diff --git a/ppocr/modeling/architectures/__init__.py b/ppocr/modeling/architectures/__init__.py
index e9a01cf0281b91d29f2cce88375be3aaf43feb2e..3f47f64a0f01c2267c7ff4aecb3815915b24dadb 100755
--- a/ppocr/modeling/architectures/__init__.py
+++ b/ppocr/modeling/architectures/__init__.py
@@ -15,10 +15,13 @@
 import copy
 import importlib
 
+from paddle.jit import to_static
+from paddle.static import InputSpec
+
 from .base_model import BaseModel
 from .distillation_model import DistillationModel
 
-__all__ = ['build_model']
+__all__ = ["build_model", "apply_to_static"]
 
 
 def build_model(config):
@@ -30,3 +33,18 @@ def build_model(config):
         mod = importlib.import_module(__name__)
         arch = getattr(mod, name)(config)
     return arch
+
+
+def apply_to_static(model, config, logger):
+    if config["Global"].get("to_static", False) is not True:
+        return model
+    assert "image_shape" in config[
+        "Global"], "image_shape must be assigned for static training mode..."
+    supported_list = ["DB"]
+    assert config["Architecture"][
+        "algorithm"] in supported_list, f"algorithms that supports static training must in in {supported_list} but got {config['Architecture']['algorithm']}"
+
+    specs = [InputSpec([None] + config["Global"]["image_shape"])]
+    model = to_static(model, input_spec=specs)
+    logger.info("Successfully to apply @to_static with specs: {}".format(specs))
+    return model
diff --git a/tools/train.py b/tools/train.py
index 42aba548d6bf5fc35f033ef2baca0fb54d79e75a..b7c25e34231fb650fd2c7c89dc17320f561962f9 100755
--- a/tools/train.py
+++ b/tools/train.py
@@ -35,6 +35,7 @@ from ppocr.postprocess import build_post_process
 from ppocr.metrics import build_metric
 from ppocr.utils.save_load import load_model
 from ppocr.utils.utility import set_seed
+from ppocr.modeling.architectures import apply_to_static
 import tools.program as program
 
 dist.get_world_size()
@@ -121,6 +122,8 @@ def main(config, device, logger, vdl_writer):
     if config['Global']['distributed']:
         model = paddle.DataParallel(model)
 
+    model = apply_to_static(model, config, logger)
+
     # build loss
     loss_class = build_loss(config['Loss'])