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fix inference and training readme
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杨zhichao.yang committed Jan 19, 2024
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2 changes: 1 addition & 1 deletion README.md
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<td class="xl69" x:str>NLP</td>
<td class="xl69" x:str>f32/f16</td>
<td class="xl69" x:str>W32A16</td>
<td class="xl69" x:str>Incoming</td>
<td class="xl69" x:str>f16</td>
<td class="xl69" x:str>N/A</td>
</tr>
<tr height="16.80" style='height:16.80pt;'>
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6 changes: 0 additions & 6 deletions training/iluvatar/t5_small-pytorch/README.md
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| BI-V100单机单卡(1x1) | fp32 | / | / | / | / | / | 41.2064 | 18.9082 | 29.1922 | 38.4298 | 27.378 /32.0 |
| BI-V100两机8卡(2x8) | fp32 | | | | | | | | | | |

注意: T5模型MFU数值较低, 为11.8%
1x8训练的MFU计算过程如下:
`MFU = 400.26068691305795 * 1024 * (60 * 10^6) * 6 / (156 * 1000^4) / 8 = 11.8%`

其中, 1024为seq_len, 60 millions为参数量, (156 * 1000^4)为A100 tf32算力

1 change: 0 additions & 1 deletion training/run_benchmarks/config/test_conf.py
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# "transformer:pytorch:R300:1:8:1": "/raid/dataset/transformer/wmt14_en_de_joined_dict",
# "bigtransfer:pytorch:R300:1:8:1": "/raid/dataset/ImageNet_1k_2012/",
# "efficientnet:pytorch:R300:1:8:1": "/raid/dataset/ImageNet_1k_2012/",


# iluvatar cases
# "bigtransfer:pytorch:BI-V100:1:8:1": "/raid/dataset/ImageNet_1k_2012/",
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