[Fix] fix base name and dist_xx (#1253)

* fix base name and dist_xx

* update registry

mmocr/models/textrecog/recognizers/__init__.py

@@ -1,6 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from .abinet import ABINet
-from .base import BaseRecognizer
+from .base_recognizer import BaseRecognizer
 from .crnn import CRNN
 from .encoder_decoder_recognizer import EncoderDecoderRecognizer
 from .master import MASTER

mmocr/models/textrecog/recognizers/encoder_decoder_recognizer.py

@@ -8,7 +8,7 @@ from mmocr.registry import MODELS
 from mmocr.utils.typing import (ConfigType, InitConfigType, OptConfigType,
                                 OptRecSampleList, RecForwardResults,
                                 RecSampleList)
-from .base import BaseRecognizer
+from .base_recognizer import BaseRecognizer
 
 
 @MODELS.register_module()

mmocr/registry.py

@@ -1,6 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
-"""MMOCR provides 17 registry nodes to support using modules across projects.
-Each node is a child of the root registry in MMEngine.
+"""MMDetection provides 17 registry nodes to support using modules across
+projects. Each node is a child of the root registry in MMEngine.
 
 More details can be found at
 https://mmengine.readthedocs.io/en/latest/tutorials/registry.html.
@@ -8,13 +8,16 @@ https://mmengine.readthedocs.io/en/latest/tutorials/registry.html.
 
 from mmengine.registry import DATA_SAMPLERS as MMENGINE_DATA_SAMPLERS
 from mmengine.registry import DATASETS as MMENGINE_DATASETS
+from mmengine.registry import EVALUATOR as MMENGINE_EVALUATOR
 from mmengine.registry import HOOKS as MMENGINE_HOOKS
+from mmengine.registry import LOG_PROCESSORS as MMENGINE_LOG_PROCESSORS
 from mmengine.registry import LOOPS as MMENGINE_LOOPS
 from mmengine.registry import METRICS as MMENGINE_METRICS
 from mmengine.registry import MODEL_WRAPPERS as MMENGINE_MODEL_WRAPPERS
 from mmengine.registry import MODELS as MMENGINE_MODELS
 from mmengine.registry import \
     OPTIM_WRAPPER_CONSTRUCTORS as MMENGINE_OPTIM_WRAPPER_CONSTRUCTORS
+from mmengine.registry import OPTIM_WRAPPERS as MMENGINE_OPTIM_WRAPPERS
 from mmengine.registry import OPTIMIZERS as MMENGINE_OPTIMIZERS
 from mmengine.registry import PARAM_SCHEDULERS as MMENGINE_PARAM_SCHEDULERS
 from mmengine.registry import \
@@ -43,24 +46,29 @@ DATASETS = Registry('dataset', parent=MMENGINE_DATASETS)
 DATA_SAMPLERS = Registry('data sampler', parent=MMENGINE_DATA_SAMPLERS)
 TRANSFORMS = Registry('transform', parent=MMENGINE_TRANSFORMS)
 
-# mangage all kinds of modules inheriting `nn.Module`
+# manage all kinds of modules inheriting `nn.Module`
 MODELS = Registry('model', parent=MMENGINE_MODELS)
-# mangage all kinds of model wrappers like 'MMDistributedDataParallel'
+# manage all kinds of model wrappers like 'MMDistributedDataParallel'
 MODEL_WRAPPERS = Registry('model_wrapper', parent=MMENGINE_MODEL_WRAPPERS)
-# mangage all kinds of weight initialization modules like `Uniform`
+# manage all kinds of weight initialization modules like `Uniform`
 WEIGHT_INITIALIZERS = Registry(
     'weight initializer', parent=MMENGINE_WEIGHT_INITIALIZERS)
 
-# mangage all kinds of optimizers like `SGD` and `Adam`
+# manage all kinds of optimizers like `SGD` and `Adam`
 OPTIMIZERS = Registry('optimizer', parent=MMENGINE_OPTIMIZERS)
+# manage optimizer wrapper
+OPTIM_WRAPPERS = Registry('optim wrapper', parent=MMENGINE_OPTIM_WRAPPERS)
 # manage constructors that customize the optimization hyperparameters.
 OPTIM_WRAPPER_CONSTRUCTORS = Registry(
     'optimizer constructor', parent=MMENGINE_OPTIM_WRAPPER_CONSTRUCTORS)
-# mangage all kinds of parameter schedulers like `MultiStepLR`
+# manage all kinds of parameter schedulers like `MultiStepLR`
 PARAM_SCHEDULERS = Registry(
     'parameter scheduler', parent=MMENGINE_PARAM_SCHEDULERS)
+
 # manage all kinds of metrics
 METRICS = Registry('metric', parent=MMENGINE_METRICS)
+# manage evaluator
+EVALUATOR = Registry('evaluator', parent=MMENGINE_EVALUATOR)
 
 # manage task-specific modules like anchor generators and box coders
 TASK_UTILS = Registry('task util', parent=MMENGINE_TASK_UTILS)
@@ -69,3 +77,6 @@ TASK_UTILS = Registry('task util', parent=MMENGINE_TASK_UTILS)
 VISUALIZERS = Registry('visualizer', parent=MMENGINE_VISUALIZERS)
 # manage visualizer backend
 VISBACKENDS = Registry('vis_backend', parent=MMENGINE_VISBACKENDS)
+
+# manage logprocessor
+LOG_PROCESSORS = Registry('log_processor', parent=MMENGINE_LOG_PROCESSORS)

tools/dist_test.sh

@@ -1,11 +1,5 @@
 #!/usr/bin/env bash
 
-if [ $# -lt 3 ]
-then
-    echo "Usage: bash $0 CONFIG CHECKPOINT GPUS"
-    exit
-fi
-
 CONFIG=$1
 CHECKPOINT=$2
 GPUS=$3

tools/dist_train.sh

@@ -1,33 +1,20 @@
+
 #!/usr/bin/env bash
 
-if [ $# -lt 3 ]
-then
-    echo "Usage: bash $0 CONFIG WORK_DIR GPUS"
-    exit
-fi
-
 CONFIG=$1
-WORK_DIR=$2
-GPUS=$3
+GPUS=$2
 NNODES=${NNODES:-1}
 NODE_RANK=${NODE_RANK:-0}
 PORT=${PORT:-29500}
 MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}
 
 PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
-
-if [ ${GPUS} == 1 ]; then
-    python $(dirname "$0")/train.py  $CONFIG --work-dir=${WORK_DIR} ${@:4}
-else
-    python -m torch.distributed.launch \
-        --nnodes=$NNODES \
-        --node_rank=$NODE_RANK \
-        --master_addr=$MASTER_ADDR \
-        --nproc_per_node=$GPUS \
-        --master_port=$PORT \
-        $(dirname "$0")/train.py \
-        $CONFIG \
-        --seed 0 \
-        --work-dir=${WORK_DIR} \
-        --launcher pytorch ${@:4}
-fi
+python -m torch.distributed.launch \
+    --nnodes=$NNODES \
+    --node_rank=$NODE_RANK \
+    --master_addr=$MASTER_ADDR \
+    --nproc_per_node=$GPUS \
+    --master_port=$PORT \
+    $(dirname "$0")/train.py \
+    $CONFIG \
+    --launcher pytorch ${@:3}