mode_export_modelzoo

mindspore/train/serialization.py

@@ -29,10 +29,9 @@ from mindspore.common.initializer import initializer
 from mindspore.common.parameter import Parameter
 from mindspore.common.api import _executor
 from mindspore.common import dtype as mstype
-from mindspore._checkparam import check_input_data
+from mindspore._checkparam import check_input_data, Validator
 from mindspore.train.quant import quant
 import mindspore.context as context
-from .._checkparam import Validator
 
 __all__ = ["save_checkpoint", "load_checkpoint", "load_param_into_net", "export", "parse_print",
            "build_searched_strategy", "merge_sliced_parameter"]

model_zoo/official/cv/lenet_quant/export.py

@@ -23,7 +23,7 @@ import mindspore
 from mindspore import Tensor
 from mindspore import context
 from mindspore.train.quant import quant
-from mindspore.train.serialization import load_checkpoint, load_param_into_net
+from mindspore.train.serialization import load_checkpoint, load_param_into_net, export
 
 from src.config import mnist_cfg as cfg
 from src.lenet_fusion import LeNet5 as LeNet5Fusion
@@ -52,4 +52,4 @@ if __name__ == "__main__":
 
     # export network
     inputs = Tensor(np.ones([1, 1, cfg.image_height, cfg.image_width]), mindspore.float32)
-    quant.export(network, inputs, file_name="lenet_quant", file_format='AIR')
+    export(network, inputs, file_name="lenet_quant", file_format='MINDIR', quant_mode='AUTO')

model_zoo/official/cv/mobilenetv2_quant/export.py

@@ -20,7 +20,7 @@ import numpy as np
 import mindspore
 from mindspore import Tensor
 from mindspore import context
-from mindspore.train.serialization import load_checkpoint, load_param_into_net
+from mindspore.train.serialization import load_checkpoint, load_param_into_net, export
 from mindspore.train.quant import quant
 
 from src.mobilenetV2 import mobilenetV2
@@ -50,5 +50,5 @@ if __name__ == '__main__':
     # export network
     print("============== Starting export ==============")
     inputs = Tensor(np.ones([1, 3, cfg.image_height, cfg.image_width]), mindspore.float32)
-    quant.export(network, inputs, file_name="mobilenet_quant", file_format='MINDIR')
+    export(network, inputs, file_name="mobilenet_quant", file_format='MINDIR', quant_mode='AUTO')
     print("============== End export ==============")

tests/st/quantization/lenet_quant/test_lenet_quant.py

@@ -24,7 +24,7 @@ from mindspore.common import dtype as mstype
 import mindspore.nn as nn
 from mindspore.nn.metrics import Accuracy
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
-from mindspore.train.serialization import load_checkpoint, load_param_into_net
+from mindspore.train.serialization import load_checkpoint, load_param_into_net, export
 from mindspore.train import Model
 from mindspore.train.quant import quant
 from mindspore.train.quant.quant_utils import load_nonquant_param_into_quant_net
@@ -136,7 +136,7 @@ def export_lenet():
 
     # export network
     inputs = Tensor(np.ones([1, 1, cfg.image_height, cfg.image_width]), mstype.float32)
-    quant.export(network, inputs, file_name="lenet_quant", file_format='MINDIR')
+    export(network, inputs, file_name="lenet_quant", file_format='MINDIR', quant_mode='AUTO')
 
 
 @pytest.mark.level0