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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 55 new columns ({'time_stats.mlp_up_proj.std', 'use_gated_mlp', 'time_stats.mlp_act.std', 'time_stats.post_attention_layernorm.max', 'time_stats.mlp_act.max', 'num_tokens', 'time_stats.attn_rope.median', 'time_stats.post_attention_layernorm.min', 'time_stats.mlp_down_proj.mean', 'time_stats.input_layernorm.max', 'time_stats.add.median', 'time_stats.mlp_down_proj.std', 'time_stats.post_attention_layernorm.std', 'time_stats.post_attention_layernorm.median', 'n_expanded_embd', 'time_stats.add.mean', 'time_stats.mlp_act.median', 'time_stats.add.min', 'time_stats.emb.max', 'time_stats.mlp_act.min', 'time_stats.add.max', 'n_head', 'time_stats.attn_rope.mean', 'time_stats.attn_post_proj.max', 'time_stats.attn_post_proj.std', 'time_stats.mlp_down_proj.max', 'time_stats.attn_pre_proj.std', 'time_stats.mlp_up_proj.min', 'time_stats.mlp_up_proj.median', 'time_stats.mlp_down_proj.median', 'time_stats.mlp_down_proj.min', 'time_stats.emb.median', 'time_stats.attn_pre_proj.median', 'time_stats.attn_rope.std', 'time_stats.post_attention_layernorm.mean', 'time_stats.add.std', 'time_stats.attn_pre_proj.mean', 'time_stats.input_layernorm.min', 'time_stats.input_layernorm.mean', 'time_stats.emb.min', 'time_stats.attn_pre_proj.min', 'time_stats.attn_post_proj.median', 'time_stats.attn_post_proj.mean', 'vocab_size', 'time_stats.input_layernorm.std', 'time_stats.attn_post_proj.min', 'time_stats.attn_rope.min', 'time_stats.emb.std', 'time_stats.mlp_up_proj.max', 'time_stats.emb.mean', 'time_stats.input_layernorm.median', 'time_stats.mlp_up_proj.mean', 'time_stats.mlp_act.mean', 'time_stats.attn_pre_proj.max', 'time_stats.attn_rope.max'}) and 28 missing columns ({'max_model_len', 'time_stats.attn_decode.max', 'time_stats.attn_output_reshape.std', 'time_stats.attn_decode.median', 'time_stats.attn_prefill.mean', 'time_stats.attn_prefill.std', 'time_stats.attn_decode.min', 'time_stats.attn_decode.mean', 'block_size', 'n_q_head', 'time_stats.attn_prefill.min', 'time_stats.attn_prefill.max', 'attention_backend', 'kv_cache_size', 'time_stats.attn_output_reshape.max', 'time_stats.attn_input_reshape.min', 'time_stats.attn_input_reshape.median', 'is_prefill', 'time_stats.attn_output_reshape.mean', 'time_stats.attn_output_reshape.min', 'time_stats.attn_prefill.median', 'time_stats.attn_input_reshape.mean', 'batch_size', 'time_stats.attn_output_reshape.median', 'time_stats.attn_input_reshape.std', 'time_stats.attn_decode.std', 'prefill_chunk_size', 'time_stats.attn_input_reshape.max'}).

This happened while the csv dataset builder was generating data using

hf://datasets/project-vajra/dev-staging-internlm-internlm-20b-a40/mlp.csv (at revision 6c5c4d2eaff539e8ec8663d21105d5e9363943ec)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              time_stats.emb.min: double
              time_stats.emb.max: double
              time_stats.emb.mean: double
              time_stats.emb.median: double
              time_stats.emb.std: double
              time_stats.input_layernorm.min: double
              time_stats.input_layernorm.max: double
              time_stats.input_layernorm.mean: double
              time_stats.input_layernorm.median: double
              time_stats.input_layernorm.std: double
              time_stats.attn_pre_proj.min: double
              time_stats.attn_pre_proj.max: double
              time_stats.attn_pre_proj.mean: double
              time_stats.attn_pre_proj.median: double
              time_stats.attn_pre_proj.std: double
              time_stats.attn_rope.min: double
              time_stats.attn_rope.max: double
              time_stats.attn_rope.mean: double
              time_stats.attn_rope.median: double
              time_stats.attn_rope.std: double
              time_stats.attn_post_proj.min: double
              time_stats.attn_post_proj.max: double
              time_stats.attn_post_proj.mean: double
              time_stats.attn_post_proj.median: double
              time_stats.attn_post_proj.std: double
              time_stats.post_attention_layernorm.min: double
              time_stats.post_attention_layernorm.max: double
              time_stats.post_attention_layernorm.mean: double
              time_stats.post_attention_layernorm.median: double
              time_stats.post_attention_layernorm.std: double
              time_stats.mlp_up_proj.min: double
              time_stats.mlp_up_proj.max: double
              time_stats.mlp_up_proj.mean: double
              time_stats.mlp_up_proj.median: double
              time_stats.mlp_up_proj.std: double
              time_stats.mlp_act.min: double
              time_stats.mlp_act.max: double
              time_stats.mlp_act.mean: double
              time_stats.mlp_act.median: double
              time_stats.mlp_act.std: double
              time_stats.mlp_down_proj.min: double
              time_stats.mlp_down_proj.max: double
              time_stats.mlp_down_proj.mean: double
              time_stats.mlp_down_proj.median: double
              time_stats.mlp_down_proj.std: double
              time_stats.add.min: double
              time_stats.add.max: double
              time_stats.add.mean: double
              time_stats.add.median: double
              time_stats.add.std: double
              n_head: int64
              n_kv_head: int64
              n_embd: int64
              n_expanded_embd: int64
              vocab_size: int64
              use_gated_mlp: bool
              num_tokens: int64
              num_tensor_parallel_workers: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 8978
              to
              {'time_stats.attn_input_reshape.min': Value('float64'), 'time_stats.attn_input_reshape.max': Value('float64'), 'time_stats.attn_input_reshape.mean': Value('float64'), 'time_stats.attn_input_reshape.median': Value('float64'), 'time_stats.attn_input_reshape.std': Value('float64'), 'time_stats.attn_decode.min': Value('float64'), 'time_stats.attn_decode.max': Value('float64'), 'time_stats.attn_decode.mean': Value('float64'), 'time_stats.attn_decode.median': Value('float64'), 'time_stats.attn_decode.std': Value('float64'), 'time_stats.attn_output_reshape.min': Value('float64'), 'time_stats.attn_output_reshape.max': Value('float64'), 'time_stats.attn_output_reshape.mean': Value('float64'), 'time_stats.attn_output_reshape.median': Value('float64'), 'time_stats.attn_output_reshape.std': Value('float64'), 'time_stats.attn_prefill.min': Value('float64'), 'time_stats.attn_prefill.max': Value('float64'), 'time_stats.attn_prefill.mean': Value('float64'), 'time_stats.attn_prefill.median': Value('float64'), 'time_stats.attn_prefill.std': Value('float64'), 'n_embd': Value('int64'), 'n_q_head': Value('int64'), 'n_kv_head': Value('int64'), 'block_size': Value('int64'), 'num_tensor_parallel_workers': Value('int64'), 'max_model_len': Value('int64'), 'batch_size': Value('int64'), 'prefill_chunk_size': Value('int64'), 'kv_cache_size': Value('int64'), 'is_prefill': Value('bool'), 'attention_backend': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1455, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1054, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 55 new columns ({'time_stats.mlp_up_proj.std', 'use_gated_mlp', 'time_stats.mlp_act.std', 'time_stats.post_attention_layernorm.max', 'time_stats.mlp_act.max', 'num_tokens', 'time_stats.attn_rope.median', 'time_stats.post_attention_layernorm.min', 'time_stats.mlp_down_proj.mean', 'time_stats.input_layernorm.max', 'time_stats.add.median', 'time_stats.mlp_down_proj.std', 'time_stats.post_attention_layernorm.std', 'time_stats.post_attention_layernorm.median', 'n_expanded_embd', 'time_stats.add.mean', 'time_stats.mlp_act.median', 'time_stats.add.min', 'time_stats.emb.max', 'time_stats.mlp_act.min', 'time_stats.add.max', 'n_head', 'time_stats.attn_rope.mean', 'time_stats.attn_post_proj.max', 'time_stats.attn_post_proj.std', 'time_stats.mlp_down_proj.max', 'time_stats.attn_pre_proj.std', 'time_stats.mlp_up_proj.min', 'time_stats.mlp_up_proj.median', 'time_stats.mlp_down_proj.median', 'time_stats.mlp_down_proj.min', 'time_stats.emb.median', 'time_stats.attn_pre_proj.median', 'time_stats.attn_rope.std', 'time_stats.post_attention_layernorm.mean', 'time_stats.add.std', 'time_stats.attn_pre_proj.mean', 'time_stats.input_layernorm.min', 'time_stats.input_layernorm.mean', 'time_stats.emb.min', 'time_stats.attn_pre_proj.min', 'time_stats.attn_post_proj.median', 'time_stats.attn_post_proj.mean', 'vocab_size', 'time_stats.input_layernorm.std', 'time_stats.attn_post_proj.min', 'time_stats.attn_rope.min', 'time_stats.emb.std', 'time_stats.mlp_up_proj.max', 'time_stats.emb.mean', 'time_stats.input_layernorm.median', 'time_stats.mlp_up_proj.mean', 'time_stats.mlp_act.mean', 'time_stats.attn_pre_proj.max', 'time_stats.attn_rope.max'}) and 28 missing columns ({'max_model_len', 'time_stats.attn_decode.max', 'time_stats.attn_output_reshape.std', 'time_stats.attn_decode.median', 'time_stats.attn_prefill.mean', 'time_stats.attn_prefill.std', 'time_stats.attn_decode.min', 'time_stats.attn_decode.mean', 'block_size', 'n_q_head', 'time_stats.attn_prefill.min', 'time_stats.attn_prefill.max', 'attention_backend', 'kv_cache_size', 'time_stats.attn_output_reshape.max', 'time_stats.attn_input_reshape.min', 'time_stats.attn_input_reshape.median', 'is_prefill', 'time_stats.attn_output_reshape.mean', 'time_stats.attn_output_reshape.min', 'time_stats.attn_prefill.median', 'time_stats.attn_input_reshape.mean', 'batch_size', 'time_stats.attn_output_reshape.median', 'time_stats.attn_input_reshape.std', 'time_stats.attn_decode.std', 'prefill_chunk_size', 'time_stats.attn_input_reshape.max'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/project-vajra/dev-staging-internlm-internlm-20b-a40/mlp.csv (at revision 6c5c4d2eaff539e8ec8663d21105d5e9363943ec)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

time_stats.attn_input_reshape.min
float64
time_stats.attn_input_reshape.max
float64
time_stats.attn_input_reshape.mean
float64
time_stats.attn_input_reshape.median
float64
time_stats.attn_input_reshape.std
float64
time_stats.attn_decode.min
float64
time_stats.attn_decode.max
float64
time_stats.attn_decode.mean
float64
time_stats.attn_decode.median
float64
time_stats.attn_decode.std
float64
time_stats.attn_output_reshape.min
float64
time_stats.attn_output_reshape.max
float64
time_stats.attn_output_reshape.mean
float64
time_stats.attn_output_reshape.median
float64
time_stats.attn_output_reshape.std
float64
time_stats.attn_prefill.min
null
time_stats.attn_prefill.max
null
time_stats.attn_prefill.mean
null
time_stats.attn_prefill.median
null
time_stats.attn_prefill.std
null
n_embd
int64
n_q_head
int64
n_kv_head
int64
block_size
int64
num_tensor_parallel_workers
int64
max_model_len
int64
batch_size
int64
prefill_chunk_size
int64
kv_cache_size
int64
is_prefill
bool
attention_backend
string
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5,120
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false
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null
5,120
40
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.1046
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0.00049
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null
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null
5,120
40
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0
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0
null
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null
5,120
40
40
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1
4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.115
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0
0.002
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null
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null
5,120
40
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.1184
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0.00049
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null
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null
5,120
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4,096
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0
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.00049
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null
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null
5,120
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.1292
0.129
0.0004
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null
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null
5,120
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.1328
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0.0004
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null
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null
5,120
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4,096
36
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32
false
AttentionBackend.FLASH_ATTENTION
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0.1362
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0.0004
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null
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5,120
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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null
5,120
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1
4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0
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null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.1502
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0.0004
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null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.1528
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0.0004
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null
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null
5,120
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1
4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0
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null
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null
5,120
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.1608
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0.0004
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null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.168
0.1678
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0.0004
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null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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null
5,120
40
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.1784
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0.00049
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null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.0004
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.1886
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0.00049
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.00049
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.2166
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null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
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null
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5,120
40
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4,096
61
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false
AttentionBackend.FLASH_ATTENTION
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0.2242
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0.0004
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null
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null
null
5,120
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.2266
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0.0022
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0.0004
null
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null
5,120
40
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4,096
63
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false
AttentionBackend.FLASH_ATTENTION
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0.2306
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0.00049
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null
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null
5,120
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.2348
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0
null
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null
5,120
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.0004
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0
null
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null
null
null
5,120
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.2416
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0.00049
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0
null
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null
null
null
5,120
40
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1
4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.2454
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0.00049
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0.0024
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null
null
null
null
null
5,120
40
40
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1
4,096
68
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32
false
AttentionBackend.FLASH_ATTENTION
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0
0.002
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0
null
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5,120
40
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1
4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.2518
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0.0004
0.002
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0.0026
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0.00049
null
null
null
null
null
5,120
40
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1
4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0
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0.2552
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0.0004
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0.0026
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null
null
null
null
null
5,120
40
40
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4,096
71
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32
false
AttentionBackend.FLASH_ATTENTION
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0.00049
0.002
0.003
0.0028
0.003
0.0004
null
null
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null
5,120
40
40
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1
4,096
72
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32
false
AttentionBackend.FLASH_ATTENTION
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0
0.002
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0.0026
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0.00049
null
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5,120
40
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4,096
73
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32
false
AttentionBackend.FLASH_ATTENTION
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0
0.002
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0.0026
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0.00049
null
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null
5,120
40
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4,096
74
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32
false
AttentionBackend.FLASH_ATTENTION
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0
0.002
0.003
0.0028
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0.0004
null
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5,120
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.2732
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0.0004
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0
null
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5,120
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.277
0.2764
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0.00049
0.003
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0
null
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null
5,120
40
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
0.003
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0
null
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5,120
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.284
0.2834
0.283
0.00049
0.003
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0
null
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null
null
5,120
40
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.287
0.287
0
0.003
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0
null
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5,120
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0
0.003
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0
null
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5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.293
0.293
0
0.003
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0
null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.296
0.296
0
0.003
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0
null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.2994
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0.00049
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0
null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.3032
0.303
0.0004
0.003
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0
null
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null
null
null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.3078
0.308
0.0004
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0.003
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0
null
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null
null
null
5,120
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40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.312
0
0.003
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0
null
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null
5,120
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.3154
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0.00049
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0
null
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null
null
null
5,120
40
40
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4,096
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32
false
AttentionBackend.FLASH_ATTENTION
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0.32
0.32
0.32
0
0.003
0.003
0.003
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0
null
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null
5,120
40
40
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4,096
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false
AttentionBackend.FLASH_ATTENTION
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0.322
0.322
0.322
0
0.003
0.003
0.003
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0
null
null
null
null
null
5,120
40
40
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1
4,096
90
0
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false
AttentionBackend.FLASH_ATTENTION
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0.326
0.326
0.326
0
0.003
0.003
0.003
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0
null
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null
null
5,120
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1
4,096
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32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.33
0.331
0.3302
0.33
0.0004
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
92
0
32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.334
0.334
0.334
0.334
0
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
93
0
32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.337
0.337
0.337
0.337
0
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
94
0
32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.34
0.341
0.3404
0.34
0.00049
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
95
0
32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.343
0.344
0.3434
0.343
0.00049
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
96
0
32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.348
0.349
0.3482
0.348
0.0004
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
97
0
32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.349
0.35
0.3498
0.35
0.0004
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
98
0
32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.354
0.354
0.354
0.354
0
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
99
0
32
false
AttentionBackend.FLASH_ATTENTION
0
0
0
0
0
0.357
0.358
0.3572
0.357
0.0004
0.003
0.003
0.003
0.003
0
null
null
null
null
null
5,120
40
40
16
1
4,096
100
0
32
false
AttentionBackend.FLASH_ATTENTION
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