[titan] 2025-07-22 23:06:24,368 - root - INFO - Starting job: default job +[titan] 2025-07-22 23:06:24,368 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 23:06:24,370 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 23:06:24,689 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 23:06:24,692 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 23:06:24,740 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 23:06:24,741 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 23:06:24,741 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 23:06:24,770 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 23:06:24,878 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 23:06:24,878 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:24,878 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:25,020 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 23:06:25,021 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:06:25,021 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:25,021 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:07,706 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:07,741 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-22 23:12:07,741 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:07,741 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:07,741 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,089 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,573 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-22 23:12:36,573 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:36,574 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,574 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. + Generating train split: 0 examples [00:00, ? 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[03:49, 65144.23 examples/s] +[titan] 2025-07-22 23:16:42,955 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-22 23:16:43,869 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-22 23:16:43,989 - root - INFO - Building dataloader... +[titan] 2025-07-22 23:16:43,991 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-22 23:16:43,993 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[rank3]: Traceback (most recent call last): +[rank3]: File "", line 198, in _run_module_as_main +[rank3]: File "", line 88, in _run_code +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank3]: main(config) +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank3]: return f(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 214, in main +[rank3]: model = AutoModelForCausalLM.from_config(model_config) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 456, in from_config +[rank3]: return model_class._from_config(config, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 311, in _wrapper +[rank3]: return func(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 2208, in _from_config +[rank3]: model = cls(config, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 312, in __init__ +[rank3]: self.model = GatedDeltaNetModel(config) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in __init__ +[rank3]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in +[rank3]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 48, in __init__ +[rank3]: self.attn = Attention( +[rank3]: ^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py", line 67, in __init__ +[rank3]: raise ImportError("Please install Flash Attention via `pip install flash-attn --no-build-isolation` first") +[rank3]: ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/3/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/3/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/4/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/4/error.json new file mode 100644 index 0000000000000000000000000000000000000000..5370a022b335c193809f9e91820db98a35a3a21a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/4/error.json @@ -0,0 +1 @@ +{"message": {"message": "ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 214, in main\n model = AutoModelForCausalLM.from_config(model_config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 456, in from_config\n return model_class._from_config(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 311, in _wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2208, in _from_config\n model = cls(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 312, in __init__\n self.model = GatedDeltaNetModel(config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in __init__\n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in \n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 48, in __init__\n self.attn = Attention(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py\", line 67, in __init__\n raise ImportError(\"Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\")\nImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\n", "timestamp": "1753197420"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/4/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/4/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..cf2436a52f35556810870bd1f9fa1066f35022c0 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/4/stderr.log @@ -0,0 +1,301 @@ +[titan] 2025-07-22 23:06:23,070 - root - INFO - Starting job: default job +[titan] 2025-07-22 23:06:23,070 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 23:06:23,072 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 23:06:23,435 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 23:06:23,438 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 23:06:23,500 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 23:06:23,500 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 23:06:23,501 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 23:06:23,513 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 23:06:23,654 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 23:06:23,654 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:23,655 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:23,877 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 23:06:23,877 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:06:23,878 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:23,878 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,808 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,843 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-22 23:12:08,843 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:08,843 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,843 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,082 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,573 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-22 23:12:36,574 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:36,574 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,574 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:16:42,912 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-22 23:16:43,607 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-22 23:16:43,732 - root - INFO - Building dataloader... +[titan] 2025-07-22 23:16:43,734 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-22 23:16:43,735 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[rank4]: Traceback (most recent call last): +[rank4]: File "", line 198, in _run_module_as_main +[rank4]: File "", line 88, in _run_code +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank4]: main(config) +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank4]: return f(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 214, in main +[rank4]: model = AutoModelForCausalLM.from_config(model_config) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 456, in from_config +[rank4]: return model_class._from_config(config, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 311, in _wrapper +[rank4]: return func(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 2208, in _from_config +[rank4]: model = cls(config, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 312, in __init__ +[rank4]: self.model = GatedDeltaNetModel(config) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in __init__ +[rank4]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in +[rank4]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 48, in __init__ +[rank4]: self.attn = Attention( +[rank4]: ^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py", line 67, in __init__ +[rank4]: raise ImportError("Please install Flash Attention via `pip install flash-attn --no-build-isolation` first") +[rank4]: ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/4/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/4/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/5/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/5/error.json new file mode 100644 index 0000000000000000000000000000000000000000..5370a022b335c193809f9e91820db98a35a3a21a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/5/error.json @@ -0,0 +1 @@ +{"message": {"message": "ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 214, in main\n model = AutoModelForCausalLM.from_config(model_config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 456, in from_config\n return model_class._from_config(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 311, in _wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2208, in _from_config\n model = cls(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 312, in __init__\n self.model = GatedDeltaNetModel(config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in __init__\n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in \n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 48, in __init__\n self.attn = Attention(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py\", line 67, in __init__\n raise ImportError(\"Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\")\nImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\n", "timestamp": "1753197420"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/5/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/5/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..7dc12a690676c75faad08aa21c368d45f9f1cc36 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/5/stderr.log @@ -0,0 +1,301 @@ +[titan] 2025-07-22 23:06:24,587 - root - INFO - Starting job: default job +[titan] 2025-07-22 23:06:24,588 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 23:06:24,589 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 23:06:24,909 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 23:06:24,913 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 23:06:24,992 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 23:06:24,992 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 23:06:24,993 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 23:06:25,001 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 23:06:25,133 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 23:06:25,133 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:25,133 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:25,258 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 23:06:25,258 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:06:25,258 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:25,258 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,084 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,119 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-22 23:12:08,119 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:08,119 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,119 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,070 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,573 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-22 23:12:36,574 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:36,575 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,575 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:16:42,998 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-22 23:16:43,693 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-22 23:16:43,816 - root - INFO - Building dataloader... +[titan] 2025-07-22 23:16:43,819 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-22 23:16:43,820 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[rank5]: Traceback (most recent call last): +[rank5]: File "", line 198, in _run_module_as_main +[rank5]: File "", line 88, in _run_code +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank5]: main(config) +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank5]: return f(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 214, in main +[rank5]: model = AutoModelForCausalLM.from_config(model_config) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 456, in from_config +[rank5]: return model_class._from_config(config, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 311, in _wrapper +[rank5]: return func(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 2208, in _from_config +[rank5]: model = cls(config, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 312, in __init__ +[rank5]: self.model = GatedDeltaNetModel(config) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in __init__ +[rank5]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in +[rank5]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 48, in __init__ +[rank5]: self.attn = Attention( +[rank5]: ^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py", line 67, in __init__ +[rank5]: raise ImportError("Please install Flash Attention via `pip install flash-attn --no-build-isolation` first") +[rank5]: ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/5/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/5/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/6/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/6/error.json new file mode 100644 index 0000000000000000000000000000000000000000..5370a022b335c193809f9e91820db98a35a3a21a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/6/error.json @@ -0,0 +1 @@ +{"message": {"message": "ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 214, in main\n model = AutoModelForCausalLM.from_config(model_config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 456, in from_config\n return model_class._from_config(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 311, in _wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2208, in _from_config\n model = cls(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 312, in __init__\n self.model = GatedDeltaNetModel(config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in __init__\n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in \n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 48, in __init__\n self.attn = Attention(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py\", line 67, in __init__\n raise ImportError(\"Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\")\nImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\n", "timestamp": "1753197420"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/6/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/6/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..92564a12c7b14e1b190054494341b4ecddc19fe0 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/6/stderr.log @@ -0,0 +1,301 @@ +[titan] 2025-07-22 23:06:21,885 - root - INFO - Starting job: default job +[titan] 2025-07-22 23:06:21,886 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 23:06:21,887 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 23:06:22,165 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 23:06:22,167 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 23:06:22,261 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 23:06:22,265 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 23:06:22,266 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 23:06:22,277 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 23:06:22,387 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 23:06:22,387 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:22,387 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:22,514 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 23:06:22,514 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:06:22,514 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:22,514 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,224 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,257 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-22 23:12:08,257 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:08,257 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:08,257 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,072 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,573 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-22 23:12:36,573 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:36,573 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,574 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:16:42,891 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-22 23:16:43,583 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-22 23:16:43,709 - root - INFO - Building dataloader... +[titan] 2025-07-22 23:16:43,711 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-22 23:16:43,713 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[rank6]: Traceback (most recent call last): +[rank6]: File "", line 198, in _run_module_as_main +[rank6]: File "", line 88, in _run_code +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank6]: main(config) +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank6]: return f(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 214, in main +[rank6]: model = AutoModelForCausalLM.from_config(model_config) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 456, in from_config +[rank6]: return model_class._from_config(config, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 311, in _wrapper +[rank6]: return func(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 2208, in _from_config +[rank6]: model = cls(config, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 312, in __init__ +[rank6]: self.model = GatedDeltaNetModel(config) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in __init__ +[rank6]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in +[rank6]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 48, in __init__ +[rank6]: self.attn = Attention( +[rank6]: ^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py", line 67, in __init__ +[rank6]: raise ImportError("Please install Flash Attention via `pip install flash-attn --no-build-isolation` first") +[rank6]: ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/6/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/6/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/7/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/7/error.json new file mode 100644 index 0000000000000000000000000000000000000000..5370a022b335c193809f9e91820db98a35a3a21a --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/7/error.json @@ -0,0 +1 @@ +{"message": {"message": "ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 214, in main\n model = AutoModelForCausalLM.from_config(model_config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py\", line 456, in from_config\n return model_class._from_config(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 311, in _wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py\", line 2208, in _from_config\n model = cls(config, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 312, in __init__\n self.model = GatedDeltaNetModel(config)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in __init__\n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 211, in \n self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 48, in __init__\n self.attn = Attention(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py\", line 67, in __init__\n raise ImportError(\"Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\")\nImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first\n", "timestamp": "1753197420"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/7/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/7/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..ebd17c58800968aade95930cd15db0f63cb02422 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/7/stderr.log @@ -0,0 +1,301 @@ +[titan] 2025-07-22 23:06:23,250 - root - INFO - Starting job: default job +[titan] 2025-07-22 23:06:23,250 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-22 23:06:23,252 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-22 23:06:23,527 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-22 23:06:23,530 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-22 23:06:23,594 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-22 23:06:23,594 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-22 23:06:23,595 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-22 23:06:23,628 - root - INFO - Loading tokenizer... +[titan] 2025-07-22 23:06:23,741 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-22 23:06:23,741 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:23,742 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:23,957 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-22 23:06:23,957 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:06:23,957 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:06:23,957 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:07,552 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:07,585 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-22 23:12:07,585 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:07,585 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:07,585 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,082 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,573 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-22 23:12:36,573 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-22 23:12:36,574 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:12:36,575 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-22 23:16:43,082 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-22 23:16:43,783 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-22 23:16:43,902 - root - INFO - Building dataloader... +[titan] 2025-07-22 23:16:43,904 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-22 23:16:43,906 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[rank7]: Traceback (most recent call last): +[rank7]: File "", line 198, in _run_module_as_main +[rank7]: File "", line 88, in _run_code +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank7]: main(config) +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank7]: return f(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 214, in main +[rank7]: model = AutoModelForCausalLM.from_config(model_config) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 456, in from_config +[rank7]: return model_class._from_config(config, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 311, in _wrapper +[rank7]: return func(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/modeling_utils.py", line 2208, in _from_config +[rank7]: model = cls(config, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 312, in __init__ +[rank7]: self.model = GatedDeltaNetModel(config) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in __init__ +[rank7]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 211, in +[rank7]: self.layers = nn.ModuleList([GatedDeltaNetBlock(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 48, in __init__ +[rank7]: self.attn = Attention( +[rank7]: ^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/attn.py", line 67, in __init__ +[rank7]: raise ImportError("Please install Flash Attention via `pip install flash-attn --no-build-isolation` first") +[rank7]: ImportError: Please install Flash Attention via `pip install flash-attn --no-build-isolation` first diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/7/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hipmwbzz/attempt_0/7/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/0/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/0/error.json new file mode 100644 index 0000000000000000000000000000000000000000..f58b9cb76f472094ff997c4cdde4db3085d7c046 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/0/error.json @@ -0,0 +1 @@ +{"message": {"message": "OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 0 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128271 has 316.00 MiB memory in use. Process 3365134 has 316.00 MiB memory in use. Process 303028 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 487, in main\n output = model(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py\", line 172, in wrapped_func\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 408, in forward\n outputs = self.model(\n ^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 278, in forward\n hidden_states, attentions, past_key_values = layer(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 92, in forward\n hidden_states = self.attn_norm(hidden_states)\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 93, in torch_dynamo_resume_in_forward_at_92\n hidden_states, attentions, past_key_values = self.attn(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 238, in forward\n q, conv_state_q = self.q_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 244, in torch_dynamo_resume_in_forward_at_238\n k, conv_state_k = self.k_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 250, in torch_dynamo_resume_in_forward_at_244\n v, conv_state_v = self.v_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 670, in forward\n y = causal_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 478, in causal_conv1d\n return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py\", line 575, in apply\n return super().apply(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py\", line 160, in wrapper\n return fn(*contiguous_args, **contiguous_kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 428, in forward\n return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in causal_conv1d_fwd\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 838, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py\", line 1209, in forward\n return compiled_fn(full_args)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 328, in runtime_wrapper\n all_outs = call_func_at_runtime_with_args(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py\", line 126, in call_func_at_runtime_with_args\n out = normalize_as_list(f(args))\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 689, in inner_fn\n outs = compiled_fn(args)\n ^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 495, in wrapper\n return compiled_fn(runtime_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py\", line 460, in __call__\n return self.current_callable(inputs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py\", line 2404, in run\n return model(new_inputs)\n ^^^^^^^^^^^^^^^^^\n File \"/tmp/torchinductor_root/r5/cr5phv2udh6fqqhl2j4nj6fhrilep4hunp3otol2355euybybi7t.py\", line 130, in call\n buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 0 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128271 has 316.00 MiB memory in use. Process 3365134 has 316.00 MiB memory in use. Process 303028 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n", "timestamp": "1753238418"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/0/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/0/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..83a0cf9e0521c48b4e21ca95ee86956fe6d530ce --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/0/stderr.log @@ -0,0 +1,592 @@ +[titan] 2025-07-23 10:36:20,396 - root - INFO - Starting job: default job +[titan] 2025-07-23 10:36:20,397 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-23 10:36:20,397 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-23 10:36:20,397 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-23 10:36:20,414 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:36:20,508 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:36:20,508 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-23 10:36:20,508 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-23 10:36:21,373 - root - INFO - Loading tokenizer... +[titan] 2025-07-23 10:36:21,911 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-23 10:36:21,912 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:21,913 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,395 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-23 10:36:22,395 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:36:22,395 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,395 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,505 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,581 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-23 10:37:12,582 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:12,582 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,582 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,839 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,976 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-23 10:37:12,976 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:12,976 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,976 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:19,181 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-23 10:37:19,861 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-23 10:37:19,978 - root - INFO - Building dataloader... +[titan] 2025-07-23 10:37:19,980 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-23 10:37:19,982 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[titan] 2025-07-23 10:37:22,833 - root - INFO -  +GatedDeltaNetForCausalLM( + (model): GatedDeltaNetModel( + (embeddings): Embedding(32000, 1024) + (layers): ModuleList( + (0-4): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (5): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (6-10): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (11): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (12-16): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (17): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (18-22): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (23): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + ) + (norm): RMSNorm(1024, eps=1e-06) + ) + (lm_head): Linear(in_features=1024, out_features=32000, bias=False) + (criterion): FusedLinearCrossEntropyLoss() +) + +[titan] 2025-07-23 10:37:22,869 - root - INFO - Compiling each block with torch.compile +[titan] 2025-07-23 10:37:22,869 - root - INFO - Compiling the embedding, norm, and lm_head layers with torch.compile +[titan] 2025-07-23 10:37:22,870 - root - INFO - Compiling the entire model with torch.compile +[titan] 2025-07-23 10:37:23,088 - root - INFO - Applied FSDP to the model +[titan] 2025-07-23 10:37:23,337 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `A_log` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:23,467 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `dt_bias` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:24,082 - root - INFO - CUDA memory usage for model: 0.19GiB(0.20%) +[titan] 2025-07-23 10:37:24,084 - root - WARNING - Warmup (100) + decay (95366) steps exceed total training steps (95366). Adjusting decay steps to 95266. +[titan] 2025-07-23 10:37:24,108 - root - INFO - Checkpointing active. Checkpoints will be loaded from and saved to /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/checkpoint +[titan] 2025-07-23 10:37:44,819 - root - ERROR - Failed to create WandB logger: api_key not configured (no-tty). call wandb.login(key=[your_api_key]) +[titan] 2025-07-23 10:37:44,844 - root - INFO - TensorBoard logging enabled. Logs will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/tb/20250723-1037 +[titan] 2025-07-23 10:37:44,844 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:37:44,888 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:37:50,895 - root - INFO - ***** Running training ***** +[titan] 2025-07-23 10:37:50,896 - root - INFO -  Training starts at step 1 +[titan] 2025-07-23 10:37:50,897 - root - INFO -  Number of tokens per sequence = 8,192 +[titan] 2025-07-23 10:37:50,897 - root - INFO -  Gradient Accumulation steps = 1 +[titan] 2025-07-23 10:37:50,898 - root - INFO -  Instantaneous batch size (per device) = 16 +[titan] 2025-07-23 10:37:50,898 - root - INFO -  Global batch size (w. parallel, distributed & accumulation) = 128 (1,048,576 tokens) +[titan] 2025-07-23 10:37:50,898 - root - INFO -  Total optimization steps = 95,366 (99,998,498,816 tokens) +[titan] 2025-07-23 10:37:50,898 - root - INFO -  Warmup steps = 100 (104,857,600 tokens) +[titan] 2025-07-23 10:37:50,898 - root - INFO -  Number of parameters = 391,059,616  +[titan] 2025-07-23 10:37:50,899 - root - INFO - Profiling active. Traces will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/profile_trace +[titan] 2025-07-23 10:38:17,673 - urllib3.connectionpool - WARNING - Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ConnectTimeoutError(, 'Connection to o151352.ingest.sentry.io timed out. (connect timeout=30)')': /api/4504800232407040/envelope/ +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py:1263: UserWarning: Dynamo does not know how to trace the builtin `cuda_utils.get_device_properties.` This function is either a Python builtin (e.g. _warnings.warn) or a third-party C/C++ Python extension (perhaps created with pybind). +If it is a Python builtin, please file an issue on GitHub so the PyTorch team can add support for it and see the next case for a workaround. +If it is a third-party C/C++ Python extension, please either wrap it into a PyTorch-understood custom operator (see https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html for more details) or, if it is traceable, use `torch.compiler.allow_in_graph`. + torch._dynamo.utils.warn_once(explanation + "\n" + "\n".join(hints)) +[titan] 2025-07-23 10:38:47,698 - urllib3.connectionpool - WARNING - Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ConnectTimeoutError(, 'Connection to o151352.ingest.sentry.io timed out. (connect timeout=30)')': /api/4504800232407040/envelope/ +[titan] 2025-07-23 10:39:17,730 - urllib3.connectionpool - WARNING - Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ConnectTimeoutError(, 'Connection to o151352.ingest.sentry.io timed out. (connect timeout=30)')': /api/4504800232407040/envelope/ +[rank0]: Traceback (most recent call last): +[rank0]: File "", line 198, in _run_module_as_main +[rank0]: File "", line 88, in _run_code +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank0]: main(config) +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank0]: return f(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 487, in main +[rank0]: output = model( +[rank0]: ^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank0]: return self._call_impl(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank0]: return inner() +[rank0]: ^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank0]: result = forward_call(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func +[rank0]: return func(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 408, in forward +[rank0]: outputs = self.model( +[rank0]: ^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank0]: return self._call_impl(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank0]: return forward_call(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 278, in forward +[rank0]: hidden_states, attentions, past_key_values = layer( +[rank0]: ^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank0]: return self._call_impl(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank0]: return inner() +[rank0]: ^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank0]: result = forward_call(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 655, in _fn +[rank0]: return fn(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank0]: return self._call_impl(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank0]: return forward_call(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 92, in forward +[rank0]: hidden_states = self.attn_norm(hidden_states) +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 93, in torch_dynamo_resume_in_forward_at_92 +[rank0]: hidden_states, attentions, past_key_values = self.attn( +[rank0]: ^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank0]: return self._call_impl(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank0]: return forward_call(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 238, in forward +[rank0]: q, conv_state_q = self.q_conv1d( +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 244, in torch_dynamo_resume_in_forward_at_238 +[rank0]: k, conv_state_k = self.k_conv1d( +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 250, in torch_dynamo_resume_in_forward_at_244 +[rank0]: v, conv_state_v = self.v_conv1d( +[rank0]: ^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank0]: return self._call_impl(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank0]: return forward_call(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 670, in forward +[rank0]: y = causal_conv1d( +[rank0]: ^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 478, in causal_conv1d +[rank0]: return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py", line 575, in apply +[rank0]: return super().apply(*args, **kwargs) # type: ignore[misc] +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py", line 160, in wrapper +[rank0]: return fn(*contiguous_args, **contiguous_kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 428, in forward +[rank0]: return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in causal_conv1d_fwd +[rank0]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282 +[rank0]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 838, in _fn +[rank0]: return fn(*args, **kwargs) +[rank0]: ^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py", line 1209, in forward +[rank0]: return compiled_fn(full_args) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 328, in runtime_wrapper +[rank0]: all_outs = call_func_at_runtime_with_args( +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py", line 126, in call_func_at_runtime_with_args +[rank0]: out = normalize_as_list(f(args)) +[rank0]: ^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 689, in inner_fn +[rank0]: outs = compiled_fn(args) +[rank0]: ^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 495, in wrapper +[rank0]: return compiled_fn(runtime_args) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py", line 460, in __call__ +[rank0]: return self.current_callable(inputs) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 2404, in run +[rank0]: return model(new_inputs) +[rank0]: ^^^^^^^^^^^^^^^^^ +[rank0]: File "/tmp/torchinductor_root/r5/cr5phv2udh6fqqhl2j4nj6fhrilep4hunp3otol2355euybybi7t.py", line 130, in call +[rank0]: buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16) +[rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank0]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 0 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128271 has 316.00 MiB memory in use. Process 3365134 has 316.00 MiB memory in use. Process 303028 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/0/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/0/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/1/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/1/error.json new file mode 100644 index 0000000000000000000000000000000000000000..24bf101276d776ad6a2c0e0551cfe5f190a1a3b5 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/1/error.json @@ -0,0 +1 @@ +{"message": {"message": "OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 1 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128272 has 316.00 MiB memory in use. Process 3365135 has 316.00 MiB memory in use. Process 303029 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 487, in main\n output = model(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py\", line 172, in wrapped_func\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 408, in forward\n outputs = self.model(\n ^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 278, in forward\n hidden_states, attentions, past_key_values = layer(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 92, in forward\n hidden_states = self.attn_norm(hidden_states)\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 93, in torch_dynamo_resume_in_forward_at_92\n hidden_states, attentions, past_key_values = self.attn(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 238, in forward\n q, conv_state_q = self.q_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 244, in torch_dynamo_resume_in_forward_at_238\n k, conv_state_k = self.k_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 250, in torch_dynamo_resume_in_forward_at_244\n v, conv_state_v = self.v_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 670, in forward\n y = causal_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 478, in causal_conv1d\n return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py\", line 575, in apply\n return super().apply(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py\", line 160, in wrapper\n return fn(*contiguous_args, **contiguous_kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 428, in forward\n return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in causal_conv1d_fwd\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 838, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py\", line 1209, in forward\n return compiled_fn(full_args)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 328, in runtime_wrapper\n all_outs = call_func_at_runtime_with_args(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py\", line 126, in call_func_at_runtime_with_args\n out = normalize_as_list(f(args))\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 689, in inner_fn\n outs = compiled_fn(args)\n ^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 495, in wrapper\n return compiled_fn(runtime_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py\", line 460, in __call__\n return self.current_callable(inputs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py\", line 2404, in run\n return model(new_inputs)\n ^^^^^^^^^^^^^^^^^\n File \"/tmp/torchinductor_root/47/c475djqe7hojirp5gpyn6bv4fzdfocgzpuek6ktlxkvvfyqhz6mw.py\", line 130, in call\n buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 1 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128272 has 316.00 MiB memory in use. Process 3365135 has 316.00 MiB memory in use. Process 303029 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n", "timestamp": "1753238418"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/1/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/1/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..3df03bf4e0790ce636ec4ce61f11b9948b291508 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/1/stderr.log @@ -0,0 +1,587 @@ +[titan] 2025-07-23 10:36:20,359 - root - INFO - Starting job: default job +[titan] 2025-07-23 10:36:20,359 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-23 10:36:20,360 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-23 10:36:21,347 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-23 10:36:21,350 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:36:21,442 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:36:21,442 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-23 10:36:21,442 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-23 10:36:21,450 - root - INFO - Loading tokenizer... +[titan] 2025-07-23 10:36:21,911 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-23 10:36:21,912 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:21,912 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,389 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-23 10:36:22,389 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:36:22,389 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,389 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:15,181 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:15,213 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-23 10:37:15,213 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:15,213 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:15,213 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:15,473 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:15,559 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-23 10:37:15,559 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:15,559 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:15,559 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:22,200 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-23 10:37:22,846 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-23 10:37:22,959 - root - INFO - Building dataloader... +[titan] 2025-07-23 10:37:22,961 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-23 10:37:22,963 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[titan] 2025-07-23 10:37:23,306 - root - INFO -  +GatedDeltaNetForCausalLM( + (model): GatedDeltaNetModel( + (embeddings): Embedding(32000, 1024) + (layers): ModuleList( + (0-4): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (5): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (6-10): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (11): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (12-16): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (17): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (18-22): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (23): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + ) + (norm): RMSNorm(1024, eps=1e-06) + ) + (lm_head): Linear(in_features=1024, out_features=32000, bias=False) + (criterion): FusedLinearCrossEntropyLoss() +) + +[titan] 2025-07-23 10:37:23,342 - root - INFO - Compiling each block with torch.compile +[titan] 2025-07-23 10:37:23,342 - root - INFO - Compiling the embedding, norm, and lm_head layers with torch.compile +[titan] 2025-07-23 10:37:23,343 - root - INFO - Compiling the entire model with torch.compile +[titan] 2025-07-23 10:37:23,422 - root - INFO - Applied FSDP to the model +[titan] 2025-07-23 10:37:23,500 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `A_log` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:23,500 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `dt_bias` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:24,080 - root - INFO - CUDA memory usage for model: 0.19GiB(0.20%) +[titan] 2025-07-23 10:37:24,082 - root - WARNING - Warmup (100) + decay (95366) steps exceed total training steps (95366). Adjusting decay steps to 95266. +[titan] 2025-07-23 10:37:24,105 - root - INFO - Checkpointing active. Checkpoints will be loaded from and saved to /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/checkpoint +[titan] 2025-07-23 10:37:24,118 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:37:24,261 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:37:31,182 - root - INFO - ***** Running training ***** +[titan] 2025-07-23 10:37:31,187 - root - INFO -  Training starts at step 1 +[titan] 2025-07-23 10:37:31,188 - root - INFO -  Number of tokens per sequence = 8,192 +[titan] 2025-07-23 10:37:31,188 - root - INFO -  Gradient Accumulation steps = 1 +[titan] 2025-07-23 10:37:31,188 - root - INFO -  Instantaneous batch size (per device) = 16 +[titan] 2025-07-23 10:37:31,188 - root - INFO -  Global batch size (w. parallel, distributed & accumulation) = 128 (1,048,576 tokens) +[titan] 2025-07-23 10:37:31,188 - root - INFO -  Total optimization steps = 95,366 (99,998,498,816 tokens) +[titan] 2025-07-23 10:37:31,188 - root - INFO -  Warmup steps = 100 (104,857,600 tokens) +[titan] 2025-07-23 10:37:31,188 - root - INFO -  Number of parameters = 391,059,616  +[titan] 2025-07-23 10:37:31,188 - root - INFO - Profiling active. Traces will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/profile_trace +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py:1263: UserWarning: Dynamo does not know how to trace the builtin `cuda_utils.get_device_properties.` This function is either a Python builtin (e.g. _warnings.warn) or a third-party C/C++ Python extension (perhaps created with pybind). +If it is a Python builtin, please file an issue on GitHub so the PyTorch team can add support for it and see the next case for a workaround. +If it is a third-party C/C++ Python extension, please either wrap it into a PyTorch-understood custom operator (see https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html for more details) or, if it is traceable, use `torch.compiler.allow_in_graph`. + torch._dynamo.utils.warn_once(explanation + "\n" + "\n".join(hints)) +[rank1]: Traceback (most recent call last): +[rank1]: File "", line 198, in _run_module_as_main +[rank1]: File "", line 88, in _run_code +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank1]: main(config) +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank1]: return f(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 487, in main +[rank1]: output = model( +[rank1]: ^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank1]: return self._call_impl(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank1]: return inner() +[rank1]: ^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank1]: result = forward_call(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func +[rank1]: return func(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 408, in forward +[rank1]: outputs = self.model( +[rank1]: ^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank1]: return self._call_impl(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank1]: return forward_call(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 278, in forward +[rank1]: hidden_states, attentions, past_key_values = layer( +[rank1]: ^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank1]: return self._call_impl(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank1]: return inner() +[rank1]: ^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank1]: result = forward_call(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 655, in _fn +[rank1]: return fn(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank1]: return self._call_impl(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank1]: return forward_call(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 92, in forward +[rank1]: hidden_states = self.attn_norm(hidden_states) +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 93, in torch_dynamo_resume_in_forward_at_92 +[rank1]: hidden_states, attentions, past_key_values = self.attn( +[rank1]: ^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank1]: return self._call_impl(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank1]: return forward_call(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 238, in forward +[rank1]: q, conv_state_q = self.q_conv1d( +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 244, in torch_dynamo_resume_in_forward_at_238 +[rank1]: k, conv_state_k = self.k_conv1d( +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 250, in torch_dynamo_resume_in_forward_at_244 +[rank1]: v, conv_state_v = self.v_conv1d( +[rank1]: ^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank1]: return self._call_impl(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank1]: return forward_call(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 670, in forward +[rank1]: y = causal_conv1d( +[rank1]: ^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 478, in causal_conv1d +[rank1]: return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py", line 575, in apply +[rank1]: return super().apply(*args, **kwargs) # type: ignore[misc] +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py", line 160, in wrapper +[rank1]: return fn(*contiguous_args, **contiguous_kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 428, in forward +[rank1]: return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in causal_conv1d_fwd +[rank1]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282 +[rank1]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 838, in _fn +[rank1]: return fn(*args, **kwargs) +[rank1]: ^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py", line 1209, in forward +[rank1]: return compiled_fn(full_args) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 328, in runtime_wrapper +[rank1]: all_outs = call_func_at_runtime_with_args( +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py", line 126, in call_func_at_runtime_with_args +[rank1]: out = normalize_as_list(f(args)) +[rank1]: ^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 689, in inner_fn +[rank1]: outs = compiled_fn(args) +[rank1]: ^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 495, in wrapper +[rank1]: return compiled_fn(runtime_args) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py", line 460, in __call__ +[rank1]: return self.current_callable(inputs) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 2404, in run +[rank1]: return model(new_inputs) +[rank1]: ^^^^^^^^^^^^^^^^^ +[rank1]: File "/tmp/torchinductor_root/47/c475djqe7hojirp5gpyn6bv4fzdfocgzpuek6ktlxkvvfyqhz6mw.py", line 130, in call +[rank1]: buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16) +[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank1]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 1 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128272 has 316.00 MiB memory in use. Process 3365135 has 316.00 MiB memory in use. Process 303029 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/1/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/1/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/2/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/2/error.json new file mode 100644 index 0000000000000000000000000000000000000000..e927e076f0fee7e8cfb6d00098044a774d7f2b2d --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/2/error.json @@ -0,0 +1 @@ +{"message": {"message": "OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 2 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128274 has 316.00 MiB memory in use. Process 3365137 has 316.00 MiB memory in use. Process 303030 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 487, in main\n output = model(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py\", line 172, in wrapped_func\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 408, in forward\n outputs = self.model(\n ^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 278, in forward\n hidden_states, attentions, past_key_values = layer(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 92, in forward\n hidden_states = self.attn_norm(hidden_states)\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 93, in torch_dynamo_resume_in_forward_at_92\n hidden_states, attentions, past_key_values = self.attn(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 238, in forward\n q, conv_state_q = self.q_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 244, in torch_dynamo_resume_in_forward_at_238\n k, conv_state_k = self.k_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 250, in torch_dynamo_resume_in_forward_at_244\n v, conv_state_v = self.v_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 670, in forward\n y = causal_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 478, in causal_conv1d\n return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py\", line 575, in apply\n return super().apply(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py\", line 160, in wrapper\n return fn(*contiguous_args, **contiguous_kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 428, in forward\n return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in causal_conv1d_fwd\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 838, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py\", line 1209, in forward\n return compiled_fn(full_args)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 328, in runtime_wrapper\n all_outs = call_func_at_runtime_with_args(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py\", line 126, in call_func_at_runtime_with_args\n out = normalize_as_list(f(args))\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 689, in inner_fn\n outs = compiled_fn(args)\n ^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 495, in wrapper\n return compiled_fn(runtime_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py\", line 460, in __call__\n return self.current_callable(inputs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py\", line 2404, in run\n return model(new_inputs)\n ^^^^^^^^^^^^^^^^^\n File \"/tmp/torchinductor_root/g2/cg2i5q3ggwg534j45cjsxlnpktiyqktdtj7mlv4tq7ypdk4kw32v.py\", line 130, in call\n buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 2 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128274 has 316.00 MiB memory in use. Process 3365137 has 316.00 MiB memory in use. Process 303030 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n", "timestamp": "1753238418"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/2/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/2/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..0d621adad2df9b597ae44d930815dc9effbc1ca3 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/2/stderr.log @@ -0,0 +1,587 @@ +[titan] 2025-07-23 10:36:20,177 - root - INFO - Starting job: default job +[titan] 2025-07-23 10:36:20,177 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-23 10:36:20,178 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-23 10:36:21,156 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-23 10:36:21,159 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:36:21,235 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:36:21,235 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-23 10:36:21,236 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-23 10:36:21,367 - root - INFO - Loading tokenizer... +[titan] 2025-07-23 10:36:21,911 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-23 10:36:21,912 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:21,912 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,387 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-23 10:36:22,387 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:36:22,387 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,387 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,170 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,203 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-23 10:37:13,203 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:13,203 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,203 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,467 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,552 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-23 10:37:13,553 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:13,553 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,553 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:20,233 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-23 10:37:20,918 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-23 10:37:21,039 - root - INFO - Building dataloader... +[titan] 2025-07-23 10:37:21,041 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-23 10:37:21,043 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[titan] 2025-07-23 10:37:22,829 - root - INFO -  +GatedDeltaNetForCausalLM( + (model): GatedDeltaNetModel( + (embeddings): Embedding(32000, 1024) + (layers): ModuleList( + (0-4): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (5): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (6-10): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (11): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (12-16): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (17): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (18-22): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (23): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + ) + (norm): RMSNorm(1024, eps=1e-06) + ) + (lm_head): Linear(in_features=1024, out_features=32000, bias=False) + (criterion): FusedLinearCrossEntropyLoss() +) + +[titan] 2025-07-23 10:37:22,864 - root - INFO - Compiling each block with torch.compile +[titan] 2025-07-23 10:37:22,864 - root - INFO - Compiling the embedding, norm, and lm_head layers with torch.compile +[titan] 2025-07-23 10:37:22,865 - root - INFO - Compiling the entire model with torch.compile +[titan] 2025-07-23 10:37:23,085 - root - INFO - Applied FSDP to the model +[titan] 2025-07-23 10:37:23,337 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `A_log` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:23,467 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `dt_bias` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:24,080 - root - INFO - CUDA memory usage for model: 0.19GiB(0.20%) +[titan] 2025-07-23 10:37:24,081 - root - WARNING - Warmup (100) + decay (95366) steps exceed total training steps (95366). Adjusting decay steps to 95266. +[titan] 2025-07-23 10:37:24,106 - root - INFO - Checkpointing active. Checkpoints will be loaded from and saved to /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/checkpoint +[titan] 2025-07-23 10:37:24,122 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:37:24,265 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:37:31,220 - root - INFO - ***** Running training ***** +[titan] 2025-07-23 10:37:31,222 - root - INFO -  Training starts at step 1 +[titan] 2025-07-23 10:37:31,224 - root - INFO -  Number of tokens per sequence = 8,192 +[titan] 2025-07-23 10:37:31,224 - root - INFO -  Gradient Accumulation steps = 1 +[titan] 2025-07-23 10:37:31,225 - root - INFO -  Instantaneous batch size (per device) = 16 +[titan] 2025-07-23 10:37:31,225 - root - INFO -  Global batch size (w. parallel, distributed & accumulation) = 128 (1,048,576 tokens) +[titan] 2025-07-23 10:37:31,225 - root - INFO -  Total optimization steps = 95,366 (99,998,498,816 tokens) +[titan] 2025-07-23 10:37:31,225 - root - INFO -  Warmup steps = 100 (104,857,600 tokens) +[titan] 2025-07-23 10:37:31,225 - root - INFO -  Number of parameters = 391,059,616  +[titan] 2025-07-23 10:37:31,226 - root - INFO - Profiling active. Traces will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/profile_trace +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py:1263: UserWarning: Dynamo does not know how to trace the builtin `cuda_utils.get_device_properties.` This function is either a Python builtin (e.g. _warnings.warn) or a third-party C/C++ Python extension (perhaps created with pybind). +If it is a Python builtin, please file an issue on GitHub so the PyTorch team can add support for it and see the next case for a workaround. +If it is a third-party C/C++ Python extension, please either wrap it into a PyTorch-understood custom operator (see https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html for more details) or, if it is traceable, use `torch.compiler.allow_in_graph`. + torch._dynamo.utils.warn_once(explanation + "\n" + "\n".join(hints)) +[rank2]: Traceback (most recent call last): +[rank2]: File "", line 198, in _run_module_as_main +[rank2]: File "", line 88, in _run_code +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank2]: main(config) +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank2]: return f(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 487, in main +[rank2]: output = model( +[rank2]: ^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank2]: return self._call_impl(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank2]: return inner() +[rank2]: ^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank2]: result = forward_call(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func +[rank2]: return func(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 408, in forward +[rank2]: outputs = self.model( +[rank2]: ^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank2]: return self._call_impl(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank2]: return forward_call(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 278, in forward +[rank2]: hidden_states, attentions, past_key_values = layer( +[rank2]: ^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank2]: return self._call_impl(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank2]: return inner() +[rank2]: ^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank2]: result = forward_call(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 655, in _fn +[rank2]: return fn(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank2]: return self._call_impl(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank2]: return forward_call(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 92, in forward +[rank2]: hidden_states = self.attn_norm(hidden_states) +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 93, in torch_dynamo_resume_in_forward_at_92 +[rank2]: hidden_states, attentions, past_key_values = self.attn( +[rank2]: ^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank2]: return self._call_impl(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank2]: return forward_call(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 238, in forward +[rank2]: q, conv_state_q = self.q_conv1d( +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 244, in torch_dynamo_resume_in_forward_at_238 +[rank2]: k, conv_state_k = self.k_conv1d( +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 250, in torch_dynamo_resume_in_forward_at_244 +[rank2]: v, conv_state_v = self.v_conv1d( +[rank2]: ^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank2]: return self._call_impl(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank2]: return forward_call(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 670, in forward +[rank2]: y = causal_conv1d( +[rank2]: ^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 478, in causal_conv1d +[rank2]: return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py", line 575, in apply +[rank2]: return super().apply(*args, **kwargs) # type: ignore[misc] +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py", line 160, in wrapper +[rank2]: return fn(*contiguous_args, **contiguous_kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 428, in forward +[rank2]: return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in causal_conv1d_fwd +[rank2]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282 +[rank2]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 838, in _fn +[rank2]: return fn(*args, **kwargs) +[rank2]: ^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py", line 1209, in forward +[rank2]: return compiled_fn(full_args) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 328, in runtime_wrapper +[rank2]: all_outs = call_func_at_runtime_with_args( +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py", line 126, in call_func_at_runtime_with_args +[rank2]: out = normalize_as_list(f(args)) +[rank2]: ^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 689, in inner_fn +[rank2]: outs = compiled_fn(args) +[rank2]: ^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 495, in wrapper +[rank2]: return compiled_fn(runtime_args) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py", line 460, in __call__ +[rank2]: return self.current_callable(inputs) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 2404, in run +[rank2]: return model(new_inputs) +[rank2]: ^^^^^^^^^^^^^^^^^ +[rank2]: File "/tmp/torchinductor_root/g2/cg2i5q3ggwg534j45cjsxlnpktiyqktdtj7mlv4tq7ypdk4kw32v.py", line 130, in call +[rank2]: buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16) +[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank2]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 2 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128274 has 316.00 MiB memory in use. Process 3365137 has 316.00 MiB memory in use. Process 303030 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/2/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/2/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/3/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/3/error.json new file mode 100644 index 0000000000000000000000000000000000000000..8583bce01b094566cf5ca3cc142425ed642ba1c5 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/3/error.json @@ -0,0 +1 @@ +{"message": {"message": "OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 3 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128276 has 316.00 MiB memory in use. Process 3365138 has 316.00 MiB memory in use. Process 303031 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 487, in main\n output = model(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py\", line 172, in wrapped_func\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 408, in forward\n outputs = self.model(\n ^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 278, in forward\n hidden_states, attentions, past_key_values = layer(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 92, in forward\n hidden_states = self.attn_norm(hidden_states)\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 93, in torch_dynamo_resume_in_forward_at_92\n hidden_states, attentions, past_key_values = self.attn(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 238, in forward\n q, conv_state_q = self.q_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 244, in torch_dynamo_resume_in_forward_at_238\n k, conv_state_k = self.k_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 250, in torch_dynamo_resume_in_forward_at_244\n v, conv_state_v = self.v_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 670, in forward\n y = causal_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 478, in causal_conv1d\n return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py\", line 575, in apply\n return super().apply(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py\", line 160, in wrapper\n return fn(*contiguous_args, **contiguous_kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 428, in forward\n return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in causal_conv1d_fwd\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 838, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py\", line 1209, in forward\n return compiled_fn(full_args)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 328, in runtime_wrapper\n all_outs = call_func_at_runtime_with_args(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py\", line 126, in call_func_at_runtime_with_args\n out = normalize_as_list(f(args))\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 689, in inner_fn\n outs = compiled_fn(args)\n ^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 495, in wrapper\n return compiled_fn(runtime_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py\", line 460, in __call__\n return self.current_callable(inputs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py\", line 2404, in run\n return model(new_inputs)\n ^^^^^^^^^^^^^^^^^\n File \"/tmp/torchinductor_root/3n/c3nvohjoal4hknohsoleoiu2ky3rktgo6trp42mdevzaekq4smbg.py\", line 130, in call\n buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 3 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128276 has 316.00 MiB memory in use. Process 3365138 has 316.00 MiB memory in use. Process 303031 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n", "timestamp": "1753238418"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/3/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/3/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..d9fe746fefbc373e28287da54b82289835dcce3f --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/3/stderr.log @@ -0,0 +1,587 @@ +[titan] 2025-07-23 10:36:20,363 - root - INFO - Starting job: default job +[titan] 2025-07-23 10:36:20,364 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-23 10:36:20,364 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-23 10:36:21,348 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-23 10:36:21,350 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:36:21,458 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:36:21,459 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-23 10:36:21,459 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-23 10:36:21,467 - root - INFO - Loading tokenizer... +[titan] 2025-07-23 10:36:21,911 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-23 10:36:21,912 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:21,913 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,438 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-23 10:36:22,438 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:36:22,438 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,438 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,851 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,893 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-23 10:37:13,893 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:13,893 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,893 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,152 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,240 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-23 10:37:14,240 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:14,240 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,240 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:20,425 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-23 10:37:21,103 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-23 10:37:21,220 - root - INFO - Building dataloader... +[titan] 2025-07-23 10:37:21,222 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-23 10:37:21,223 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[titan] 2025-07-23 10:37:22,830 - root - INFO -  +GatedDeltaNetForCausalLM( + (model): GatedDeltaNetModel( + (embeddings): Embedding(32000, 1024) + (layers): ModuleList( + (0-4): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (5): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (6-10): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (11): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (12-16): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (17): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (18-22): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (23): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + ) + (norm): RMSNorm(1024, eps=1e-06) + ) + (lm_head): Linear(in_features=1024, out_features=32000, bias=False) + (criterion): FusedLinearCrossEntropyLoss() +) + +[titan] 2025-07-23 10:37:22,866 - root - INFO - Compiling each block with torch.compile +[titan] 2025-07-23 10:37:22,866 - root - INFO - Compiling the embedding, norm, and lm_head layers with torch.compile +[titan] 2025-07-23 10:37:22,867 - root - INFO - Compiling the entire model with torch.compile +[titan] 2025-07-23 10:37:23,110 - root - INFO - Applied FSDP to the model +[titan] 2025-07-23 10:37:23,337 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `A_log` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:23,467 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `dt_bias` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:24,097 - root - INFO - CUDA memory usage for model: 0.19GiB(0.20%) +[titan] 2025-07-23 10:37:24,099 - root - WARNING - Warmup (100) + decay (95366) steps exceed total training steps (95366). Adjusting decay steps to 95266. +[titan] 2025-07-23 10:37:24,122 - root - INFO - Checkpointing active. Checkpoints will be loaded from and saved to /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/checkpoint +[titan] 2025-07-23 10:37:24,127 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:37:24,280 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:37:31,897 - root - INFO - ***** Running training ***** +[titan] 2025-07-23 10:37:31,933 - root - INFO -  Training starts at step 1 +[titan] 2025-07-23 10:37:31,934 - root - INFO -  Number of tokens per sequence = 8,192 +[titan] 2025-07-23 10:37:31,947 - root - INFO -  Gradient Accumulation steps = 1 +[titan] 2025-07-23 10:37:31,948 - root - INFO -  Instantaneous batch size (per device) = 16 +[titan] 2025-07-23 10:37:31,949 - root - INFO -  Global batch size (w. parallel, distributed & accumulation) = 128 (1,048,576 tokens) +[titan] 2025-07-23 10:37:31,952 - root - INFO -  Total optimization steps = 95,366 (99,998,498,816 tokens) +[titan] 2025-07-23 10:37:31,953 - root - INFO -  Warmup steps = 100 (104,857,600 tokens) +[titan] 2025-07-23 10:37:31,953 - root - INFO -  Number of parameters = 391,059,616  +[titan] 2025-07-23 10:37:31,954 - root - INFO - Profiling active. Traces will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/profile_trace +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py:1263: UserWarning: Dynamo does not know how to trace the builtin `cuda_utils.get_device_properties.` This function is either a Python builtin (e.g. _warnings.warn) or a third-party C/C++ Python extension (perhaps created with pybind). +If it is a Python builtin, please file an issue on GitHub so the PyTorch team can add support for it and see the next case for a workaround. +If it is a third-party C/C++ Python extension, please either wrap it into a PyTorch-understood custom operator (see https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html for more details) or, if it is traceable, use `torch.compiler.allow_in_graph`. + torch._dynamo.utils.warn_once(explanation + "\n" + "\n".join(hints)) +[rank3]: Traceback (most recent call last): +[rank3]: File "", line 198, in _run_module_as_main +[rank3]: File "", line 88, in _run_code +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank3]: main(config) +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank3]: return f(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 487, in main +[rank3]: output = model( +[rank3]: ^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank3]: return self._call_impl(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank3]: return inner() +[rank3]: ^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank3]: result = forward_call(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func +[rank3]: return func(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 408, in forward +[rank3]: outputs = self.model( +[rank3]: ^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank3]: return self._call_impl(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank3]: return forward_call(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 278, in forward +[rank3]: hidden_states, attentions, past_key_values = layer( +[rank3]: ^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank3]: return self._call_impl(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank3]: return inner() +[rank3]: ^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank3]: result = forward_call(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 655, in _fn +[rank3]: return fn(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank3]: return self._call_impl(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank3]: return forward_call(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 92, in forward +[rank3]: hidden_states = self.attn_norm(hidden_states) +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 93, in torch_dynamo_resume_in_forward_at_92 +[rank3]: hidden_states, attentions, past_key_values = self.attn( +[rank3]: ^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank3]: return self._call_impl(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank3]: return forward_call(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 238, in forward +[rank3]: q, conv_state_q = self.q_conv1d( +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 244, in torch_dynamo_resume_in_forward_at_238 +[rank3]: k, conv_state_k = self.k_conv1d( +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 250, in torch_dynamo_resume_in_forward_at_244 +[rank3]: v, conv_state_v = self.v_conv1d( +[rank3]: ^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank3]: return self._call_impl(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank3]: return forward_call(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 670, in forward +[rank3]: y = causal_conv1d( +[rank3]: ^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 478, in causal_conv1d +[rank3]: return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py", line 575, in apply +[rank3]: return super().apply(*args, **kwargs) # type: ignore[misc] +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py", line 160, in wrapper +[rank3]: return fn(*contiguous_args, **contiguous_kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 428, in forward +[rank3]: return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in causal_conv1d_fwd +[rank3]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282 +[rank3]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 838, in _fn +[rank3]: return fn(*args, **kwargs) +[rank3]: ^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py", line 1209, in forward +[rank3]: return compiled_fn(full_args) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 328, in runtime_wrapper +[rank3]: all_outs = call_func_at_runtime_with_args( +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py", line 126, in call_func_at_runtime_with_args +[rank3]: out = normalize_as_list(f(args)) +[rank3]: ^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 689, in inner_fn +[rank3]: outs = compiled_fn(args) +[rank3]: ^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 495, in wrapper +[rank3]: return compiled_fn(runtime_args) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py", line 460, in __call__ +[rank3]: return self.current_callable(inputs) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 2404, in run +[rank3]: return model(new_inputs) +[rank3]: ^^^^^^^^^^^^^^^^^ +[rank3]: File "/tmp/torchinductor_root/3n/c3nvohjoal4hknohsoleoiu2ky3rktgo6trp42mdevzaekq4smbg.py", line 130, in call +[rank3]: buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16) +[rank3]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank3]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 3 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128276 has 316.00 MiB memory in use. Process 3365138 has 316.00 MiB memory in use. Process 303031 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.30 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/3/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/3/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/4/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/4/error.json new file mode 100644 index 0000000000000000000000000000000000000000..86bbb9c0592c8db1da7f61c937b6ae703797f4b1 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/4/error.json @@ -0,0 +1 @@ +{"message": {"message": "OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 4 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128277 has 316.00 MiB memory in use. Process 3365139 has 316.00 MiB memory in use. Process 303040 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 487, in main\n output = model(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py\", line 172, in wrapped_func\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 408, in forward\n outputs = self.model(\n ^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 278, in forward\n hidden_states, attentions, past_key_values = layer(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 92, in forward\n hidden_states = self.attn_norm(hidden_states)\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 93, in torch_dynamo_resume_in_forward_at_92\n hidden_states, attentions, past_key_values = self.attn(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 238, in forward\n q, conv_state_q = self.q_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 244, in torch_dynamo_resume_in_forward_at_238\n k, conv_state_k = self.k_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 250, in torch_dynamo_resume_in_forward_at_244\n v, conv_state_v = self.v_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 670, in forward\n y = causal_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 478, in causal_conv1d\n return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py\", line 575, in apply\n return super().apply(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py\", line 160, in wrapper\n return fn(*contiguous_args, **contiguous_kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 428, in forward\n return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in causal_conv1d_fwd\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 838, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py\", line 1209, in forward\n return compiled_fn(full_args)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 328, in runtime_wrapper\n all_outs = call_func_at_runtime_with_args(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py\", line 126, in call_func_at_runtime_with_args\n out = normalize_as_list(f(args))\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 689, in inner_fn\n outs = compiled_fn(args)\n ^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 495, in wrapper\n return compiled_fn(runtime_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py\", line 460, in __call__\n return self.current_callable(inputs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py\", line 2404, in run\n return model(new_inputs)\n ^^^^^^^^^^^^^^^^^\n File \"/tmp/torchinductor_root/xv/cxvmfi6yr3z46nbg55tjpsrom3ok6iubilxyghzmt6cmn3ihfv7y.py\", line 130, in call\n buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 4 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128277 has 316.00 MiB memory in use. Process 3365139 has 316.00 MiB memory in use. Process 303040 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n", "timestamp": "1753238418"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/4/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/4/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..4e9fa2d19c1d20dc43aae99e1cbc7286816c32b6 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/4/stderr.log @@ -0,0 +1,587 @@ +[titan] 2025-07-23 10:36:20,144 - root - INFO - Starting job: default job +[titan] 2025-07-23 10:36:20,144 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-23 10:36:20,144 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-23 10:36:21,157 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-23 10:36:21,159 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:36:21,248 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:36:21,248 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-23 10:36:21,248 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-23 10:36:21,367 - root - INFO - Loading tokenizer... +[titan] 2025-07-23 10:36:21,911 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-23 10:36:21,912 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:21,912 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,439 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-23 10:36:22,439 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:36:22,439 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,439 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,822 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,857 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-23 10:37:13,858 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:13,858 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,858 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,124 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,212 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-23 10:37:14,212 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:14,212 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,213 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:20,285 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-23 10:37:20,969 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-23 10:37:21,089 - root - INFO - Building dataloader... +[titan] 2025-07-23 10:37:21,091 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-23 10:37:21,092 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[titan] 2025-07-23 10:37:22,832 - root - INFO -  +GatedDeltaNetForCausalLM( + (model): GatedDeltaNetModel( + (embeddings): Embedding(32000, 1024) + (layers): ModuleList( + (0-4): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (5): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (6-10): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (11): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (12-16): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (17): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (18-22): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (23): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + ) + (norm): RMSNorm(1024, eps=1e-06) + ) + (lm_head): Linear(in_features=1024, out_features=32000, bias=False) + (criterion): FusedLinearCrossEntropyLoss() +) + +[titan] 2025-07-23 10:37:22,867 - root - INFO - Compiling each block with torch.compile +[titan] 2025-07-23 10:37:22,868 - root - INFO - Compiling the embedding, norm, and lm_head layers with torch.compile +[titan] 2025-07-23 10:37:22,868 - root - INFO - Compiling the entire model with torch.compile +[titan] 2025-07-23 10:37:23,085 - root - INFO - Applied FSDP to the model +[titan] 2025-07-23 10:37:23,337 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `A_log` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:23,467 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `dt_bias` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:24,078 - root - INFO - CUDA memory usage for model: 0.19GiB(0.20%) +[titan] 2025-07-23 10:37:24,080 - root - WARNING - Warmup (100) + decay (95366) steps exceed total training steps (95366). Adjusting decay steps to 95266. +[titan] 2025-07-23 10:37:24,103 - root - INFO - Checkpointing active. Checkpoints will be loaded from and saved to /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/checkpoint +[titan] 2025-07-23 10:37:24,137 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:37:24,287 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:37:32,152 - root - INFO - ***** Running training ***** +[titan] 2025-07-23 10:37:32,153 - root - INFO -  Training starts at step 1 +[titan] 2025-07-23 10:37:32,217 - root - INFO -  Number of tokens per sequence = 8,192 +[titan] 2025-07-23 10:37:32,236 - root - INFO -  Gradient Accumulation steps = 1 +[titan] 2025-07-23 10:37:32,238 - root - INFO -  Instantaneous batch size (per device) = 16 +[titan] 2025-07-23 10:37:32,238 - root - INFO -  Global batch size (w. parallel, distributed & accumulation) = 128 (1,048,576 tokens) +[titan] 2025-07-23 10:37:32,239 - root - INFO -  Total optimization steps = 95,366 (99,998,498,816 tokens) +[titan] 2025-07-23 10:37:32,239 - root - INFO -  Warmup steps = 100 (104,857,600 tokens) +[titan] 2025-07-23 10:37:32,239 - root - INFO -  Number of parameters = 391,059,616  +[titan] 2025-07-23 10:37:32,240 - root - INFO - Profiling active. Traces will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/profile_trace +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py:1263: UserWarning: Dynamo does not know how to trace the builtin `cuda_utils.get_device_properties.` This function is either a Python builtin (e.g. _warnings.warn) or a third-party C/C++ Python extension (perhaps created with pybind). +If it is a Python builtin, please file an issue on GitHub so the PyTorch team can add support for it and see the next case for a workaround. +If it is a third-party C/C++ Python extension, please either wrap it into a PyTorch-understood custom operator (see https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html for more details) or, if it is traceable, use `torch.compiler.allow_in_graph`. + torch._dynamo.utils.warn_once(explanation + "\n" + "\n".join(hints)) +[rank4]: Traceback (most recent call last): +[rank4]: File "", line 198, in _run_module_as_main +[rank4]: File "", line 88, in _run_code +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank4]: main(config) +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank4]: return f(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 487, in main +[rank4]: output = model( +[rank4]: ^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank4]: return self._call_impl(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank4]: return inner() +[rank4]: ^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank4]: result = forward_call(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func +[rank4]: return func(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 408, in forward +[rank4]: outputs = self.model( +[rank4]: ^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank4]: return self._call_impl(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank4]: return forward_call(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 278, in forward +[rank4]: hidden_states, attentions, past_key_values = layer( +[rank4]: ^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank4]: return self._call_impl(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank4]: return inner() +[rank4]: ^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank4]: result = forward_call(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 655, in _fn +[rank4]: return fn(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank4]: return self._call_impl(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank4]: return forward_call(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 92, in forward +[rank4]: hidden_states = self.attn_norm(hidden_states) +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 93, in torch_dynamo_resume_in_forward_at_92 +[rank4]: hidden_states, attentions, past_key_values = self.attn( +[rank4]: ^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank4]: return self._call_impl(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank4]: return forward_call(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 238, in forward +[rank4]: q, conv_state_q = self.q_conv1d( +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 244, in torch_dynamo_resume_in_forward_at_238 +[rank4]: k, conv_state_k = self.k_conv1d( +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 250, in torch_dynamo_resume_in_forward_at_244 +[rank4]: v, conv_state_v = self.v_conv1d( +[rank4]: ^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank4]: return self._call_impl(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank4]: return forward_call(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 670, in forward +[rank4]: y = causal_conv1d( +[rank4]: ^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 478, in causal_conv1d +[rank4]: return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py", line 575, in apply +[rank4]: return super().apply(*args, **kwargs) # type: ignore[misc] +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py", line 160, in wrapper +[rank4]: return fn(*contiguous_args, **contiguous_kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 428, in forward +[rank4]: return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in causal_conv1d_fwd +[rank4]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282 +[rank4]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 838, in _fn +[rank4]: return fn(*args, **kwargs) +[rank4]: ^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py", line 1209, in forward +[rank4]: return compiled_fn(full_args) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 328, in runtime_wrapper +[rank4]: all_outs = call_func_at_runtime_with_args( +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py", line 126, in call_func_at_runtime_with_args +[rank4]: out = normalize_as_list(f(args)) +[rank4]: ^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 689, in inner_fn +[rank4]: outs = compiled_fn(args) +[rank4]: ^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 495, in wrapper +[rank4]: return compiled_fn(runtime_args) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py", line 460, in __call__ +[rank4]: return self.current_callable(inputs) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 2404, in run +[rank4]: return model(new_inputs) +[rank4]: ^^^^^^^^^^^^^^^^^ +[rank4]: File "/tmp/torchinductor_root/xv/cxvmfi6yr3z46nbg55tjpsrom3ok6iubilxyghzmt6cmn3ihfv7y.py", line 130, in call +[rank4]: buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16) +[rank4]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank4]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 4 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128277 has 316.00 MiB memory in use. Process 3365139 has 316.00 MiB memory in use. Process 303040 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/4/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/4/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/5/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/5/error.json new file mode 100644 index 0000000000000000000000000000000000000000..94a77a2091e71ca9466bb2349a7fa6777d9831aa --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/5/error.json @@ -0,0 +1 @@ +{"message": {"message": "OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 5 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128278 has 316.00 MiB memory in use. Process 3365140 has 316.00 MiB memory in use. Process 303050 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 487, in main\n output = model(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py\", line 172, in wrapped_func\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 408, in forward\n outputs = self.model(\n ^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 278, in forward\n hidden_states, attentions, past_key_values = layer(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 92, in forward\n hidden_states = self.attn_norm(hidden_states)\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 93, in torch_dynamo_resume_in_forward_at_92\n hidden_states, attentions, past_key_values = self.attn(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 238, in forward\n q, conv_state_q = self.q_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 244, in torch_dynamo_resume_in_forward_at_238\n k, conv_state_k = self.k_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 250, in torch_dynamo_resume_in_forward_at_244\n v, conv_state_v = self.v_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 670, in forward\n y = causal_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 478, in causal_conv1d\n return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py\", line 575, in apply\n return super().apply(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py\", line 160, in wrapper\n return fn(*contiguous_args, **contiguous_kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 428, in forward\n return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in causal_conv1d_fwd\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 838, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py\", line 1209, in forward\n return compiled_fn(full_args)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 328, in runtime_wrapper\n all_outs = call_func_at_runtime_with_args(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py\", line 126, in call_func_at_runtime_with_args\n out = normalize_as_list(f(args))\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 689, in inner_fn\n outs = compiled_fn(args)\n ^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 495, in wrapper\n return compiled_fn(runtime_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py\", line 460, in __call__\n return self.current_callable(inputs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py\", line 2404, in run\n return model(new_inputs)\n ^^^^^^^^^^^^^^^^^\n File \"/tmp/torchinductor_root/pp/cppwpz6qtb6prvpzopyoqms52ohjl4ff6blw7cstonzobfbddotn.py\", line 130, in call\n buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 5 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128278 has 316.00 MiB memory in use. Process 3365140 has 316.00 MiB memory in use. Process 303050 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n", "timestamp": "1753238418"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/5/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/5/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..08f657f194c105b0974975183a5fda5a205c269e --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/5/stderr.log @@ -0,0 +1,587 @@ +[titan] 2025-07-23 10:36:20,382 - root - INFO - Starting job: default job +[titan] 2025-07-23 10:36:20,383 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-23 10:36:20,383 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-23 10:36:21,356 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-23 10:36:21,358 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:36:21,461 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:36:21,461 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-23 10:36:21,461 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-23 10:36:21,481 - root - INFO - Loading tokenizer... +[titan] 2025-07-23 10:36:21,911 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-23 10:36:21,912 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:21,912 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,394 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-23 10:36:22,394 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:36:22,394 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,394 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,942 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,973 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-23 10:37:12,974 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:12,974 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,974 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,234 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,322 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-23 10:37:13,322 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:13,322 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,323 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:19,506 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-23 10:37:20,187 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-23 10:37:20,318 - root - INFO - Building dataloader... +[titan] 2025-07-23 10:37:20,320 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-23 10:37:20,322 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[titan] 2025-07-23 10:37:22,833 - root - INFO -  +GatedDeltaNetForCausalLM( + (model): GatedDeltaNetModel( + (embeddings): Embedding(32000, 1024) + (layers): ModuleList( + (0-4): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (5): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (6-10): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (11): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (12-16): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (17): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (18-22): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (23): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + ) + (norm): RMSNorm(1024, eps=1e-06) + ) + (lm_head): Linear(in_features=1024, out_features=32000, bias=False) + (criterion): FusedLinearCrossEntropyLoss() +) + +[titan] 2025-07-23 10:37:22,869 - root - INFO - Compiling each block with torch.compile +[titan] 2025-07-23 10:37:22,869 - root - INFO - Compiling the embedding, norm, and lm_head layers with torch.compile +[titan] 2025-07-23 10:37:22,870 - root - INFO - Compiling the entire model with torch.compile +[titan] 2025-07-23 10:37:23,089 - root - INFO - Applied FSDP to the model +[titan] 2025-07-23 10:37:23,337 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `A_log` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:23,467 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `dt_bias` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:24,081 - root - INFO - CUDA memory usage for model: 0.19GiB(0.20%) +[titan] 2025-07-23 10:37:24,082 - root - WARNING - Warmup (100) + decay (95366) steps exceed total training steps (95366). Adjusting decay steps to 95266. +[titan] 2025-07-23 10:37:24,106 - root - INFO - Checkpointing active. Checkpoints will be loaded from and saved to /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/checkpoint +[titan] 2025-07-23 10:37:24,141 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:37:24,287 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:37:30,940 - root - INFO - ***** Running training ***** +[titan] 2025-07-23 10:37:30,942 - root - INFO -  Training starts at step 1 +[titan] 2025-07-23 10:37:30,942 - root - INFO -  Number of tokens per sequence = 8,192 +[titan] 2025-07-23 10:37:30,943 - root - INFO -  Gradient Accumulation steps = 1 +[titan] 2025-07-23 10:37:30,943 - root - INFO -  Instantaneous batch size (per device) = 16 +[titan] 2025-07-23 10:37:30,944 - root - INFO -  Global batch size (w. parallel, distributed & accumulation) = 128 (1,048,576 tokens) +[titan] 2025-07-23 10:37:30,944 - root - INFO -  Total optimization steps = 95,366 (99,998,498,816 tokens) +[titan] 2025-07-23 10:37:30,944 - root - INFO -  Warmup steps = 100 (104,857,600 tokens) +[titan] 2025-07-23 10:37:30,944 - root - INFO -  Number of parameters = 391,059,616  +[titan] 2025-07-23 10:37:30,944 - root - INFO - Profiling active. Traces will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/profile_trace +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py:1263: UserWarning: Dynamo does not know how to trace the builtin `cuda_utils.get_device_properties.` This function is either a Python builtin (e.g. _warnings.warn) or a third-party C/C++ Python extension (perhaps created with pybind). +If it is a Python builtin, please file an issue on GitHub so the PyTorch team can add support for it and see the next case for a workaround. +If it is a third-party C/C++ Python extension, please either wrap it into a PyTorch-understood custom operator (see https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html for more details) or, if it is traceable, use `torch.compiler.allow_in_graph`. + torch._dynamo.utils.warn_once(explanation + "\n" + "\n".join(hints)) +[rank5]: Traceback (most recent call last): +[rank5]: File "", line 198, in _run_module_as_main +[rank5]: File "", line 88, in _run_code +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank5]: main(config) +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank5]: return f(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 487, in main +[rank5]: output = model( +[rank5]: ^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank5]: return self._call_impl(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank5]: return inner() +[rank5]: ^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank5]: result = forward_call(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func +[rank5]: return func(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 408, in forward +[rank5]: outputs = self.model( +[rank5]: ^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank5]: return self._call_impl(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank5]: return forward_call(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 278, in forward +[rank5]: hidden_states, attentions, past_key_values = layer( +[rank5]: ^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank5]: return self._call_impl(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank5]: return inner() +[rank5]: ^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank5]: result = forward_call(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 655, in _fn +[rank5]: return fn(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank5]: return self._call_impl(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank5]: return forward_call(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 92, in forward +[rank5]: hidden_states = self.attn_norm(hidden_states) +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 93, in torch_dynamo_resume_in_forward_at_92 +[rank5]: hidden_states, attentions, past_key_values = self.attn( +[rank5]: ^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank5]: return self._call_impl(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank5]: return forward_call(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 238, in forward +[rank5]: q, conv_state_q = self.q_conv1d( +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 244, in torch_dynamo_resume_in_forward_at_238 +[rank5]: k, conv_state_k = self.k_conv1d( +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 250, in torch_dynamo_resume_in_forward_at_244 +[rank5]: v, conv_state_v = self.v_conv1d( +[rank5]: ^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank5]: return self._call_impl(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank5]: return forward_call(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 670, in forward +[rank5]: y = causal_conv1d( +[rank5]: ^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 478, in causal_conv1d +[rank5]: return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py", line 575, in apply +[rank5]: return super().apply(*args, **kwargs) # type: ignore[misc] +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py", line 160, in wrapper +[rank5]: return fn(*contiguous_args, **contiguous_kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 428, in forward +[rank5]: return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in causal_conv1d_fwd +[rank5]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282 +[rank5]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 838, in _fn +[rank5]: return fn(*args, **kwargs) +[rank5]: ^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py", line 1209, in forward +[rank5]: return compiled_fn(full_args) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 328, in runtime_wrapper +[rank5]: all_outs = call_func_at_runtime_with_args( +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py", line 126, in call_func_at_runtime_with_args +[rank5]: out = normalize_as_list(f(args)) +[rank5]: ^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 689, in inner_fn +[rank5]: outs = compiled_fn(args) +[rank5]: ^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 495, in wrapper +[rank5]: return compiled_fn(runtime_args) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py", line 460, in __call__ +[rank5]: return self.current_callable(inputs) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 2404, in run +[rank5]: return model(new_inputs) +[rank5]: ^^^^^^^^^^^^^^^^^ +[rank5]: File "/tmp/torchinductor_root/pp/cppwpz6qtb6prvpzopyoqms52ohjl4ff6blw7cstonzobfbddotn.py", line 130, in call +[rank5]: buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16) +[rank5]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank5]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 5 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128278 has 316.00 MiB memory in use. Process 3365140 has 316.00 MiB memory in use. Process 303050 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/5/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/5/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/6/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/6/error.json new file mode 100644 index 0000000000000000000000000000000000000000..4e2b70bffadeb68f03cf148c9b16b0703b8eb886 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/6/error.json @@ -0,0 +1 @@ +{"message": {"message": "OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 6 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128279 has 316.00 MiB memory in use. Process 3365141 has 316.00 MiB memory in use. Process 303053 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 487, in main\n output = model(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py\", line 172, in wrapped_func\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 408, in forward\n outputs = self.model(\n ^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 278, in forward\n hidden_states, attentions, past_key_values = layer(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 92, in forward\n hidden_states = self.attn_norm(hidden_states)\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 93, in torch_dynamo_resume_in_forward_at_92\n hidden_states, attentions, past_key_values = self.attn(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 238, in forward\n q, conv_state_q = self.q_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 244, in torch_dynamo_resume_in_forward_at_238\n k, conv_state_k = self.k_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 250, in torch_dynamo_resume_in_forward_at_244\n v, conv_state_v = self.v_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 670, in forward\n y = causal_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 478, in causal_conv1d\n return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py\", line 575, in apply\n return super().apply(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py\", line 160, in wrapper\n return fn(*contiguous_args, **contiguous_kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 428, in forward\n return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in causal_conv1d_fwd\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 838, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py\", line 1209, in forward\n return compiled_fn(full_args)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 328, in runtime_wrapper\n all_outs = call_func_at_runtime_with_args(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py\", line 126, in call_func_at_runtime_with_args\n out = normalize_as_list(f(args))\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 689, in inner_fn\n outs = compiled_fn(args)\n ^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 495, in wrapper\n return compiled_fn(runtime_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py\", line 460, in __call__\n return self.current_callable(inputs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py\", line 2404, in run\n return model(new_inputs)\n ^^^^^^^^^^^^^^^^^\n File \"/tmp/torchinductor_root/ol/colla2jf2yznlbsq3gnmt6dr6z53nuim5dyugjsmgbzld4lcsl2n.py\", line 130, in call\n buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 6 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128279 has 316.00 MiB memory in use. Process 3365141 has 316.00 MiB memory in use. Process 303053 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n", "timestamp": "1753238418"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/6/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/6/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..b98519d175f0b86ead186b349b69c34ad138ae06 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/6/stderr.log @@ -0,0 +1,587 @@ +[titan] 2025-07-23 10:36:20,373 - root - INFO - Starting job: default job +[titan] 2025-07-23 10:36:20,373 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-23 10:36:20,374 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-23 10:36:21,351 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-23 10:36:21,353 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:36:21,463 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:36:21,463 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-23 10:36:21,463 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-23 10:36:21,480 - root - INFO - Loading tokenizer... +[titan] 2025-07-23 10:36:21,911 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-23 10:36:21,912 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:21,912 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,386 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-23 10:36:22,386 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:36:22,386 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,386 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,802 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,833 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-23 10:37:12,833 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:12,834 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:12,834 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,082 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,167 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-23 10:37:13,167 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:13,167 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,167 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:19,422 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-23 10:37:20,093 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-23 10:37:20,209 - root - INFO - Building dataloader... +[titan] 2025-07-23 10:37:20,211 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-23 10:37:20,214 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[titan] 2025-07-23 10:37:22,830 - root - INFO -  +GatedDeltaNetForCausalLM( + (model): GatedDeltaNetModel( + (embeddings): Embedding(32000, 1024) + (layers): ModuleList( + (0-4): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (5): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (6-10): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (11): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (12-16): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (17): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (18-22): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (23): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + ) + (norm): RMSNorm(1024, eps=1e-06) + ) + (lm_head): Linear(in_features=1024, out_features=32000, bias=False) + (criterion): FusedLinearCrossEntropyLoss() +) + +[titan] 2025-07-23 10:37:22,866 - root - INFO - Compiling each block with torch.compile +[titan] 2025-07-23 10:37:22,866 - root - INFO - Compiling the embedding, norm, and lm_head layers with torch.compile +[titan] 2025-07-23 10:37:22,867 - root - INFO - Compiling the entire model with torch.compile +[titan] 2025-07-23 10:37:23,086 - root - INFO - Applied FSDP to the model +[titan] 2025-07-23 10:37:23,337 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `A_log` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:23,467 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `dt_bias` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:24,078 - root - INFO - CUDA memory usage for model: 0.19GiB(0.20%) +[titan] 2025-07-23 10:37:24,080 - root - WARNING - Warmup (100) + decay (95366) steps exceed total training steps (95366). Adjusting decay steps to 95266. +[titan] 2025-07-23 10:37:24,103 - root - INFO - Checkpointing active. Checkpoints will be loaded from and saved to /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/checkpoint +[titan] 2025-07-23 10:37:24,108 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:37:24,206 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:37:31,239 - root - INFO - ***** Running training ***** +[titan] 2025-07-23 10:37:31,242 - root - INFO -  Training starts at step 1 +[titan] 2025-07-23 10:37:31,243 - root - INFO -  Number of tokens per sequence = 8,192 +[titan] 2025-07-23 10:37:31,244 - root - INFO -  Gradient Accumulation steps = 1 +[titan] 2025-07-23 10:37:31,244 - root - INFO -  Instantaneous batch size (per device) = 16 +[titan] 2025-07-23 10:37:31,244 - root - INFO -  Global batch size (w. parallel, distributed & accumulation) = 128 (1,048,576 tokens) +[titan] 2025-07-23 10:37:31,244 - root - INFO -  Total optimization steps = 95,366 (99,998,498,816 tokens) +[titan] 2025-07-23 10:37:31,244 - root - INFO -  Warmup steps = 100 (104,857,600 tokens) +[titan] 2025-07-23 10:37:31,244 - root - INFO -  Number of parameters = 391,059,616  +[titan] 2025-07-23 10:37:31,245 - root - INFO - Profiling active. Traces will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/profile_trace +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py:1263: UserWarning: Dynamo does not know how to trace the builtin `cuda_utils.get_device_properties.` This function is either a Python builtin (e.g. _warnings.warn) or a third-party C/C++ Python extension (perhaps created with pybind). +If it is a Python builtin, please file an issue on GitHub so the PyTorch team can add support for it and see the next case for a workaround. +If it is a third-party C/C++ Python extension, please either wrap it into a PyTorch-understood custom operator (see https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html for more details) or, if it is traceable, use `torch.compiler.allow_in_graph`. + torch._dynamo.utils.warn_once(explanation + "\n" + "\n".join(hints)) +[rank6]: Traceback (most recent call last): +[rank6]: File "", line 198, in _run_module_as_main +[rank6]: File "", line 88, in _run_code +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank6]: main(config) +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank6]: return f(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 487, in main +[rank6]: output = model( +[rank6]: ^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank6]: return self._call_impl(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank6]: return inner() +[rank6]: ^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank6]: result = forward_call(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func +[rank6]: return func(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 408, in forward +[rank6]: outputs = self.model( +[rank6]: ^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank6]: return self._call_impl(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank6]: return forward_call(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 278, in forward +[rank6]: hidden_states, attentions, past_key_values = layer( +[rank6]: ^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank6]: return self._call_impl(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank6]: return inner() +[rank6]: ^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank6]: result = forward_call(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 655, in _fn +[rank6]: return fn(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank6]: return self._call_impl(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank6]: return forward_call(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 92, in forward +[rank6]: hidden_states = self.attn_norm(hidden_states) +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 93, in torch_dynamo_resume_in_forward_at_92 +[rank6]: hidden_states, attentions, past_key_values = self.attn( +[rank6]: ^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank6]: return self._call_impl(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank6]: return forward_call(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 238, in forward +[rank6]: q, conv_state_q = self.q_conv1d( +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 244, in torch_dynamo_resume_in_forward_at_238 +[rank6]: k, conv_state_k = self.k_conv1d( +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 250, in torch_dynamo_resume_in_forward_at_244 +[rank6]: v, conv_state_v = self.v_conv1d( +[rank6]: ^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank6]: return self._call_impl(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank6]: return forward_call(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 670, in forward +[rank6]: y = causal_conv1d( +[rank6]: ^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 478, in causal_conv1d +[rank6]: return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py", line 575, in apply +[rank6]: return super().apply(*args, **kwargs) # type: ignore[misc] +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py", line 160, in wrapper +[rank6]: return fn(*contiguous_args, **contiguous_kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 428, in forward +[rank6]: return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in causal_conv1d_fwd +[rank6]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282 +[rank6]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 838, in _fn +[rank6]: return fn(*args, **kwargs) +[rank6]: ^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py", line 1209, in forward +[rank6]: return compiled_fn(full_args) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 328, in runtime_wrapper +[rank6]: all_outs = call_func_at_runtime_with_args( +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py", line 126, in call_func_at_runtime_with_args +[rank6]: out = normalize_as_list(f(args)) +[rank6]: ^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 689, in inner_fn +[rank6]: outs = compiled_fn(args) +[rank6]: ^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 495, in wrapper +[rank6]: return compiled_fn(runtime_args) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py", line 460, in __call__ +[rank6]: return self.current_callable(inputs) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 2404, in run +[rank6]: return model(new_inputs) +[rank6]: ^^^^^^^^^^^^^^^^^ +[rank6]: File "/tmp/torchinductor_root/ol/colla2jf2yznlbsq3gnmt6dr6z53nuim5dyugjsmgbzld4lcsl2n.py", line 130, in call +[rank6]: buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16) +[rank6]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank6]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 6 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128279 has 316.00 MiB memory in use. Process 3365141 has 316.00 MiB memory in use. Process 303053 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/6/stdout.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/6/stdout.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/7/error.json b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/7/error.json new file mode 100644 index 0000000000000000000000000000000000000000..a8890c824fbb78593f2e8da94c6291684f2284d3 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/7/error.json @@ -0,0 +1 @@ +{"message": {"message": "OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 7 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128280 has 316.00 MiB memory in use. Process 3365142 has 316.00 MiB memory in use. Process 303060 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", "extraInfo": {"py_callstack": "Traceback (most recent call last):\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 355, in wrapper\n return f(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py\", line 487, in main\n output = model(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py\", line 172, in wrapped_func\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 408, in forward\n outputs = self.model(\n ^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 278, in forward\n hidden_states, attentions, past_key_values = layer(\n ^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1857, in _call_impl\n return inner()\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1805, in inner\n result = forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 92, in forward\n hidden_states = self.attn_norm(hidden_states)\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py\", line 93, in torch_dynamo_resume_in_forward_at_92\n hidden_states, attentions, past_key_values = self.attn(\n ^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 238, in forward\n q, conv_state_q = self.q_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 244, in torch_dynamo_resume_in_forward_at_238\n k, conv_state_k = self.k_conv1d(\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py\", line 250, in torch_dynamo_resume_in_forward_at_244\n v, conv_state_v = self.v_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 670, in forward\n y = causal_conv1d(\n ^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 478, in causal_conv1d\n return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py\", line 575, in apply\n return super().apply(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py\", line 160, in wrapper\n return fn(*contiguous_args, **contiguous_kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 428, in forward\n return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in causal_conv1d_fwd\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py\", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282\n BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index))))\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 838, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py\", line 1209, in forward\n return compiled_fn(full_args)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 328, in runtime_wrapper\n all_outs = call_func_at_runtime_with_args(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py\", line 126, in call_func_at_runtime_with_args\n out = normalize_as_list(f(args))\n ^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 689, in inner_fn\n outs = compiled_fn(args)\n ^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py\", line 495, in wrapper\n return compiled_fn(runtime_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py\", line 460, in __call__\n return self.current_callable(inputs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py\", line 2404, in run\n return model(new_inputs)\n ^^^^^^^^^^^^^^^^^\n File \"/tmp/torchinductor_root/ab/cabkgxsgwike5ls6n6th3bjdoagzhwbzueq53qpicujk2k7n2lnx.py\", line 130, in call\n buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 7 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128280 has 316.00 MiB memory in use. Process 3365142 has 316.00 MiB memory in use. Process 303060 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n", "timestamp": "1753238418"}}} \ No newline at end of file diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/7/stderr.log b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/7/stderr.log new file mode 100644 index 0000000000000000000000000000000000000000..08ca257f073f90db56ca2cf519d73727f638d8e4 --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/logs/none_hp1j2ryu/attempt_0/7/stderr.log @@ -0,0 +1,587 @@ +[titan] 2025-07-23 10:36:20,105 - root - INFO - Starting job: default job +[titan] 2025-07-23 10:36:20,106 - root - INFO - { + "activation_checkpoint": { + "mode": "none", + "selective_ac_option": "2" + }, + "activation_offload": { + "mode": "none" + }, + "checkpoint": { + "async_mode": "disabled", + "create_seed_checkpoint": false, + "enable_checkpoint": true, + "exclude_from_loading": [], + "export_dtype": "float32", + "folder": "checkpoint", + "interval": 8192, + "interval_type": "steps", + "keep_latest_k": 100, + "load_step": -1, + "model_weights_only": false + }, + "comm": { + "init_timeout_seconds": 300, + "trace_buf_size": 20000, + "train_timeout_seconds": 100 + }, + "experimental": { + "context_parallel_degree": 1, + "context_parallel_rotate_method": "allgather", + "custom_model_path": "", + "enable_async_tensor_parallel": false, + "enable_compiled_autograd": false, + "pipeline_parallel_degree": 1, + "pipeline_parallel_microbatches": null, + "pipeline_parallel_schedule": "1F1B", + "pipeline_parallel_schedule_csv": "", + "pipeline_parallel_split_points": [] + }, + "fault_tolerance": { + "enable": false, + "group_size": 0, + "min_replica_size": 1, + "replica_id": 0 + }, + "float8": { + "enable_fsdp_float8_all_gather": false, + "force_recompute_fp8_weight_in_bwd": false, + "precompute_float8_dynamic_scale_for_fsdp": false, + "recipe_name": null + }, + "job": { + "config_file": "flame/models/fla.toml", + "description": "default job", + "dump_folder": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1", + "print_args": true, + "use_for_integration_test": false + }, + "lr_scheduler": { + "decay_ratio": 1.0, + "decay_type": "linear", + "lr_min": 0.01, + "warmup_steps": 100 + }, + "memory_estimation": { + "disable_fake_mode": false, + "enabled": false + }, + "metrics": { + "disable_color_printing": false, + "enable_tensorboard": true, + "enable_wandb": true, + "log_freq": 1, + "save_for_all_ranks": false, + "save_tb_folder": "tb" + }, + "model": { + "config": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json", + "converters": [], + "name": "fla", + "print_after_conversion": false, + "tokenizer_path": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer" + }, + "optimizer": { + "early_step_in_backward": false, + "eps": 1e-08, + "implementation": "fused", + "lr": 0.0003, + "name": "AdamW" + }, + "profiling": { + "enable_memory_snapshot": false, + "enable_profiling": true, + "profile_freq": 512, + "save_memory_snapshot_folder": "memory_snapshot", + "save_traces_folder": "profile_trace" + }, + "training": { + "batch_size": 16, + "compile": true, + "context_len": 8192, + "data_dir": null, + "data_files": null, + "data_parallel_replicate_degree": 1, + "data_parallel_shard_degree": -1, + "data_probs": "0.55,0.3,0.15", + "dataset": "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro", + "dataset_name": "default,default,default", + "dataset_split": "train,train,train", + "deterministic": false, + "disable_loss_parallel": false, + "enable_cpu_offload": false, + "fsdp_reshard_after_forward": "default", + "gc_freq": 50, + "gradient_accumulation_steps": 1, + "max_norm": 1.0, + "mixed_precision_param": "bfloat16", + "mixed_precision_reduce": "float32", + "num_workers": 32, + "persistent_workers": false, + "pin_memory": false, + "prefetch_factor": 2, + "seed": 42, + "seq_len": 8192, + "skip_nan_inf": true, + "steps": 95366, + "streaming": true, + "tensor_parallel_degree": 1, + "varlen": false + } +} +[titan] 2025-07-23 10:36:20,106 - root - INFO - [GC] Initial GC collection. 0.00 seconds. +[titan] 2025-07-23 10:36:21,157 - root - WARNING - ENV[TORCH_NCCL_ASYNC_ERROR_HANDLING] = 1 will be overridden to 3 based on job config +[titan] 2025-07-23 10:36:21,159 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:36:21,247 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:36:21,247 - root - INFO - Peak FLOPS used for computing MFU: 3.120e+14 +[titan] 2025-07-23 10:36:21,247 - root - INFO - Building 1-D device mesh with ['dp_shard'], [8] +[titan] 2025-07-23 10:36:21,367 - root - INFO - Loading tokenizer... +[titan] 2025-07-23 10:36:21,911 - root - INFO - LlamaTokenizerFast(name_or_path='/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/tokenizer', vocab_size=32000, model_max_length=10000000000, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': ''}, clean_up_tokenization_spaces=False, added_tokens_decoder={ + 0: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 1: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), + 2: AddedToken("", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), +} +) +[titan] 2025-07-23 10:36:21,912 - root - INFO - Loading dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged,/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default,default,default +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:21,913 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,388 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample:default (p = 0.550): +IterableDataset({ + features: ['text', 'id', 'dump', 'url', 'file_path', 'language', 'language_score', 'token_count', 'score', 'int_score'], + num_shards: 140 +}) +[titan] 2025-07-23 10:36:22,388 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:36:22,388 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample has insufficient shards (140). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:36:22,388 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/fineweb-edu-sample' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,840 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,884 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged:default (p = 0.300): +IterableDataset({ + features: ['repo', 'content'], + num_shards: 1 +}) +[titan] 2025-07-23 10:37:13,884 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:13,884 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged has insufficient shards (1). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:13,884 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/small_repos_20B_sample_merged' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,138 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,226 - root - INFO - Subset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro:default (p = 0.150): +IterableDataset({ + features: ['text', 'cc-path', 'domain', 'lang', 'lang_score', 'timestamp', 'url', 'math_score'], + num_shards: 100 +}) +[titan] 2025-07-23 10:37:14,226 - root - INFO - Shuffling the dataset with seed 42 +[titan] 2025-07-23 10:37:14,226 - root - WARNING - Dataset /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro has insufficient shards (100). Need 256 shards minimum for desired data parallel workers × 32 dataloader workers. Resharding dataset to 256 shards and disabling streaming mode. +`trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:14,226 - datasets.load - ERROR - `trust_remote_code` is not supported anymore. +Please check that the Hugging Face dataset '/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/dataset/megamath-web-pro' isn't based on a loading script and remove `trust_remote_code`. +If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet. +[titan] 2025-07-23 10:37:20,449 - root - INFO - Interleaving 3 datasets with probabilities [0.55, 0.3, 0.15] +[titan] 2025-07-23 10:37:21,134 - root - INFO - IterableDataset({ + features: ['text', 'content'], + num_shards: 256 +}) +[titan] 2025-07-23 10:37:21,252 - root - INFO - Building dataloader... +[titan] 2025-07-23 10:37:21,254 - root - INFO - Loading model config from /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/configs/gdn_6_1_340M.json +[titan] 2025-07-23 10:37:21,256 - root - INFO - Building model from the config +GatedDeltaNetConfig { + "allow_neg_eigval": false, + "architectures": [ + "GatedDeltaNetForCausalLM" + ], + "attn": { + "layers": [ + 5, + 11, + 17, + 23 + ], + "num_heads": 16, + "num_kv_heads": 8, + "qkv_bias": false, + "rope_theta": 160000.0, + "window_size": null + }, + "attn_mode": "chunk", + "bos_token_id": 1, + "conv_size": 4, + "eos_token_id": 2, + "expand_k": 1, + "expand_v": 1, + "fuse_cross_entropy": true, + "fuse_norm": true, + "fuse_swiglu": true, + "head_dim": 256, + "hidden_act": "swish", + "hidden_ratio": 4, + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": null, + "max_position_embeddings": 8192, + "model_type": "gated_deltanet", + "norm_eps": 1e-06, + "norm_first": false, + "num_heads": 4, + "num_hidden_layers": 24, + "num_v_heads": null, + "qk_activation": "silu", + "qk_norm": "l2", + "tie_word_embeddings": false, + "torch_dtype": "float32", + "transformers_version": "4.53.3", + "use_beta": true, + "use_cache": true, + "use_gate": true, + "use_l2warp": false, + "use_output_norm": true, + "use_short_conv": true, + "vocab_size": 32000 +} + +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py:593: UserWarning: The `backend` parameter is set to `cuda`, but `causal_conv1d_fn` is not available. Switching to the Triton implementation instead. Consider installing `causal_conv1d` to enable the CUDA backend. + warnings.warn( +[titan] 2025-07-23 10:37:22,830 - root - INFO -  +GatedDeltaNetForCausalLM( + (model): GatedDeltaNetModel( + (embeddings): Embedding(32000, 1024) + (layers): ModuleList( + (0-4): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (5): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (6-10): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (11): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (12-16): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (17): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (18-22): 5 x GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): GatedDeltaNet( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=1024, bias=False) + (v_proj): Linear(in_features=1024, out_features=1024, bias=False) + (a_proj): Linear(in_features=1024, out_features=4, bias=False) + (b_proj): Linear(in_features=1024, out_features=4, bias=False) + (q_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (k_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (v_conv1d): ShortConvolution(1024, 1024, kernel_size=(4,), stride=(1,), padding=(3,), groups=1024, bias=False, activation=silu, backend=triton) + (g_proj): Linear(in_features=1024, out_features=1024, bias=False) + (o_norm): FusedRMSNormGated(256, eps=1e-06, activation=swish) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + (23): GatedDeltaNetBlock( + (attn_norm): RMSNorm(1024, eps=1e-06) + (attn): Attention( + (q_proj): Linear(in_features=1024, out_features=1024, bias=False) + (k_proj): Linear(in_features=1024, out_features=512, bias=False) + (v_proj): Linear(in_features=1024, out_features=512, bias=False) + (o_proj): Linear(in_features=1024, out_features=1024, bias=False) + (rotary): RotaryEmbedding(dim=64, base=160000.0, interleaved=False, pos_idx_in_fp32=True) + ) + (mlp_norm): RMSNorm(1024, eps=1e-06) + (mlp): GatedMLP( + (gate_proj): Linear(in_features=1024, out_features=2816, bias=False) + (up_proj): Linear(in_features=1024, out_features=2816, bias=False) + (down_proj): Linear(in_features=2816, out_features=1024, bias=False) + (swiglu_linear): SwiGLULinear() + ) + ) + ) + (norm): RMSNorm(1024, eps=1e-06) + ) + (lm_head): Linear(in_features=1024, out_features=32000, bias=False) + (criterion): FusedLinearCrossEntropyLoss() +) + +[titan] 2025-07-23 10:37:22,866 - root - INFO - Compiling each block with torch.compile +[titan] 2025-07-23 10:37:22,866 - root - INFO - Compiling the embedding, norm, and lm_head layers with torch.compile +[titan] 2025-07-23 10:37:22,866 - root - INFO - Compiling the entire model with torch.compile +[titan] 2025-07-23 10:37:23,112 - root - INFO - Applied FSDP to the model +[titan] 2025-07-23 10:37:23,337 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `A_log` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:23,467 - fla.models.gated_deltanet.modeling_gated_deltanet - WARNING - `dt_bias` is a DTensor, skipping initialization +[titan] 2025-07-23 10:37:24,098 - root - INFO - CUDA memory usage for model: 0.19GiB(0.20%) +[titan] 2025-07-23 10:37:24,099 - root - WARNING - Warmup (100) + decay (95366) steps exceed total training steps (95366). Adjusting decay steps to 95266. +[titan] 2025-07-23 10:37:24,123 - root - INFO - Checkpointing active. Checkpoints will be loaded from and saved to /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/checkpoint +[titan] 2025-07-23 10:37:24,132 - root - INFO - CUDA capacity: NVIDIA H20 with 95.00GiB memory +[titan] 2025-07-23 10:37:24,285 - root - WARNING - Peak flops undefined for: NVIDIA H20, fallback to A100 +[titan] 2025-07-23 10:37:31,211 - root - INFO - ***** Running training ***** +[titan] 2025-07-23 10:37:31,213 - root - INFO -  Training starts at step 1 +[titan] 2025-07-23 10:37:31,214 - root - INFO -  Number of tokens per sequence = 8,192 +[titan] 2025-07-23 10:37:31,214 - root - INFO -  Gradient Accumulation steps = 1 +[titan] 2025-07-23 10:37:31,214 - root - INFO -  Instantaneous batch size (per device) = 16 +[titan] 2025-07-23 10:37:31,214 - root - INFO -  Global batch size (w. parallel, distributed & accumulation) = 128 (1,048,576 tokens) +[titan] 2025-07-23 10:37:31,214 - root - INFO -  Total optimization steps = 95,366 (99,998,498,816 tokens) +[titan] 2025-07-23 10:37:31,215 - root - INFO -  Warmup steps = 100 (104,857,600 tokens) +[titan] 2025-07-23 10:37:31,215 - root - INFO -  Number of parameters = 391,059,616  +[titan] 2025-07-23 10:37:31,215 - root - INFO - Profiling active. Traces will be saved at /mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/pretrain-linear-moe/flame/exp/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/profile_trace +/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py:1263: UserWarning: Dynamo does not know how to trace the builtin `cuda_utils.get_device_properties.` This function is either a Python builtin (e.g. _warnings.warn) or a third-party C/C++ Python extension (perhaps created with pybind). +If it is a Python builtin, please file an issue on GitHub so the PyTorch team can add support for it and see the next case for a workaround. +If it is a third-party C/C++ Python extension, please either wrap it into a PyTorch-understood custom operator (see https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html for more details) or, if it is traceable, use `torch.compiler.allow_in_graph`. + torch._dynamo.utils.warn_once(explanation + "\n" + "\n".join(hints)) +[rank7]: Traceback (most recent call last): +[rank7]: File "", line 198, in _run_module_as_main +[rank7]: File "", line 88, in _run_code +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 615, in +[rank7]: main(config) +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper +[rank7]: return f(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/flame/train.py", line 487, in main +[rank7]: output = model( +[rank7]: ^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank7]: return self._call_impl(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank7]: return inner() +[rank7]: ^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank7]: result = forward_call(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func +[rank7]: return func(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 408, in forward +[rank7]: outputs = self.model( +[rank7]: ^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank7]: return self._call_impl(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank7]: return forward_call(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 278, in forward +[rank7]: hidden_states, attentions, past_key_values = layer( +[rank7]: ^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank7]: return self._call_impl(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1857, in _call_impl +[rank7]: return inner() +[rank7]: ^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1805, in inner +[rank7]: result = forward_call(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 655, in _fn +[rank7]: return fn(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank7]: return self._call_impl(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank7]: return forward_call(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 92, in forward +[rank7]: hidden_states = self.attn_norm(hidden_states) +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/models/gated_deltanet/modeling_gated_deltanet.py", line 93, in torch_dynamo_resume_in_forward_at_92 +[rank7]: hidden_states, attentions, past_key_values = self.attn( +[rank7]: ^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank7]: return self._call_impl(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank7]: return forward_call(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 238, in forward +[rank7]: q, conv_state_q = self.q_conv1d( +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 244, in torch_dynamo_resume_in_forward_at_238 +[rank7]: k, conv_state_k = self.k_conv1d( +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/layers/gated_deltanet.py", line 250, in torch_dynamo_resume_in_forward_at_244 +[rank7]: v, conv_state_v = self.v_conv1d( +[rank7]: ^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl +[rank7]: return self._call_impl(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl +[rank7]: return forward_call(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 670, in forward +[rank7]: y = causal_conv1d( +[rank7]: ^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 478, in causal_conv1d +[rank7]: return CausalConv1dFunction.apply(x, weight, bias, residual, activation, cu_seqlens) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/autograd/function.py", line 575, in apply +[rank7]: return super().apply(*args, **kwargs) # type: ignore[misc] +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/utils.py", line 160, in wrapper +[rank7]: return fn(*contiguous_args, **contiguous_kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 428, in forward +[rank7]: return causal_conv1d_fwd(x, weight, bias, residual, activation, cu_seqlens) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in causal_conv1d_fwd +[rank7]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flash-linear-attention/fla/modules/convolution.py", line 282, in torch_dynamo_resume_in_causal_conv1d_fwd_at_282 +[rank7]: BT = min(64, triton.next_power_of_2(triton.cdiv(max(16, B*T), get_multiprocessor_count(x.device.index)))) +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 838, in _fn +[rank7]: return fn(*args, **kwargs) +[rank7]: ^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/aot_autograd.py", line 1209, in forward +[rank7]: return compiled_fn(full_args) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 328, in runtime_wrapper +[rank7]: all_outs = call_func_at_runtime_with_args( +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/utils.py", line 126, in call_func_at_runtime_with_args +[rank7]: out = normalize_as_list(f(args)) +[rank7]: ^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 689, in inner_fn +[rank7]: outs = compiled_fn(args) +[rank7]: ^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_functorch/_aot_autograd/runtime_wrappers.py", line 495, in wrapper +[rank7]: return compiled_fn(runtime_args) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/output_code.py", line 460, in __call__ +[rank7]: return self.current_callable(inputs) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: File "/mnt/nanjingcephfs/project_wx-rec-alg-bdc-exp/bwzheng/yulan/hyw/dataset/Selection/pretrain-linear-moe/flame/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 2404, in run +[rank7]: return model(new_inputs) +[rank7]: ^^^^^^^^^^^^^^^^^ +[rank7]: File "/tmp/torchinductor_root/ab/cabkgxsgwike5ls6n6th3bjdoagzhwbzueq53qpicujk2k7n2lnx.py", line 130, in call +[rank7]: buf0 = empty_strided_cuda((16, 8192, 1024), (8388608, 1024, 1), torch.bfloat16) +[rank7]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +[rank7]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 7 has a total capacity of 95.00 GiB of which 32.94 MiB is free. Process 4128280 has 316.00 MiB memory in use. Process 3365142 has 316.00 MiB memory in use. Process 303060 has 94.34 GiB memory in use. Of the allocated memory 91.43 GiB is allocated by PyTorch, and 114.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. 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15823, + "▁Jenn": 15824, + "▁erst": 15825, + "Actions": 15826, + "Environment": 15827, + "via": 15828, + "▁struggling": 15829, + "▁DVD": 15830, + "whe": 15831, + "▁throwing": 15832, + "Bounds": 15833, + "▁MD": 15834, + "▁\"../": 15835, + "▁satisfy": 15836, + "▁Colorado": 15837, + "▁Active": 15838, + "Tasks": 15839, + "<>();": 15840, + "▁slipped": 15841, + "▁poison": 15842, + "zb": 15843, + "Dispatch": 15844, + "warning": 15845, + "▁ultimate": 15846, + "picture": 15847, + "expression": 15848, + "▁Talk": 15849, + "▁flick": 15850, + "▁raising": 15851, + "▁transactions": 15852, + "▁glance": 15853, + "▁gri": 15854, + "▁през": 15855, + "selection": 15856, + "ња": 15857, + "endl": 15858, + "▁Abb": 15859, + "▁bold": 15860, + "▁maintained": 15861, + "Exists": 15862, + "▁encouraged": 15863, + "Qual": 15864, + "▁essere": 15865, + "▁hired": 15866, + "letter": 15867, + "itches": 15868, + "others": 15869, + "▁woj": 15870, + "▁injuries": 15871, + "▁dil": 15872, + "execut": 15873, + "▁Steel": 15874, + "▁Garden": 15875, + "зя": 15876, + "\\,\\": 15877, + "▁Angel": 15878, + "prim": 15879, + ">:]<": 15880, + "gb": 15881, + "peat": 15882, + "inte": 15883, + "▁apolog": 15884, + "▁regulations": 15885, + "Src": 15886, + "kh": 15887, + "Upload": 15888, + "mapping": 15889, + "▁presents": 15890, + "▁poetry": 15891, + "▁stops": 15892, + "▁Tol": 15893, + "▁tower": 15894, + "▁OUT": 15895, + "Thank": 15896, + "▁organic": 15897, + "▁drei": 15898, + "▁pound": 15899, + "century": 15900, + "▁modules": 15901, + "▁дере": 15902, + "▁worn": 15903, + "▁parad": 15904, + "▁Cos": 15905, + "fic": 15906, + "▁без": 15907, + "▁Jimmy": 15908, + "▁lands": 15909, + "▁minist": 15910, + "vspace": 15911, + "▁lighting": 15912, + "▁naked": 15913, + "▁designer": 15914, + "▁Stream": 15915, + "TMP": 15916, + "Center": 15917, + "resentation": 15918, + "ONT": 15919, + "▁ers": 15920, + "▁measurement": 15921, + "▁muscles": 15922, + "▁Ign": 15923, + "▁COM": 15924, + "▁fru": 15925, + "▁genre": 15926, + "▁alpha": 15927, + "▁retirement": 15928, + "▁Gon": 15929, + "ől": 15930, + "contents": 15931, + "▁healing": 15932, + "▁sido": 15933, + "incipal": 15934, + "Permission": 15935, + "рак": 15936, + "▁Gordon": 15937, + "▁Rank": 15938, + "▁Autom": 15939, + "Constructor": 15940, + "wiki": 15941, + "▁concerning": 15942, + "rizona": 15943, + "▁variant": 15944, + "▁arranged": 15945, + "▁Spr": 15946, + "BPACK": 15947, + "Timestamp": 15948, + "restore": 15949, + "aware": 15950, + "▁Observ": 15951, + "▁SV": 15952, + "ipp": 15953, + "▁Executive": 15954, + "▁colleg": 15955, + "▁explicitly": 15956, + "written": 15957, + "▁Kön": 15958, + "irus": 15959, + "▁Hold": 15960, + "▁Pract": 15961, + "Character": 15962, + "▁redistribute": 15963, + "uerto": 15964, + "▁Student": 15965, + "▁elder": 15966, + "▁Dop": 15967, + "vp": 15968, + "▁Hub": 15969, + "▁grounds": 15970, + "▁Ry": 15971, + "▁signals": 15972, + "▁gifts": 15973, + "▁strengthen": 15974, + "▁Lyn": 15975, + "commun": 15976, + "▁най": 15977, + "▁finance": 15978, + "noc": 15979, + "helm": 15980, + "▁cuts": 15981, + "▁adventure": 15982, + "▁Ric": 15983, + "▁intellectual": 15984, + "▁Output": 15985, + "▁awk": 15986, + "▁concentration": 15987, + "▁guidance": 15988, + "Buff": 15989, + "▁filling": 15990, + "▁regul": 15991, + "▁delicious": 15992, + "([]": 15993, + "ших": 15994, + "▁tons": 15995, + "activity": 15996, + "GP": 15997, + "LOB": 15998, + "stadt": 15999, + "tal": 16000, + "▁img": 16001, + "▁rush": 16002, + "attice": 16003, + "▁pok": 16004, + "steps": 16005, + "▁lid": 16006, + "▁DNA": 16007, + "Browser": 16008, + "▁ladies": 16009, + "▁années": 16010, + "▁rescue": 16011, + "avity": 16012, + "rock": 16013, + "▁glasses": 16014, + "▁Bey": 16015, + ")}$": 16016, + "detail": 16017, + "▁dés": 16018, + "tax": 16019, + "▁favourite": 16020, + "▁precision": 16021, + "▁conoc": 16022, + "Ms": 16023, + "▁Native": 16024, + "▁Pil": 16025, + "InputStream": 16026, + "orp": 16027, + "▁Pap": 16028, + "▁picking": 16029, + "iph": 16030, + "Loading": 16031, + "▁priest": 16032, + "Hook": 16033, + "▁pist": 16034, + "▁Une": 16035, + "%,": 16036, + "▁bil": 16037, + "▁conservative": 16038, + "eval": 16039, + "iking": 16040, + "'},": 16041, + "▁sauce": 16042, + "▁Due": 16043, + "assen": 16044, + "▁occasionally": 16045, + "▁Дж": 16046, + "unknown": 16047, + "DED": 16048, + "▁drum": 16049, + "▁dub": 16050, + "ATURE": 16051, + "usage": 16052, + "getType": 16053, + "reply": 16054, + "▁strategic": 16055, + "▁kap": 16056, + "design": 16057, + "datetime": 16058, + "▁Prim": 16059, + "Master": 16060, + "▁Corps": 16061, + "▁considerable": 16062, + "▁Tu": 16063, + "▁ла": 16064, + "▁tous": 16065, + "▁clar": 16066, + "▁poem": 16067, + "album": 16068, + "]*": 16069, + "loaded": 16070, + "▁traveling": 16071, + "вые": 16072, + "▁Ferr": 16073, + "▁pharm": 16074, + "abi": 16075, + "▁}\\": 16076, + "collect": 16077, + "▁Bour": 16078, + "OC": 16079, + "▁measurements": 16080, + "▁Professional": 16081, + "▁sensor": 16082, + "utsche": 16083, + "▁demanded": 16084, + "▁accompanied": 16085, + "▁prend": 16086, + "▁encoding": 16087, + "▁Geschichte": 16088, + "▁mig": 16089, + "▁Gib": 16090, + "▁Reich": 16091, + "▁myster": 16092, + "▁Mock": 16093, + "▁physically": 16094, + "▁Bau": 16095, + "▁Single": 16096, + "▁managing": 16097, + "▁Kil": 16098, + "▁Temple": 16099, + "▁lev": 16100, + "▁lí": 16101, + "CPU": 16102, + "▁Premier": 16103, + "▁Give": 16104, + "iri": 16105, + "NV": 16106, + "▁AI": 16107, + "▁fp": 16108, + "лександ": 16109, + "▁tant": 16110, + "▁fot": 16111, + "Nullable": 16112, + "▁guards": 16113, + "Once": 16114, + "▁chamber": 16115, + "film": 16116, + "▁bias": 16117, + "▁Tai": 16118, + "insic": 16119, + "▁ml": 16120, + "▁Ka": 16121, + "вал": 16122, + "▁SER": 16123, + "▁Someone": 16124, + "}}_{": 16125, + "Fixed": 16126, + "▁bent": 16127, + "▁prohib": 16128, + "▁bid": 16129, + "▁fewer": 16130, + "кры": 16131, + "▁lugar": 16132, + "▁deserve": 16133, + "ssl": 16134, + "▁cfg": 16135, + "reck": 16136, + "▁stability": 16137, + "resize": 16138, + "▁assertThat": 16139, + "Trigger": 16140, + "▁станов": 16141, + "plugins": 16142, + "▁lets": 16143, + "хід": 16144, + "▁Laura": 16145, + "нер": 16146, + "▁brut": 16147, + "▁FI": 16148, + "isons": 16149, + "▁dyn": 16150, + "icher": 16151, + "rayed": 16152, + "▁frequent": 16153, + "▁jedoch": 16154, + "▁Marine": 16155, + "strings": 16156, + "▁Util": 16157, + "▁bos": 16158, + "Mus": 16159, + "▁Portugal": 16160, + "Strategy": 16161, + "▁посе": 16162, + "▁slice": 16163, + "▁insight": 16164, + "▁widget": 16165, + "▁général": 16166, + "messages": 16167, + "▁Hu": 16168, + "▁requirement": 16169, + "Side": 16170, + "emplates": 16171, + "▁ceremony": 16172, + "▁physics": 16173, + "▁graduate": 16174, + "para": 16175, + "▁preserv": 16176, + "▁shops": 16177, + "zek": 16178, + "▁ub": 16179, + "prepare": 16180, + "▁Oil": 16181, + "▁fib": 16182, + "▁runtime": 16183, + "▁hogy": 16184, + "Warning": 16185, + "▁Convert": 16186, + "bourne": 16187, + "▁emerged": 16188, + "▁Ди": 16189, + "ighth": 16190, + "guard": 16191, + "kal": 16192, + "validation": 16193, + "ência": 16194, + "▁drinks": 16195, + "theorem": 16196, + "HR": 16197, + "iev": 16198, + "ployee": 16199, + "Usage": 16200, + "▁спе": 16201, + "dispatch": 16202, + "▁instantly": 16203, + "obi": 16204, + "▁justify": 16205, + "▁Nev": 16206, + "▁явля": 16207, + "agra": 16208, + "▁transmission": 16209, + "fly": 16210, + ";';": 17021, + "▁cousin": 17022, + "createElement": 17023, + "Could": 17024, + "▁capac": 17025, + "▁pause": 17026, + "ArrayList": 17027, + "kte": 17028, + "ordered": 17029, + "▁shaking": 17030, + "labels": 17031, + "▁reducing": 17032, + "вых": 17033, + "USED": 17034, + "▁voting": 17035, + "▁Ministry": 17036, + "▁Mig": 17037, + "▁Chen": 17038, + "▁accompany": 17039, + "ulle": 17040, + "▁ga": 17041, + "▁equipped": 17042, + "▁nun": 17043, + "Bet": 17044, + "▁licensed": 17045, + "ARCH": 17046, + "FN": 17047, + "▁engines": 17048, + "▁ster": 17049, + "▁locale": 17050, + "▁въ": 17051, + "links": 17052, + "▁Capital": 17053, + "▁alien": 17054, + "Wr": 17055, + "ръ": 17056, + "Cart": 17057, + "▁Marketing": 17058, + "▁RT": 17059, + "FileName": 17060, + "▁ti": 17061, + "iji": 17062, + "▁versus": 17063, + "live": 17064, + "Sym": 17065, + "kor": 17066, + "▁emission": 17067, + "umm": 17068, + "ycz": 17069, + "▁climbed": 17070, + "▁plusieurs": 17071, + "кри": 17072, + "yar": 17073, + "osten": 17074, + "▁usb": 17075, + "▁crossing": 17076, + "▁polynom": 17077, + "▁removal": 17078, + "▁Adams": 17079, + "▁ihre": 17080, + "anden": 17081, + "▁Benj": 17082, + "▁Phill": 17083, + "▁wounded": 17084, + "▁Castle": 17085, + "bild": 17086, + "Annotation": 17087, + "Processor": 17088, + "▁tin": 17089, + "folg": 17090, + "▁Students": 17091, + "▁Mexican": 17092, + "▁administrative": 17093, + "ILED": 17094, + "▁conqu": 17095, + "▁cheer": 17096, + "▁Ces": 17097, + "Because": 17098, + "▁Juni": 17099, + "▁encontr": 17100, + "avi": 17101, + "VI": 17102, + "aku": 17103, + "▁Ton": 17104, + "▁smoking": 17105, + "▁bay": 17106, + "works": 17107, + "ат": 17108, + "attered": 17109, + "▁Boolean": 17110, + "▁Balt": 17111, + "defer": 17112, + "pathy": 17113, + "Ah": 17114, + "▁akt": 17115, + "▁governor": 17116, + "Pad": 17117, + "▁sisters": 17118, + "Lat": 17119, + "▁revel": 17120, + "▁SY": 17121, + "itos": 17122, + "▁filters": 17123, + "Chunk": 17124, + "consum": 17125, + "▁removing": 17126, + "▁Herr": 17127, + "▁generator": 17128, + "▁Cra": 17129, + "▁farmers": 17130, + "▁Members": 17131, + "▁overcome": 17132, + "▁Cin": 17133, + "igkeit": 17134, + "criptions": 17135, + "Tests": 17136, + "▁клу": 17137, + "▁shake": 17138, + "▁yy": 17139, + "placement": 17140, + "▁awards": 17141, + "▁episodes": 17142, + "▁Blood": 17143, + "▁bullet": 17144, + "▁viene": 17145, + "▁Financial": 17146, + "Future": 17147, + "▁rou": 17148, + "▁biologie": 17149, + "▁useState": 17150, + "iani": 17151, + "piece": 17152, + "▁speaker": 17153, + "▁refr": 17154, + "ARK": 17155, + "▁MIT": 17156, + "▁Tan": 17157, + "▁Based": 17158, + "▁cultiv": 17159, + "▁hungry": 17160, + "▁Ay": 17161, + "▁Hey": 17162, + "▁excitement": 17163, + "ibraries": 17164, + "Hit": 17165, + "▁Ende": 17166, + "NG": 17167, + "FIL": 17168, + ".\")": 17169, + "Family": 17170, + "inery": 17171, + "necess": 17172, + "velope": 17173, + "▁Bot": 17174, + "porter": 17175, + "▁climb": 17176, + "▁Eli": 17177, + "urent": 17178, + "▁mistakes": 17179, + "ában": 17180, + "marks": 17181, + "pkt": 17182, + "Library": 17183, + "sted": 17184, + "ublice": 17185, + "▁Administration": 17186, + "▁shapes": 17187, + "публи": 17188, + "God": 17189, + "innen": 17190, + "коло": 17191, + "<<<<": 17192, + "ibe": 17193, + "ês": 17194, + "▁США": 17195, + "▁Foreign": 17196, + "▁Margaret": 17197, + "▁gene": 17198, + "▁disturb": 17199, + "▁тер": 17200, + "▁onClick": 17201, + "▁Engineering": 17202, + "▁stopping": 17203, + "▁restrictions": 17204, + ",*": 17205, + "BUF": 17206, + "▁shadows": 17207, + "hci": 17208, + "▁Christians": 17209, + "▁fence": 17210, + "▁luxury": 17211, + "akh": 17212, + "coord": 17213, + "▁investigate": 17214, + "▁conventional": 17215, + "\"—": 17216, + "▁visits": 17217, + "isé": 17218, + "▁Sac": 17219, + "className": 17220, + "▁Psych": 17221, + "▁reflected": 17222, + "▁пло": 17223, + "▁Vice": 17224, + "ław": 17225, + "________________": 17226, + "▁Wolf": 17227, + "rente": 17228, + "▁Champion": 17229, + "▁simulation": 17230, + "esota": 17231, + "▁Soon": 17232, + "▁Cel": 17233, + "▁theories": 17234, + "▁STR": 17235, + "▁collective": 17236, + "▁coordinate": 17237, + "querySelector": 17238, + "emed": 17239, + "Break": 17240, + "▁gef": 17241, + "▁electricity": 17242, + "▁gathering": 17243, + "aters": 17244, + "exper": 17245, + "▁Roma": 17246, + "▁Cooper": 17247, + "SYMBOL": 17248, + "vd": 17249, + "iversary": 17250, + "aines": 17251, + "▁Grad": 17252, + "▁independence": 17253, + "woh": 17254, + "▁consequence": 17255, + "▁conversations": 17256, + "▁Rou": 17257, + "▁andere": 17258, + "▁Systems": 17259, + "гар": 17260, + "▁moist": 17261, + "flu": 17262, + "ція": 17263, + "ниш": 17264, + "▁rode": 17265, + "▁perd": 17266, + "▁szer": 17267, + "▁flood": 17268, + "▁intim": 17269, + "stderr": 17270, + "▁reflection": 17271, + "Scan": 17272, + "▁disaster": 17273, + "akespe": 17274, + "▁Invalid": 17275, + "▁humor": 17276, + "▁Friedrich": 17277, + "▁suggestions": 17278, + "uvud": 17279, + "Delay": 17280, + "brief": 17281, + "▁ис": 17282, + "glied": 17283, + "fas": 17284, + "▁Smart": 17285, + "▁medi": 17286, + "sdk": 17287, + "▁seus": 17288, + "▁Arizona": 17289, + "▁innocent": 17290, + "Warn": 17291, + "acious": 17292, + "▁Moscow": 17293, + "▁caps": 17294, + "Delegate": 17295, + "▁dramatic": 17296, + "books": 17297, + "▁shore": 17298, + "uki": 17299, + "▁Russell": 17300, + "▁correlation": 17301, + "Help": 17302, + "▁pubblic": 17303, + "zym": 17304, + "comb": 17305, + "EY": 17306, + "LENGTH": 17307, + "▁Mün": 17308, + "▁_.": 17309, + "▁ferm": 17310, + "▁Ian": 17311, + "▁Studio": 17312, + "▁affairs": 17313, + "los": 17314, + "Rules": 17315, + "running": 17316, + "▁Posted": 17317, + "Pixel": 17318, + "▁dancing": 17319, + "▁agreements": 17320, + "▁Pic": 17321, + "ancia": 17322, + "▁má": 17323, + "ationToken": 17324, + "descriptor": 17325, + "▁Carter": 17326, + "Release": 17327, + "************": 17328, + "▁outstanding": 17329, + "changes": 17330, + "ARRAY": 17331, + "▁Barbara": 17332, + "▁nurse": 17333, + "(\r": 17334, + "▁Douglas": 17335, + "▁nucle": 17336, + "ouri": 17337, + "▁Style": 17338, + "avo": 17339, + "▁painful": 17340, + "▁slic": 17341, + "▁seinem": 17342, + "SUPPORT": 17343, + "ogene": 17344, + "▁satell": 17345, + "tagon": 17346, + "▁collapse": 17347, + "velle": 17348, + "MON": 17349, + "aughters": 17350, + "▁threatened": 17351, + "▁Illegal": 17352, + "▁desperate": 17353, + "strict": 17354, + "rus": 17355, + "ститу": 17356, + "\\\":": 17357, + "▁conflic": 17358, + "download": 17359, + "atos": 17360, + "▁Position": 17361, + ".*;": 17362, + "▁theater": 17363, + "▁pleasant": 17364, + "▁Cette": 17365, + "▁Singapore": 17366, + "heet": 17367, + "▁pir": 17368, + "▁acquis": 17369, + "▁назва": 17370, + "теля": 17371, + "▁recru": 17372, + "жения": 17373, + "ёл": 17374, + "версите": 17375, + "▁respective": 17376, + "▁tunnel": 17377, + "▁Dean": 17378, + "Du": 17379, + "▁uncle": 17380, + "▁offensive": 17381, + "colo": 17382, + "▁Unlike": 17383, + "series": 17384, + "▁Arn": 17385, + "minute": 17386, + "▁descriptor": 17387, + "▁stones": 17388, + "ICATION": 17389, + "▁Pad": 17390, + "▁iPhone": 17391, + "ei": 17392, + "▁fantasy": 17393, + "▁Korean": 17394, + "\"}": 17395, + "▁orth": 17396, + "halten": 17397, + "deep": 17398, + "▁Kay": 17399, + "requency": 17400, + "▁duties": 17401, + "awt": 17402, + "▁nearest": 17403, + "▁disorder": 17404, + "стру": 17405, + "▁Chile": 17406, + "▁seq": 17407, + "▁transportation": 17408, + "OO": 17409, + "▁Dez": 17410, + "iju": 17411, + "▁Results": 17412, + "jed": 17413, + "ivel": 17414, + "HOST": 17415, + "▁€": 17416, + "▁Î": 17417, + "▁chin": 17418, + "▁matt": 17419, + "▁voted": 17420, + "▁gehör": 17421, + "▁▁▁▁▁▁▁▁▁▁▁": 17422, + "▁sue": 17423, + "▁legacy": 17424, + "вся": 17425, + "SOURCE": 17426, + "WORK": 17427, + "itis": 17428, + "▁$|": 17429, + "▁обо": 17430, + "▁nr": 17431, + "▁Tamb": 17432, + "▁snap": 17433, + "▁impressed": 17434, + "▁deposit": 17435, + "▁divid": 17436, + "Segment": 17437, + "▁кар": 17438, + "▁Gas": 17439, + "▁crimes": 17440, + "▁insult": 17441, + "▁Hum": 17442, + "▁bounded": 17443, + "▁kicked": 17444, + "▁Му": 17445, + "▁|\\": 17446, + "added": 17447, + "Produ": 17448, + "▁./": 17449, + "▁awkward": 17450, + "▁Кра": 17451, + "▁ї": 17452, + "▁CONTR": 17453, + "▁beim": 17454, + "▁placeholder": 17455, + "spi": 17456, + "▁Bei": 17457, + "▁Pf": 17458, + "ientes": 17459, + "disk": 17460, + "blk": 17461, + "neo": 17462, + "itarian": 17463, + "▁cogn": 17464, + "▁sout": 17465, + "▁trash": 17466, + "▁Rab": 17467, + "▁decline": 17468, + "tat": 17469, + "▁combine": 17470, + "▁Tot": 17471, + "▁drops": 17472, + "Times": 17473, + "cheduler": 17474, + "▁governments": 17475, + "Tex": 17476, + "▁Used": 17477, + "зан": 17478, + "▁pd": 17479, + "мет": 17480, + "▁&=&": 17481, + "▁Nag": 17482, + "▁дол": 17483, + "▁Always": 17484, + "rtc": 17485, + "ске": 17486, + "▁performances": 17487, + "rupted": 17488, + "▁два": 17489, + "▁managers": 17490, + "▁Pitt": 17491, + "▁mystery": 17492, + "▁settle": 17493, + "ulse": 17494, + "cross": 17495, + "question": 17496, + "asha": 17497, + "seed": 17498, + "urable": 17499, + "Final": 17500, + "++++": 17501, + "inputs": 17502, + "▁backup": 17503, + "▁Learning": 17504, + "▁*,": 17505, + "logo": 17506, + "▁seinen": 17507, + "▁vulnerable": 17508, + "directory": 17509, + "ië": 17510, + "▁friendship": 17511, + "tu": 17512, + "▁Vec": 17513, + "rifice": 17514, + "▁бра": 17515, + "▁involve": 17516, + "TON": 17517, + "▁corrid": 17518, + "separ": 17519, + "Destroy": 17520, + "▁jul": 17521, + "▁inequality": 17522, + "▁ain": 17523, + "hex": 17524, + "▁wider": 17525, + "тели": 17526, + "▁jack": 17527, + "▁quot": 17528, + "▁Glen": 17529, + "initely": 17530, + "ihood": 17531, + "▁waist": 17532, + "▁Manchester": 17533, + "regular": 17534, + "▁(&": 17535, + "▁masses": 17536, + "▁DEFAULT": 17537, + "▁chairs": 17538, + "▁Fast": 17539, + "▁citt": 17540, + "_{{\\": 17541, + "oa": 17542, + "▁$\\{": 17543, + "▁seeds": 17544, + "▁Ald": 17545, + "▁Batt": 17546, + "fab": 17547, + "▁democracy": 17548, + "DTO": 17549, + "▁Hij": 17550, + "PTR": 17551, + "Na": 17552, + "▁Harvard": 17553, + "sid": 17554, + "Pred": 17555, + "fers": 17556, + "▁spare": 17557, + "AMP": 17558, + "▁groupe": 17559, + "▁sender": 17560, + "▁Christopher": 17561, + "▁prisoners": 17562, + "▁Ker": 17563, + "▁Crist": 17564, + "▁ALL": 17565, + "rice": 17566, + "▁antes": 17567, + "natural": 17568, + "▁Susan": 17569, + "▁Juli": 17570, + "▁diab": 17571, + "ixon": 17572, + "icator": 17573, + "▁flexible": 17574, + "▁reserve": 17575, + "Contains": 17576, + "▁Hil": 17577, + "▁Isa": 17578, + "▁towns": 17579, + "GS": 17580, + "▁Trad": 17581, + "▁Lock": 17582, + "▁Grund": 17583, + "▁criticism": 17584, + "ню": 17585, + "▁că": 17586, + "▁politician": 17587, + "stable": 17588, + "Accept": 17589, + "Summary": 17590, + "▁também": 17591, + "}^{-": 17592, + "▁IM": 17593, + "idal": 17594, + "мор": 17595, + "Blue": 17596, + "GROUP": 17597, + "▁terminal": 17598, + "▁complexity": 17599, + "▁locally": 17600, + "DOWN": 17601, + "▁Near": 17602, + "Depth": 17603, + "▁pole": 17604, + "▁equality": 17605, + "Site": 17606, + "▁isinstance": 17607, + "Speed": 17608, + "ippi": 17609, + ",&": 17610, + "▁Enc": 17611, + "щен": 17612, + "▁mater": 17613, + "▁slaves": 17614, + "ACTION": 17615, + "usalem": 17616, + "▁haz": 17617, + "▁Beat": 17618, + "▁wrest": 17619, + "▁llam": 17620, + "Ins": 17621, + "мина": 17622, + "▁був": 17623, + "▁Frame": 17624, + "ushes": 17625, + "▁virtually": 17626, + "▁Perm": 17627, + "▁weights": 17628, + "▁llvm": 17629, + "▁cave": 17630, + "states": 17631, + "DMA": 17632, + "ellt": 17633, + "ifact": 17634, + "vendor": 17635, + "▁Emma": 17636, + "Locale": 17637, + "▁SET": 17638, + "▁geometry": 17639, + "Styles": 17640, + "▁Referee": 17641, + "▁weit": 17642, + "fica": 17643, + "▁ads": 17644, + "gray": 17645, + "▁Burg": 17646, + "iona": 17647, + "dagger": 17648, + "▁Januar": 17649, + "дей": 17650, + "isterschaft": 17651, + "ppo": 17652, + "oids": 17653, + "▁départ": 17654, + "Shader": 17655, + "▁constraint": 17656, + "Secret": 17657, + "▁Peters": 17658, + "▁eyeb": 17659, + "▁mesh": 17660, + "▁cookie": 17661, + "▁Pick": 17662, + "▁nick": 17663, + "bye": 17664, + "▁savings": 17665, + "Try": 17666, + "python": 17667, + "▁patri": 17668, + "▁multip": 17669, + "▁kinda": 17670, + "▁'_": 17671, + "▁Franz": 17672, + "▁cloth": 17673, + "зульта": 17674, + "▁fleet": 17675, + "▁humanity": 17676, + "resa": 17677, + "blob": 17678, + "▁TX": 17679, + "▁Buch": 17680, + "▁Lond": 17681, + "▁valley": 17682, + "▁murm": 17683, + "▁Trade": 17684, + "linewidth": 17685, + "▁especial": 17686, + "upper": 17687, + "▁hosp": 17688, + "▁tanto": 17689, + "▁oldest": 17690, + "▁Roose": 17691, + "▁hitting": 17692, + "dog": 17693, + "ovi": 17694, + "},\r": 17695, + "▁compatible": 17696, + "▁Website": 17697, + "poch": 17698, + "▁Bag": 17699, + "▁accomplish": 17700, + "Christ": 17701, + "asset": 17702, + "▁Until": 17703, + "▁geld": 17704, + "Listen": 17705, + "SB": 17706, + "Setup": 17707, + "icia": 17708, + "▁lum": 17709, + "▁janvier": 17710, + "PAGE": 17711, + "▁Nu": 17712, + "/\"": 17713, + "▁divorce": 17714, + "Execute": 17715, + "Depend": 17716, + "▁Scottish": 17717, + "▁Ts": 17718, + "ruppe": 17719, + "▁refuse": 17720, + "▁Oktober": 17721, + "ijk": 17722, + "▁Amy": 17723, + "▁dimin": 17724, + "▁gross": 17725, + "▁trat": 17726, + "isible": 17727, + "mixer": 17728, + "▁autres": 17729, + "▁neat": 17730, + "▁otros": 17731, + "Void": 17732, + "▁schol": 17733, + "▁Walker": 17734, + "▁tube": 17735, + "ologists": 17736, + "▁груп": 17737, + "▁haben": 17738, + "uber": 17739, + "ACTIVE": 17740, + "▁Attendance": 17741, + "▁оп": 17742, + "▁blade": 17743, + "oplus": 17744, + "▁Original": 17745, + "▁manufacturer": 17746, + "asz": 17747, + "âte": 17748, + "rer": 17749, + "▁Json": 17750, + "▁succeeded": 17751, + "uffle": 17752, + "▁backed": 17753, + "esian": 17754, + "tick": 17755, + "External": 17756, + "▁XIX": 17757, + "▁hearts": 17758, + "▁После": 17759, + "olu": 17760, + "▁лет": 17761, + "VICE": 17762, + "ário": 17763, + "▁fraud": 17764, + "edu": 17765, + "Primary": 17766, + "▁gaming": 17767, + "▁plt": 17768, + "igator": 17769, + "IES": 17770, + "Compiler": 17771, + "▁monument": 17772, + "agem": 17773, + "▁Rain": 17774, + "▁moins": 17775, + "oku": 17776, + "osex": 17777, + "▁Kansas": 17778, + "▁gepublice": 17779, + "▁Joy": 17780, + "Scene": 17781, + "▁kingdom": 17782, + "rices": 17783, + "▁juin": 17784, + "▁uncomfortable": 17785, + "▁Money": 17786, + "obb": 17787, + "expl": 17788, + "strcmp": 17789, + "▁dread": 17790, + "rition": 17791, + "▁Chi": 17792, + "▁demonstrated": 17793, + "▁vertices": 17794, + "чо": 17795, + "▁Culture": 17796, + "FX": 17797, + "Dictionary": 17798, + "▁Dru": 17799, + "trm": 17800, + "▁examine": 17801, + "▁therap": 17802, + "ième": 17803, + "мини": 17804, + "▁produces": 17805, + "▁photographs": 17806, + "▁threads": 17807, + "▁MI": 17808, + "▁extraordinary": 17809, + "ским": 17810, + "▁gepubliceerd": 17811, + "▁Poland": 17812, + "▁guaranteed": 17813, + "RG": 17814, + "osc": 17815, + "али": 17816, + "▁тех": 17817, + "errno": 17818, + "science": 17819, + "iffs": 17820, + "▁Tam": 17821, + "▁Beth": 17822, + "▁Travel": 17823, + "▁translate": 17824, + "ché": 17825, + "▁ling": 17826, + "▁belongs": 17827, + "▁electrical": 17828, + "ensk": 17829, + "▁Compet": 17830, + "cg": 17831, + "VC": 17832, + "topic": 17833, + "▁presum": 17834, + "вета": 17835, + "▁approximation": 17836, + "▁grim": 17837, + "▁Из": 17838, + "_{(": 17839, + "вин": 17840, + "ution": 17841, + "owych": 17842, + "åg": 17843, + "sterreich": 17844, + "▁characteristic": 17845, + "oming": 17846, + "▁/*!": 17847, + "▁prize": 17848, + "▁Minnesota": 17849, + "ted": 17850, + "цы": 17851, + "▁Om": 17852, + "▁indices": 17853, + "▁stem": 17854, + "regon": 17855, + "ниче": 17856, + "▁Salv": 17857, + "ése": 17858, + "▁aged": 17859, + "▁Past": 17860, + "▁internation": 17861, + "▁Vic": 17862, + "▁resume": 17863, + "akespeare": 17864, + "▁estado": 17865, + "▁abilities": 17866, + "▁brow": 17867, + "▁NFL": 17868, + "▁trends": 17869, + "▁Austin": 17870, + "▁LIMIT": 17871, + "▁Kor": 17872, + "▁folk": 17873, + "▁ward": 17874, + "▁nest": 17875, + "▁Junior": 17876, + "▁maintaining": 17877, + "Pub": 17878, + "OBJECT": 17879, + "▁bloody": 17880, + "▁sj": 17881, + "▁dtype": 17882, + "Pane": 17883, + "▁bacter": 17884, + "▁gradually": 17885, + "mr": 17886, + "Team": 17887, + "▁indicating": 17888, + "▁decrease": 17889, + "tek": 17890, + "▁Represent": 17891, + "▁developers": 17892, + "Guid": 17893, + "▁Diet": 17894, + "▁retr": 17895, + "Navigation": 17896, + "esi": 17897, + "▁lazy": 17898, + "Standard": 17899, + "Er": 17900, + "AW": 17901, + "▁États": 17902, + "▁assured": 17903, + "San": 17904, + "▁Andre": 17905, + "’,": 17906, + "fang": 17907, + "ération": 17908, + "▁industries": 17909, + "▁incon": 17910, + "Emit": 17911, + "▁где": 17912, + "▁retriev": 17913, + "eni": 17914, + "▁Turkey": 17915, + "izers": 17916, + "Angle": 17917, + "▁oc": 17918, + "▁palm": 17919, + "▁stan": 17920, + "льно": 17921, + "▁CSS": 17922, + "▁frances": 17923, + "▁grin": 17924, + "▁tiempo": 17925, + "▁Prix": 17926, + "]).": 17927, + "▁deput": 17928, + "▁Pin": 17929, + "▁sixt": 17930, + "▁predicted": 17931, + "azure": 17932, + "▁Motor": 17933, + "▁ihm": 17934, + "▁manus": 17935, + "apos": 17936, + "▁instruments": 17937, + "▁counts": 17938, + "▁aimed": 17939, + "profit": 17940, + "▁dok": 17941, + "обра": 17942, + "▁estud": 17943, + "iesz": 17944, + "▁piss": 17945, + "▁inaug": 17946, + "▁voters": 17947, + "▁packages": 17948, + "▁cute": 17949, + "▁fitness": 17950, + "▁leurs": 17951, + "▁sorted": 17952, + "phant": 17953, + "OPT": 17954, + "▁zip": 17955, + "season": 17956, + "emi": 17957, + "encoding": 17958, + "won": 17959, + "elect": 17960, + "▁tooth": 17961, + "▁upcoming": 17962, + "▁Graham": 17963, + "nut": 17964, + "▁Ark": 17965, + "ält": 17966, + "▁precious": 17967, + "agle": 17968, + "née": 17969, + "ница": 17970, + "aris": 17971, + "▁pile": 17972, + "cole": 17973, + "▁WITH": 17974, + "routing": 17975, + "▁***": 17976, + "Appearance": 17977, + "llvm": 17978, + "▁Oliver": 17979, + "▁PL": 17980, + "ifndef": 17981, + "etzt": 17982, + "skiego": 17983, + "▁pon": 17984, + "ARGET": 17985, + "kö": 17986, + "alled": 17987, + "▁=\\": 17988, + "sure": 17989, + "matches": 17990, + "▁temperatures": 17991, + "SEL": 17992, + "▁clone": 17993, + "▁eller": 17994, + "erna": 17995, + "▁поло": 17996, + "Management": 17997, + "company": 17998, + "▁lun": 17999, + "▁streaming": 18000, + "▁Ni": 18001, + "▁sí": 18002, + "Contact": 18003, + "▁Credit": 18004, + "▁Oak": 18005, + "▁представ": 18006, + "radius": 18007, + "cli": 18008, + "IENT": 18009, + "▁Lucy": 18010, + "▁calculation": 18011, + "▁pixel": 18012, + "▁mul": 18013, + "▁outcomes": 18014, + "▁centers": 18015, + "▁residence": 18016, + "Constraint": 18017, + "▁preserve": 18018, + "peon": 18019, + "uffix": 18020, + "▁Roberts": 18021, + "▁promot": 18022, + "?!": 18023, + "balance": 18024, + "▁courts": 18025, + "▁disg": 18026, + "PRINT": 18027, + "▁их": 18028, + "elfare": 18029, + "▁retreat": 18030, + "▁Ав": 18031, + "Cost": 18032, + "also": 18033, + "▁Für": 18034, + "▁März": 18035, + "DIO": 18036, + "▁bez": 18037, + "AUTH": 18038, + "Den": 18039, + "▁atom": 18040, + "▁roman": 18041, + "▁Pel": 18042, + "▁Roosevelt": 18043, + "▁Plant": 18044, + "Contents": 18045, + "▁Between": 18046, + "▁coupling": 18047, + "structure": 18048, + "▁Marshall": 18049, + "▁Career": 18050, + "▁railway": 18051, + "▁Bureau": 18052, + "▁possibilities": 18053, + "▁kor": 18054, + "){\r": 18055, + "mero": 18056, + "mov": 18057, + "англ": 18058, + "AIN": 18059, + "mund": 18060, + "lette": 18061, + "▁summar": 18062, + "▁describing": 18063, + "▁NAS": 18064, + "▁Emb": 18065, + "Instruction": 18066, + "liest": 18067, + "▁Sig": 18068, + "Bill": 18069, + "▁verd": 18070, + "plant": 18071, + "▁galaxies": 18072, + "\"])": 18073, + "▁PyObject": 18074, + "▁Gy": 18075, + "▁mě": 18076, + "▁organisation": 18077, + "Her": 18078, + "Sep": 18079, + "ocom": 18080, + "▁Same": 18081, + "▁bite": 18082, + "▁Seattle": 18083, + "зыва": 18084, + "Observer": 18085, + "’.": 18086, + "▁morph": 18087, + "urches": 18088, + "alph": 18089, + "reement": 18090, + "consin": 18091, + "^-": 18092, + "▁dann": 18093, + "translate": 18094, + "вих": 18095, + "React": 18096, + "▁cats": 18097, + "▁brew": 18098, + "▁ds": 18099, + "▁circles": 18100, + "▁drift": 18101, + "agma": 18102, + "▁Valent": 18103, + "PIN": 18104, + "ARM": 18105, + "▁surviv": 18106, + "alin": 18107, + "Pref": 18108, + "friendly": 18109, + "▁uncertainty": 18110, + "▁fd": 18111, + "▁engineer": 18112, + "Ben": 18113, + "icular": 18114, + "orest": 18115, + "▁horizontal": 18116, + "UTC": 18117, + "textrm": 18118, + "Live": 18119, + "Score": 18120, + "▁Germans": 18121, + "distance": 18122, + "uti": 18123, + "▁équ": 18124, + "▁numerical": 18125, + "▁reass": 18126, + "Activ": 18127, + "▁cod": 18128, + "bullet": 18129, + "ensing": 18130, + "▁Gem": 18131, + "▁navigation": 18132, + "addClass": 18133, + "▁simultaneously": 18134, + "вий": 18135, + "▁його": 18136, + "▁Hö": 18137, + "▁harsh": 18138, + "precated": 18139, + "ССР": 18140, + "▁Equip": 18141, + "adget": 18142, + "▁TYPE": 18143, + "▁mg": 18144, + "IGH": 18145, + "▁vin": 18146, + "▁findings": 18147, + "ivan": 18148, + "▁possession": 18149, + "▁того": 18150, + "▁parsed": 18151, + "riors": 18152, + "zeichnet": 18153, + "ников": 18154, + "Worker": 18155, + "▁enables": 18156, + "▁($\\": 18157, + "▁Copy": 18158, + "▁orientation": 18159, + "стре": 18160, + "▁Indians": 18161, + "▁Gary": 18162, + "▁Insurance": 18163, + "isan": 18164, + "Chat": 18165, + "▁comun": 18166, + "▁coron": 18167, + "ография": 18168, + "updated": 18169, + "▁Ин": 18170, + "These": 18171, + "SEC": 18172, + "▁boyfriend": 18173, + "Diagnostics": 18174, + "Hint": 18175, + "mul": 18176, + "▁inode": 18177, + "xA": 18178, + "eft": 18179, + "OPTION": 18180, + "unct": 18181, + "annon": 18182, + "ENS": 18183, + "strip": 18184, + "▁enthusi": 18185, + "▁Whit": 18186, + "▁Фи": 18187, + "aude": 18188, + "▁disagree": 18189, + "▁snapped": 18190, + "Phys": 18191, + "▁Syn": 18192, + "▁sour": 18193, + "▁Lux": 18194, + "ugar": 18195, + "tile": 18196, + "▁infection": 18197, + "▁Feb": 18198, + "▁Chem": 18199, + "dataset": 18200, + "chts": 18201, + "Dynamic": 18202, + "▁сред": 18203, + "▁queen": 18204, + "worker": 18205, + "swap": 18206, + "▁timestamp": 18207, + "▁Integr": 18208, + "▁interviews": 18209, + "such": 18210, + "▁laughter": 18211, + "prof": 18212, + "▁Bird": 18213, + "(|": 18214, + "ân": 18215, + "▁gra": 18216, + "&=": 18217, + "zens": 18218, + "getMessage": 18219, + "▁Ost": 18220, + "▁gab": 18221, + "▁mortgage": 18222, + "multicol": 18223, + "LEVEL": 18224, + "partition": 18225, + "seen": 18226, + "▁declar": 18227, + "AU": 18228, + "▁ox": 18229, + "▁ligger": 18230, + "▁Carm": 18231, + "geme": 18232, + "▁Vegas": 18233, + "▁Eug": 18234, + "orus": 18235, + "▁brick": 18236, + "▁así": 18237, + "▁Magazine": 18238, + "HasColumnType": 18239, + "VR": 18240, + "licher": 18241, + "▁Future": 18242, + "▁Jug": 18243, + "attan": 18244, + "constructor": 18245, + "VP": 18246, + "▁тур": 18247, + "чина": 18248, + "Comparator": 18249, + "▁authentic": 18250, + "▁monster": 18251, + "▁transformed": 18252, + "▁firms": 18253, + "FW": 18254, + "▁catalog": 18255, + "boards": 18256, + "▁diseases": 18257, + "▁Benjamin": 18258, + "▁horizon": 18259, + "▁Available": 18260, + "Mvc": 18261, + "Stud": 18262, + "▁lord": 18263, + "general": 18264, + "пар": 18265, + "▁cabinet": 18266, + "▁Basic": 18267, + "TestCase": 18268, + "ansk": 18269, + "▁Snow": 18270, + "ierten": 18271, + "▁vocal": 18272, + "Padding": 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18325, + "чение": 18326, + "▁Category": 18327, + "▁sq": 18328, + "▁Фе": 18329, + "VA": 18330, + "Diff": 18331, + "Tri": 18332, + "issement": 18333, + "▁actress": 18334, + "▁Пе": 18335, + "▁jej": 18336, + "▁twisted": 18337, + "▁Nicol": 18338, + "▁junior": 18339, + "Sound": 18340, + "▁Brasil": 18341, + "▁juice": 18342, + "▁>>>": 18343, + "▁Alb": 18344, + "▁softly": 18345, + "▁McK": 18346, + "▁Gren": 18347, + "▁italiano": 18348, + "▁creatures": 18349, + "▁residential": 18350, + "▁Instagram": 18351, + "ucks": 18352, + "▁killer": 18353, + "▁Johnny": 18354, + "▁enterprise": 18355, + "Dto": 18356, + "chestra": 18357, + "▁Tel": 18358, + "▁Activ": 18359, + "factor": 18360, + "oust": 18361, + "▁vacuum": 18362, + "рал": 18363, + "')->": 18364, + "▁Left": 18365, + "▁defect": 18366, + "▁ninete": 18367, + "fare": 18368, + "▁regret": 18369, + "▁shar": 18370, + "ctrine": 18371, + "mesh": 18372, + "city": 18373, + "icit": 18374, + "▁Fem": 18375, + "limited": 18376, + "oka": 18377, + "!\\!\\": 18378, + "Donald": 18379, + "зно": 18380, + "▁provision": 18381, + "▁discussions": 18382, + "Drag": 18383, + "▁Incl": 18384, + "Exit": 18385, + "▁Abd": 18386, + "story": 18387, + "ieve": 18388, + "▁był": 18389, + "olving": 18390, + "wohner": 18391, + "▁guidelines": 18392, + "▁straw": 18393, + "üss": 18394, + "▁було": 18395, + "▁burden": 18396, + "▁spatial": 18397, + "▁stretched": 18398, + "▁Inf": 18399, + "▁typedef": 18400, + "▁robot": 18401, + "▁Doc": 18402, + "pliers": 18403, + "wal": 18404, + "camp": 18405, + "▁diffé": 18406, + "▁McG": 18407, + "▁tel": 18408, + "arette": 18409, + "▁subsequently": 18410, + "▁honey": 18411, + "FUNC": 18412, + "▁establishment": 18413, + "tesy": 18414, + "▁który": 18415, + "▁сель": 18416, + "▁FO": 18417, + "▁Islands": 18418, + "▁mp": 18419, + "Scalar": 18420, + "▁Yan": 18421, + "cken": 18422, + "▁variation": 18423, + "ią": 18424, + "optim": 18425, + "azor": 18426, + "tuple": 18427, + "▁gravity": 18428, + "▁conclude": 18429, + "▁collections": 18430, + "ész": 18431, + "▁Liver": 18432, + "▁ethnic": 18433, + "compile": 18434, + "▁parl": 18435, + "Surface": 18436, + "{'": 18437, + "▁paragraph": 18438, + "posite": 18439, + "ítulo": 18440, + "oba": 18441, + "binary": 18442, + "rob": 18443, + "▁Pedro": 18444, + "▁fis": 18445, + "▁Grande": 18446, + "odox": 18447, + "▁posting": 18448, + "": 26345, + "olent": 26346, + "▁этого": 26347, + "▁Generic": 26348, + "▁*/,": 26349, + "▁combinations": 26350, + "▁rejo": 26351, + "спубли": 26352, + "capacity": 26353, + "▁traces": 26354, + "▁opacity": 26355, + "▁Official": 26356, + "icion": 26357, + "▁emotionally": 26358, + "▁Joel": 26359, + "ському": 26360, + "▁legendary": 26361, + "▁pam": 26362, + "▁También": 26363, + ".<": 26364, + "iba": 26365, + "midt": 26366, + "бом": 26367, + "▁ensuite": 26368, + "Authorization": 26369, + "Pag": 26370, + "▁helmet": 26371, + "▁territo": 26372, + "secondary": 26373, + "▁segunda": 26374, + "▁Wire": 26375, + "recated": 26376, + "▁invoked": 26377, + "▁ValueError": 26378, + "▁фо": 26379, + "ALIGN": 26380, + "CURRENT": 26381, + "\\+\\_\\": 26382, + "▁compilation": 26383, + "ær": 26384, + "▁Palmar": 26385, + "▁influences": 26386, + "/:": 26387, + "Mix": 26388, + "NOP": 26389, + "econom": 26390, + "▁tucked": 26391, + "▁});\r": 26392, + "ANK": 26393, + "reject": 26394, + "▁pension": 26395, + "▁generates": 26396, + "чё": 26397, + "▁incap": 26398, + "▁clicked": 26399, + "▁fus": 26400, + "ourses": 26401, + "▁Easter": 26402, + "%;": 26403, + "zin": 26404, + "▁obligations": 26405, + "▁Tips": 26406, + "};\r": 26407, + ".\"_": 26408, + "▁BSD": 26409, + "ática": 26410, + "▁expose": 26411, + "Pars": 26412, + "▁Amanda": 26413, + "куп": 26414, + "▁guessed": 26415, + "dsi": 26416, + "▁Leip": 26417, + "Broad": 26418, + "▁Hughes": 26419, + "ié": 26420, + "▁Wahl": 26421, + "▁formerly": 26422, + "Relative": 26423, + "▁Yu": 26424, + "▁Mountains": 26425, + "▁Enum": 26426, + "▁strang": 26427, + "_-": 26428, + "recht": 26429, + "viv": 26430, + "pause": 26431, + "▁Londres": 26432, + "▁elbow": 26433, + "▁Hawaii": 26434, + "▁Casino": 26435, + "Threshold": 26436, + "Units": 26437, + "Include": 26438, + "ито": 26439, + "asury": 26440, + "▁steht": 26441, + "▁damned": 26442, + "▁packets": 26443, + "▁Werk": 26444, + "▁elevator": 26445, + "iedad": 26446, + "govern": 26447, + "▁CONTRACT": 26448, + "mals": 26449, + "▁remem": 26450, + "▁entonces": 26451, + "▁vas": 26452, + "▁sympathy": 26453, + "▁befindet": 26454, + "incing": 26455, + "DataSet": 26456, + "▁additionally": 26457, + "▁musician": 26458, + "шего": 26459, + "▁listop": 26460, + ">\")": 26461, + "Printf": 26462, + "▁Felix": 26463, + "▁carved": 26464, + "▁nicely": 26465, + "гом": 26466, + "chap": 26467, + "▁Nieder": 26468, + "▁Lav": 26469, + "▁modifications": 26470, + "moment": 26471, + "▁balcon": 26472, + "▁dependency": 26473, + "CKET": 26474, + "▁vanished": 26475, + "▁fighters": 26476, + "▁zunächst": 26477, + "ioctl": 26478, + "▁defens": 26479, + "▁Nem": 26480, + "Utility": 26481, + "▁curv": 26482, + "▁DAMAGES": 26483, + "▁Rogers": 26484, + "▁gratitude": 26485, + "▁Denmark": 26486, + "рая": 26487, + "grpc": 26488, + "▁juni": 26489, + "▁октября": 26490, + "▁immense": 26491, + "▁prevented": 26492, + "▁foam": 26493, + "▁Extra": 26494, + "aimed": 26495, + "▁Criteria": 26496, + "▁Simply": 26497, + "boxes": 26498, + "▁Legend": 26499, + "▁Players": 26500, + "▁Mercedes": 26501, + "▁Branch": 26502, + "TERN": 26503, + "omena": 26504, + "▁incorporate": 26505, + "conde": 26506, + "▁Estado": 26507, + "▁wasted": 26508, + "▁complaining": 26509, + "▁warriors": 26510, + "oter": 26511, + "▁этом": 26512, + "▁conten": 26513, + "▁machinery": 26514, + "▁technological": 26515, + "▁TD": 26516, + "▁gras": 26517, + "▁minimize": 26518, + "▁Door": 26519, + "▁bzw": 26520, + "▁prac": 26521, + "TREE": 26522, + "▁Wing": 26523, + "▁Transaction": 26524, + "▁MVT": 26525, + "▁Klein": 26526, + "commons": 26527, + "▁}{": 26528, + "▁Heritage": 26529, + "▁fade": 26530, + "рок": 26531, + "setValue": 26532, + "▁Wallace": 26533, + "MX": 26534, + "▁ACT": 26535, + "▁footage": 26536, + "▁entstand": 26537, + "arga": 26538, + "▁nails": 26539, + "▁capitalism": 26540, + "▁Garc": 26541, + "▁suspension": 26542, + "ilis": 26543, + "▁Mov": 26544, + "uffled": 26545, + "Arc": 26546, + "▁Beautiful": 26547, + "WAY": 26548, + "Parallel": 26549, + "XXXX": 26550, + "diag": 26551, + "▁DT": 26552, + "mq": 26553, + "TextView": 26554, + "MLE": 26555, + "ennen": 26556, + "▁infected": 26557, + "▁therapist": 26558, + "INGS": 26559, + "▁cidade": 26560, + "ън": 26561, + "▁pdf": 26562, + "▁bump": 26563, + "CTX": 26564, + "▁INCLUDING": 26565, + "▁Gef": 26566, + "ENTIAL": 26567, + "▁handy": 26568, + "▁temporal": 26569, + "AtA": 26570, + "ISH": 26571, + "▁Pattern": 26572, + "▁lan": 26573, + "ependant": 26574, + "▁shining": 26575, + "idy": 26576, + "▁NT": 26577, + "▁Fran": 26578, + "▁nurses": 26579, + "▁betray": 26580, + "▁sensible": 26581, + "▁апреля": 26582, + "▁'[": 26583, + "▁thirteen": 26584, + ")}_{": 26585, + "▁Noah": 26586, + "INSERT": 26587, + "istically": 26588, + "▁Appendix": 26589, + "▁recher": 26590, + "Receiver": 26591, + "▁dernier": 26592, + "лла": 26593, + "лиза": 26594, + "▁Partido": 26595, + "▁maximal": 26596, + "snap": 26597, + "▁часть": 26598, + "STOP": 26599, + "▁ultra": 26600, + "▁développ": 26601, + "▁tegen": 26602, + "▁Чи": 26603, + "LIB": 26604, + "▁baseline": 26605, + "reload": 26606, + "▁Arbitro": 26607, + "▁kall": 26608, + "capture": 26609, + "Arm": 26610, + "quin": 26611, + "impse": 26612, + "zas": 26613, + "▁Cand": 26614, + "▁brains": 26615, + "▁hostile": 26616, + "▁marble": 26617, + "oons": 26618, + "▁Loss": 26619, + "MetaData": 26620, + "▁República": 26621, + "▁andra": 26622, + "oden": 26623, + "▁documented": 26624, + "▁Moses": 26625, + "odd": 26626, + "▁wax": 26627, + "usch": 26628, + "▁diagnosed": 26629, + "inkle": 26630, + "▁Xbox": 26631, + "▁seventy": 26632, + "cias": 26633, + "▁noviembre": 26634, + "Compute": 26635, + "});\r": 26636, + "▁Philippe": 26637, + "▁För": 26638, + "Leave": 26639, + "▁sage": 26640, + "▁unpre": 26641, + "▁Fortunately": 26642, + "▁apost": 26643, + "entities": 26644, + "▁ellos": 26645, + "authorized": 26646, + "GBT": 26647, + "▁insist": 26648, + "▁inspire": 26649, + "Mass": 26650, + "▁rôle": 26651, + "fee": 26652, + "ipart": 26653, + "цер": 26654, + "unate": 26655, + "▁CNN": 26656, + ":}": 26657, + "▁unhappy": 26658, + "▁imported": 26659, + "HIGH": 26660, + "rings": 26661, + "▁Instance": 26662, + "Bay": 26663, + "agles": 26664, + "mee": 26665, + "bery": 26666, + "▁Stories": 26667, + "▁Chase": 26668, + "▁carriage": 26669, + "▁misunder": 26670, + "▁imagin": 26671, + "pw": 26672, + "▁Meter": 26673, + "▁crowds": 26674, + "▁Fame": 26675, + "skill": 26676, + "▁comed": 26677, + "▁ranch": 26678, + "▁lacking": 26679, + "▁submar": 26680, + "iante": 26681, + "▁lanz": 26682, + "▁служ": 26683, + "-----------": 26684, + "▁obten": 26685, + "▁downstairs": 26686, + "YN": 26687, + "rotation": 26688, + "▁Jesse": 26689, + "$(\"#": 26690, + "▁puls": 26691, + "irling": 26692, + "▁Schaus": 26693, + "▁deployed": 26694, + "▁{}\",": 26695, + "▁Marvel": 26696, + "ENUM": 26697, + "▁Mathemat": 26698, + "▁nn": 26699, + "compet": 26700, + "ków": 26701, + "bil": 26702, + "Which": 26703, + "isine": 26704, + "▁rude": 26705, + "▁niveau": 26706, + "▁área": 26707, + "▁près": 26708, + "atis": 26709, + "▁[...]": 26710, + "fur": 26711, + "omm": 26712, + "packed": 26713, + "мене": 26714, + "scriptstyle": 26715, + "▁Ath": 26716, + "▁desp": 26717, + "eltemperaturen": 26718, + "▁talents": 26719, + "ocy": 26720, + "▁raises": 26721, + "LIMIT": 26722, + "▁editorial": 26723, + "▁Animal": 26724, + "drive": 26725, + "▁работа": 26726, + "bss": 26727, + "▁Sev": 26728, + "epoch": 26729, + "▁RC": 26730, + "UNUSED": 26731, + "▁mandatory": 26732, + "(?:": 26733, + "▁Bin": 26734, + "▁synthetic": 26735, + "▁gown": 26736, + "▁Dob": 26737, + "kap": 26738, + "▁harmon": 26739, + "▁liberty": 26740, + "▁Rice": 26741, + "▁prayers": 26742, + "▁mise": 26743, + "▁confusing": 26744, + "▁leap": 26745, + "▁arrives": 26746, + "kamp": 26747, + "▁thats": 26748, + "ACC": 26749, + "▁Parameters": 26750, + "▁одно": 26751, + "▁Bio": 26752, + "density": 26753, + "▁glimpse": 26754, + "FORE": 26755, + "▁Listen": 26756, + "Prev": 26757, + "}\\,\\": 26758, + "куль": 26759, + "▁SEC": 26760, + "▁explored": 26761, + "▁meantime": 26762, + "AIL": 26763, + "▁WP": 26764, + "▁raison": 26765, + "▁existe": 26766, + "▁lesser": 26767, + "▁Validate": 26768, + "▁caution": 26769, + "usta": 26770, + "heading": 26771, + "EFF": 26772, + ".'\"": 26773, + "▁Gilbert": 26774, + "▁limitation": 26775, + "▁retour": 26776, + "▁Commonwealth": 26777, + "▁gewann": 26778, + "▁miserable": 26779, + "▁networking": 26780, + "▁ottobre": 26781, + "▁Dise": 26782, + "edges": 26783, + "▁sede": 26784, + "вича": 26785, + "uniform": 26786, + "▁деятель": 26787, + "iros": 26788, + "▁desen": 26789, + "▁parc": 26790, + "▁Rico": 26791, + "Ns": 26792, + "guid": 26793, + "orio": 26794, + "avelength": 26795, + "▁Gle": 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27948, + "lbl": 27949, + "▁varies": 27950, + "▁fluctuations": 27951, + "▁долж": 27952, + "▁особи": 27953, + "▁warehouse": 27954, + "However": 27955, + "▁corrections": 27956, + "dhd": 27957, + "▁fals": 27958, + "▁controversy": 27959, + "▁curse": 27960, + "▁télé": 27961, + "řed": 27962, + "▁AU": 27963, + "▁тор": 27964, + "▁crít": 27965, + "idan": 27966, + "iliary": 27967, + "▁Panel": 27968, + "cule": 27969, + "▁Poor": 27970, + "▁BA": 27971, + "▁ignorant": 27972, + "èmes": 27973, + "▁aesthetic": 27974, + "Linked": 27975, + "getInt": 27976, + "Unicode": 27977, + "[@": 27978, + "▁Zent": 27979, + "Manifest": 27980, + "▁vars": 27981, + "PB": 27982, + "▁ву": 27983, + "▁Describe": 27984, + "▁Anything": 27985, + "oirs": 27986, + "▁socks": 27987, + "▁imped": 27988, + "▁neue": 27989, + "▁dispers": 27990, + "Collect": 27991, + "filer": 27992, + "▁Frau": 27993, + "▁Hockey": 27994, + "▁teens": 27995, + "▁Roberto": 27996, + "lauf": 27997, + "вать": 27998, + "▁ско": 27999, + "isArray": 28000, + 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28052, + "▁Buc": 28053, + "▁PD": 28054, + "▁Statement": 28055, + "▁PI": 28056, + "▁Jackie": 28057, + "▁ordin": 28058, + "▁kör": 28059, + "enze": 28060, + "▁utilized": 28061, + "áct": 28062, + "azed": 28063, + "▁severely": 28064, + "▁även": 28065, + "▁libro": 28066, + "▁Eu": 28067, + "äst": 28068, + "PART": 28069, + "▁Butler": 28070, + "▁puzzle": 28071, + "Fall": 28072, + "Country": 28073, + "pfn": 28074, + "▁україн": 28075, + "▁Orchestra": 28076, + "▁alto": 28077, + "▁ancora": 28078, + "▁decomposition": 28079, + "▁م": 28080, + "▁appetite": 28081, + "adu": 28082, + "▁THAT": 28083, + "▁comenz": 28084, + "mina": 28085, + "▁initiated": 28086, + "▁Tat": 28087, + "▁sometime": 28088, + "rek": 28089, + "bread": 28090, + "▁Statistics": 28091, + "▁Cob": 28092, + "Follow": 28093, + "▁geometric": 28094, + "шла": 28095, + "▁proceedings": 28096, + "Dlg": 28097, + "seven": 28098, + "▁[-": 28099, + "▁Buffalo": 28100, + "▁blacks": 28101, + "▁sov": 28102, + "▁custody": 28103, + "▁ras": 28104, + 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"add_prefix_space": null, + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "1": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "2": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [], + "bos_token": "", + "clean_up_tokenization_spaces": false, + "eos_token": "", + "extra_special_tokens": {}, + "legacy": true, + "model_max_length": 1000000000000000019884624838656, + "pad_token": null, + "sp_model_kwargs": {}, + "spaces_between_special_tokens": false, + "tokenizer_class": "LlamaTokenizerFast", + "unk_token": "", + "use_default_system_prompt": false +} diff --git a/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/train.sh b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/train.sh new file mode 100644 index 0000000000000000000000000000000000000000..28513f9c43d27d32a7550d0a8621ce0e32794aaa --- /dev/null +++ b/gdn_6_1_340M.json-ctx8192-steps95366-lr3e-4-decay_typelinear-decay_ratio1-bs16-nn1/train.sh @@ -0,0 +1,121 @@ +#!/usr/bin/bash + +params="" +if [ $# -ne 0 ]; then + params="$*" +fi + +# use envs as local params for convenience +# e.g. +# NNODE=1 NGPU=8 LOG_RANK=0 ./train.sh +NNODE=${NNODE:-"1"} +NGPU=${NGPU:-"8"} +LOG_RANK=${LOG_RANK:-0} + +if [[ -z "${MASTER_ADDR}" ]]; then + export MASTER_ADDR="localhost" +fi +if [[ -z "${MASTER_PORT}" ]]; then + export MASTER_PORT="0" +fi + +: ' +Usage: + +bash train.sh -h + +Training a 340M model: + +NNODE=1 NGPU=8 LOG_RANK=0 bash train.sh \ + --job.config_file flame/models/fla.toml \ + --job.dump_folder exp/transformer-340M-10B/batch32.seqlen2048.warmup1024.update1.steps20480.lr3e-4 \ + --model.config configs/transformer_340M.json \ + --model.tokenizer_path fla-hub/transformer-1.3B-100B \ + --optimizer.name AdamW \ + --optimizer.eps 1e-15 \ + --optimizer.lr 3e-4 \ + --lr_scheduler.warmup_steps 1024 \ + --lr_scheduler.lr_min 0.1 \ + --lr_scheduler.decay_type cosine \ + --training.batch_size 32 \ + --training.seq_len 2048 \ + --training.gradient_accumulation_steps 1 \ + --training.steps 20480 \ + --training.max_norm 1.0 \ + --training.skip_nan_inf \ + --training.dataset HuggingFaceFW/fineweb-edu \ + --training.dataset_name default \ + --training.dataset_split train \ + --training.streaming \ + --training.num_workers 32 \ + --training.prefetch_factor 2 \ + --training.seed 42 \ + --training.compile \ + --training.tensor_parallel_degree 1 \ + --training.disable_loss_parallel \ + --checkpoint.interval 2048 \ + --checkpoint.load_step -1 \ + --metrics.log_freq 1 +' + +echo "Launching training..." + +set -x +path=$(grep -oP '(?<=--job.dump_folder )[^ ]+' <<< "$params") +steps=$(grep -oP '(?<=--training.steps )[^ ]+' <<< "$params") +config=$(grep -oP '(?<=--model.config )[^ ]+' <<< "$params") +tokenizer=$(grep -oP '(?<=--model.tokenizer_path )[^ ]+' <<< "$params") +model=$( + python -c "import fla, sys; from transformers import AutoConfig; print(AutoConfig.from_pretrained(sys.argv[1]).to_json_string())" "$config" | jq -r '.model_type' +) + +mkdir -p $path +cp *.sh $path +cp -r configs $path +cp -r flame $path +cp -r 3rdparty/flash-linear-attention/fla $path +cp -r 3rdparty/torchtitan/torchtitan $path + +# for offline systems +# export TRANSFORMERS_OFFLINE=1 +# export HF_DATASETS_OFFLINE=1 +# export HF_HUB_OFFLINE=1 +if [ "$date" == "" ]; then + date=$(date +%Y%m%d%H%M) +fi +RUN_NAME="$model-$(basename $path)" +RUN_ID="$RUN_NAME-$date" + +export WANDB_RESUME=allow +if [[ -z "${WANDB_PROJECT}" ]]; then + export WANDB_PROJECT="fla" +fi +if [[ -z "${WANDB_NAME}" ]]; then + export WANDB_NAME="$RUN_NAME" +fi +if [[ -z "${WANDB_RUN_ID}" ]]; then + export WANDB_RUN_ID="$RUN_ID" +fi + +PYTORCH_CUDA_ALLOC_CONF="expandable_segments:True" \ +torchrun --nnodes=${NNODE} \ + --nproc_per_node=${NGPU} \ + --rdzv_backend c10d \ + --rdzv_endpoint "${MASTER_ADDR}:${MASTER_PORT}" \ + --local-ranks-filter ${LOG_RANK} \ + --role rank \ + --tee 3 \ + --log-dir $path/logs \ + -m flame.train \ + $params + +echo "TRAINING DONE!" +echo "Converting the DCP checkpoints to HF format..." + +python -m flame.utils.convert_dcp_to_hf \ + --path $path \ + --step $steps \ + --config $config \ + --tokenizer $tokenizer + +echo "RUNNING DONE!"