[Refactor] Fix spelling (open-mmlab#1681)

* [Refactor] Fix spelling

* [Refactor] Fix spelling

* [Refactor] Fix spelling

* [Refactor] Fix spelling

.dev_scripts/generate_readme.py

@@ -301,7 +301,7 @@ def generate_model_table(models,
     if any('Converted From' in model.data for model in models):
         table_string += (
             f"\n*Models with \* are converted from the [official repo]({converted_from['Code']}). "
-            "The config files of these models are only for inference. We haven't reprodcue the training results.*\n"
+            "The config files of these models are only for inference. We haven't reproduce the training results.*\n"
         )
 
     return table_string

configs/beit/README.md

@@ -74,7 +74,7 @@ python tools/test.py configs/beit/benchmarks/beit-base-p16_8xb128-coslr-100e_in1
 | `beit-base-p16_beit-pre_8xb128-coslr-100e_in1k` | [BEIT](https://download.openmmlab.com/mmselfsup/1.x/beit/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221128-ab79e626.pth) |   86.53    |   17.58   |   83.10   |    N/A    | [config](benchmarks/beit-base-p16_8xb128-coslr-100e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/1.x/beit/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221128-0ca393e9.pth) \| [log](https://download.openmmlab.com/mmselfsup/1.x/beit/beit_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221128-0ca393e9.json) |
 | `beit-base-p16_beit-in21k-pre_3rdparty_in1k`\* |             BEIT ImageNet-21k              |   86.53    |   17.58   |   85.28   |   97.59   | [config](benchmarks/beit-base-p16_8xb64_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/beit/beit-base_3rdparty_in1k_20221114-c0a4df23.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/microsoft/unilm/tree/master/beit). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/microsoft/unilm/tree/master/beit). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/beitv2/README.md

@@ -74,7 +74,7 @@ python tools/test.py configs/beitv2/benchmarks/beit-base-p16_8xb128-coslr-100e_i
 | `beit-base-p16_beitv2-pre_8xb128-coslr-100e_in1k` | [BEITV2](https://download.openmmlab.com/mmselfsup/1.x/beitv2/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k_20221212-a157be30.pth) |   86.53    |   17.58   |   85.00   |    N/A    | [config](benchmarks/beit-base-p16_8xb128-coslr-100e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/1.x/beitv2/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221212-d1c0789e.pth) \| [log](https://download.openmmlab.com/mmselfsup/1.x/beitv2/beitv2_vit-base-p16_8xb256-amp-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20221212-d1c0789e.json) |
 | `beit-base-p16_beitv2-in21k-pre_3rdparty_in1k`\* |            BEITV2 ImageNet-21k             |   86.53    |   17.58   |   86.47   |   97.99   | [config](benchmarks/beit-base-p16_8xb64_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/beit/beitv2-base_3rdparty_in1k_20221114-73e11905.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/microsoft/unilm/tree/master/beit2). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/microsoft/unilm/tree/master/beit2). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/blip/README.md

@@ -112,7 +112,7 @@ python tools/test.py configs/blip/blip-base_8xb32_caption.py https://download.op
 | :-------------------------- | :--------: | :-------: | :---------------------------------: | :------------------------------------------------------------------------------------------------------------: |
 | `blip-base_3rdparty_nlvr`\* |   259.37   |   82.33   | [config](./blip-base_8xb32_nlvr.py) | [model](https://download.openmmlab.com/mmclassification/v1/blip/blip-base_3rdparty_nlvr_20230427-3b14d33f.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/salesforce/LAVIS). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/salesforce/LAVIS). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 *Results with # denote zero-shot evaluation. The corresponding model hasn't been finetuned on that dataset.*
 

configs/blip2/README.md

@@ -58,7 +58,7 @@ python tools/test.py configs/blip2/blip2_8xb32_retrieval.py https://download.ope
 | :--------------------------- | :--------: | :------: | :----------------------------------: | :-------------------------------------------------------------------------------------------------------------: |
 | `blip2_3rdparty_retrieval`\* |  1173.19   |  85.40   | [config](./blip2_8xb32_retrieval.py) | [model](https://download.openmmlab.com/mmclassification/v1/blip2/blip2_3rdparty_pretrain_20230505-f7ef4390.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/salesforce/LAVIS). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/salesforce/LAVIS). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/chinese_clip/README.md

@@ -55,7 +55,7 @@ python tools/test.py configs/chinese_clip/cn-clip_resnet50_zeroshot-cls_cifar100
 | `cn-clip_vit-large-p14_zeroshot-cls_cifar100`\* |   406.00   |   74.80   | [config](cn-clip_vit-large-p14_zeroshot-cls_cifar100.py) | [model](https://download.openmmlab.com/mmpretrain/v1.0/chinese_clip/cn-clip_vit-large-p14_3rdparty_20230519-3f844503.pth) |
 | `cn-clip_vit-huge-p14_zeroshot-cls_cifar100`\*  |   958.00   |   79.10   | [config](cn-clip_vit-huge-p14_zeroshot-cls_cifar100.py)  | [model](https://download.openmmlab.com/mmpretrain/v1.0/chinese_clip/cn-clip_vit-huge-p14_3rdparty_20230519-e4f49b00.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/OFA-Sys/Chinese-CLIP). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/OFA-Sys/Chinese-CLIP). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/clip/README.md

@@ -74,7 +74,7 @@ python tools/test.py configs/clip/vit-base-p32_pt-64xb64_in1k.py https://downloa
 | `vit-base-p16_clip-openai-in12k-pre_3rdparty_in1k-384px`\* | CLIP OPENAI ImageNet-12k  |   86.57    |   49.37   |   86.87   |   98.05   | [config](vit-base-p16_pt-64xb64_in1k-384px.py) | [model](https://download.openmmlab.com/mmclassification/v0/clip/clip-vit-base-p16_openai-in12k-pre_3rdparty_in1k-384px_20221220-8df86b74.pth) |
 | `vit-base-p16_clip-openai-pre_3rdparty_in1k-384px`\* |        CLIP OPENAI        |   86.57    |   49.37   |   86.25   |   97.90   | [config](vit-base-p16_pt-64xb64_in1k-384px.py) | [model](https://download.openmmlab.com/mmclassification/v0/clip/clip-vit-base-p16_openai-pre_3rdparty_in1k-384px_20221220-eb012e87.pth) |
 
-*Models with * are converted from the [timm](https://github.com/rwightman/pytorch-image-models). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [timm](https://github.com/rwightman/pytorch-image-models). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/conformer/README.md

@@ -70,7 +70,7 @@ python tools/test.py configs/conformer/conformer-tiny-p16_8xb128_in1k.py https:/
 | `conformer-small-p32_8xb128_in1k`     | From scratch |   38.85    |   7.09    |   81.96   |   96.02   | [config](conformer-small-p32_8xb128_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/conformer/conformer-small-p32_8xb128_in1k_20211206-947a0816.pth) |
 | `conformer-base-p16_3rdparty_in1k`\*  | From scratch |   83.29    |   22.89   |   83.82   |   96.59   | [config](conformer-base-p16_8xb128_in1k.py)  | [model](https://download.openmmlab.com/mmclassification/v0/conformer/conformer-base-p16_3rdparty_8xb128_in1k_20211206-bfdf8637.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/pengzhiliang/Conformer/blob/main/models.py#L89). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/pengzhiliang/Conformer/blob/main/models.py#L89). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/convmixer/README.md

@@ -63,7 +63,7 @@ python tools/test.py configs/convmixer/convmixer-768-32_10xb64_in1k.py https://d
 | `convmixer-1024-20_3rdparty_in1k`\* | From scratch |   24.38    |   5.55    |   76.94   |   93.36   | [config](convmixer-1024-20_10xb64_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/convmixer/convmixer-1024-20_3rdparty_10xb64_in1k_20220323-48f8aeba.pth) |
 | `convmixer-1536-20_3rdparty_in1k`\* | From scratch |   51.63    |   48.71   |   81.37   |   95.61   | [config](convmixer-1536-20_10xb64_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/convmixer/convmixer-1536_20_3rdparty_10xb64_in1k_20220323-ea5786f3.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/locuslab/convmixer). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/locuslab/convmixer). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/convnext/README.md

@@ -81,7 +81,7 @@ python tools/test.py configs/convnext/convnext-tiny_32xb128_in1k.py https://down
 | `convnext-large_3rdparty_in21k`\*  |   197.77   |   34.37   | [config](convnext-large_64xb64_in21k.py)  | [model](https://download.openmmlab.com/mmclassification/v0/convnext/convnext-large_3rdparty_in21k_20220124-41b5a79f.pth) |
 | `convnext-xlarge_3rdparty_in21k`\* |   350.20   |   60.93   | [config](convnext-xlarge_64xb64_in21k.py) | [model](https://download.openmmlab.com/mmclassification/v0/convnext/convnext-xlarge_3rdparty_in21k_20220124-f909bad7.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/facebookresearch/ConvNeXt). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/facebookresearch/ConvNeXt). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ### Image Classification on ImageNet-1k
 
@@ -109,7 +109,7 @@ python tools/test.py configs/convnext/convnext-tiny_32xb128_in1k.py https://down
 | `convnext-xlarge_in21k-pre_3rdparty_in1k`\*       | ImageNet-21k |   350.20   |   60.93   |   86.97   |   98.20   |    [config](convnext-xlarge_64xb64_in1k.py)    | [model](https://download.openmmlab.com/mmclassification/v0/convnext/convnext-xlarge_in21k-pre-3rdparty_64xb64_in1k_20220124-76b6863d.pth) |
 | `convnext-xlarge_in21k-pre-3rdparty_in1k-384px`\* | From scratch |   350.20   |  179.20   |   87.76   |   98.55   | [config](convnext-xlarge_64xb64_in1k-384px.py) | [model](https://download.openmmlab.com/mmclassification/v0/convnext/convnext-xlarge_in21k-pre-3rdparty_in1k-384px_20221219-b161bc14.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/facebookresearch/ConvNeXt). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/facebookresearch/ConvNeXt). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/convnext_v2/README.md

@@ -68,7 +68,7 @@ python tools/test.py configs/convnext_v2/convnext-v2-atto_32xb32_in1k.py https:/
 | `convnext-v2-large_3rdparty-fcmae_in1k`\* |   197.96   |   34.40   | [config](convnext-v2-large_32xb32_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/convnext-v2/convnext-v2-large_3rdparty-fcmae_in1k_20230104-bf38df92.pth) |
 | `convnext-v2-huge_3rdparty-fcmae_in1k`\*  |   660.29   |  115.00   | [config](convnext-v2-huge_32xb32_in1k.py)  | [model](https://download.openmmlab.com/mmclassification/v0/convnext-v2/convnext-v2-huge_3rdparty-fcmae_in1k_20230104-fe43ae6c.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/facebookresearch/ConvNeXt-V2). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/facebookresearch/ConvNeXt-V2). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ### Image Classification on ImageNet-1k
 
@@ -93,7 +93,7 @@ python tools/test.py configs/convnext_v2/convnext-v2-atto_32xb32_in1k.py https:/
 | `convnext-v2-huge_fcmae-in21k-pre_3rdparty_in1k-384px`\* | FCMAE ImageNet-21k |   660.29   |  337.96   |   88.68   |   98.73   | [config](convnext-v2-huge_32xb32_in1k-384px.py)  | [model](https://download.openmmlab.com/mmclassification/v0/convnext-v2/convnext-v2-huge_fcmae-in21k-pre_3rdparty_in1k-384px_20230104-02a4eb35.pth) |
 | `convnext-v2-huge_fcmae-in21k-pre_3rdparty_in1k-512px`\* | FCMAE ImageNet-21k |   660.29   |  600.81   |   88.86   |   98.74   | [config](convnext-v2-huge_32xb32_in1k-512px.py)  | [model](https://download.openmmlab.com/mmclassification/v0/convnext-v2/convnext-v2-huge_fcmae-in21k-pre_3rdparty_in1k-512px_20230104-ce32e63c.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/facebookresearch/ConvNeXt-V2). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/facebookresearch/ConvNeXt-V2). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/cspnet/README.md

@@ -63,7 +63,7 @@ python tools/test.py configs/cspnet/cspdarknet50_8xb32_in1k.py https://download.
 | `cspresnet50_3rdparty_8xb32_in1k`\*  | From scratch |   21.62    |   3.48    |   79.55   |   94.68   | [config](cspresnet50_8xb32_in1k.py)  | [model](https://download.openmmlab.com/mmclassification/v0/cspnet/cspresnet50_3rdparty_8xb32_in1k_20220329-dd6dddfb.pth) |
 | `cspresnext50_3rdparty_8xb32_in1k`\* | From scratch |   20.57    |   3.11    |   79.96   |   94.96   | [config](cspresnext50_8xb32_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/cspnet/cspresnext50_3rdparty_8xb32_in1k_20220329-2cc84d21.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/rwightman/pytorch-image-models). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/rwightman/pytorch-image-models). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/davit/README.md

@@ -63,7 +63,7 @@ python tools/test.py configs/davit/davit-tiny_4xb256_in1k.py https://download.op
 | `davit-small_3rdparty_in1k`\* | From scratch |   49.75    |   8.80    |   83.61   |   96.75   | [config](davit-small_4xb256_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/davit/davit-small_3rdparty_in1k_20221116-51a849a6.pth) |
 | `davit-base_3rdparty_in1k`\*  | From scratch |   87.95    |   15.51   |   84.09   |   96.82   | [config](davit-base_4xb256_in1k.py)  | [model](https://download.openmmlab.com/mmclassification/v0/davit/davit-base_3rdparty_in1k_20221116-19e0d956.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/dingmyu/davit/blob/main/mmdet/mmdet/models/backbones/davit.py#L355). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/dingmyu/davit/blob/main/mmdet/mmdet/models/backbones/davit.py#L355). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/deit/README.md

@@ -75,7 +75,7 @@ python tools/test.py configs/deit/deit-tiny_4xb256_in1k.py https://download.open
 | `deit-base_224px-pre_3rdparty_in1k-384px`\*       |    224px     |   86.86    |   55.54   |   83.04   |   96.31   |      [config](deit-base_16xb32_in1k-384px.py)      | [model](https://download.openmmlab.com/mmclassification/v0/deit/deit-base_3rdparty_ft-16xb32_in1k-384px_20211124-822d02f2.pth) |
 | `deit-base-distilled_224px-pre_3rdparty_in1k-384px`\* |    224px     |   87.63    |   55.65   |   85.55   |   97.35   | [config](deit-base-distilled_16xb32_in1k-384px.py) | [model](https://download.openmmlab.com/mmclassification/v0/deit/deit-base-distilled_3rdparty_ft-16xb32_in1k-384px_20211216-e48d6000.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L168). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/facebookresearch/deit/blob/f5123946205daf72a88783dae94cabff98c49c55/models.py#L168). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ```{warning}
 MMPretrain doesn't support training the distilled version DeiT.

configs/deit3/README.md

@@ -76,7 +76,7 @@ python tools/test.py configs/deit3/deit3-small-p16_64xb64_in1k.py https://downlo
 | `deit3-huge-p14_3rdparty_in1k`\*                  | From scratch |   632.13   |  167.40   |   85.21   |   97.36   |    [config](deit3-huge-p14_64xb32_in1k.py)     | [model](https://download.openmmlab.com/mmclassification/v0/deit3/deit3-huge-p14_3rdparty_in1k_20221009-e107bcb7.pth) |
 | `deit3-huge-p14_in21k-pre_3rdparty_in1k`\*        | ImageNet-21k |   632.13   |  167.40   |   87.19   |   98.26   |    [config](deit3-huge-p14_64xb32_in1k.py)     | [model](https://download.openmmlab.com/mmclassification/v0/deit3/deit3-huge-p14_in21k-pre_3rdparty_in1k_20221009-19b8a535.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/facebookresearch/deit/blob/main/models_v2.py#L171). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/facebookresearch/deit/blob/main/models_v2.py#L171). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation
 

configs/densenet/README.md

@@ -64,7 +64,7 @@ python tools/test.py configs/densenet/densenet121_4xb256_in1k.py https://downloa
 | `densenet201_3rdparty_in1k`\* | From scratch |   20.01    |   4.37    |   77.32   |   93.64   | [config](densenet201_4xb256_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/densenet/densenet201_4xb256_in1k_20220426-05cae4ef.pth) |
 | `densenet161_3rdparty_in1k`\* | From scratch |   28.68    |   7.82    |   77.61   |   93.83   | [config](densenet161_4xb256_in1k.py) | [model](https://download.openmmlab.com/mmclassification/v0/densenet/densenet161_4xb256_in1k_20220426-ee6a80a9.pth) |
 
-*Models with * are converted from the [official repo](https://github.com/pytorch/vision/blob/main/torchvision/models/densenet.py). The config files of these models are only for inference. We haven't reprodcue the training results.*
+*Models with * are converted from the [official repo](https://github.com/pytorch/vision/blob/main/torchvision/models/densenet.py). The config files of these models are only for inference. We haven't reproduce the training results.*
 
 ## Citation