support paddle2onnx in act (#1349)

example/auto_compression/pytorch_yolo_series/run.py

@@ -113,6 +113,7 @@ def main():
         config=all_config,
         eval_callback=eval_func)
     ac.compress()
+    ac.export_onnx()
 
 
 if __name__ == '__main__':

paddleslim/auto_compression/compressor.py

@@ -29,7 +29,7 @@ from ..quant.quanter import convert, quant_post
 from ..common.recover_program import recover_inference_program
 from ..common import get_logger
 from ..common.patterns import get_patterns
-from ..common.load_model import load_inference_model, get_model_dir
+from ..common.load_model import load_inference_model, get_model_dir, export_onnx
 from ..common.dataloader import wrap_dataloader, get_feed_vars
 from ..common.config_helper import load_config
 from ..analysis import TableLatencyPredictor
@@ -826,3 +826,17 @@ class AutoCompression:
             fetch_vars=test_program_info.fetch_targets,
             executor=self._exe,
             program=test_program)
+
+    def export_onnx(self,
+                    model_name='quant_model.onnx',
+                    deploy_backend='tensorrt'):
+        infer_model_path = os.path.join(self.final_dir, self.model_filename)
+        assert os.path.exists(
+            infer_model_path), 'Not found {}, please check it.'.format(
+                infer_model_path)
+        export_onnx(
+            self.final_dir,
+            model_filename=self.model_filename,
+            params_filename=self.params_filename,
+            save_file_path=os.path.join(self.final_dir, model_name),
+            deploy_backend=deploy_backend)

paddleslim/common/__init__.py

@@ -25,7 +25,7 @@ from .analyze_helper import VarCollector
 from . import wrapper_function
 from . import recover_program
 from . import patterns
-from .load_model import load_inference_model, get_model_dir, load_onnx_model
+from .load_model import load_inference_model, get_model_dir, load_onnx_model, export_onnx
 from .dataloader import wrap_dataloader, get_feed_vars
 from .config_helper import load_config, save_config
 

paddleslim/common/load_model.py

@@ -17,16 +17,15 @@ import logging
 import os
 import shutil
 import sys
+import pkg_resources as pkg
 import paddle
-from x2paddle.decoder.onnx_decoder import ONNXDecoder
-from x2paddle.op_mapper.onnx2paddle.onnx_op_mapper import ONNXOpMapper
-from x2paddle.optimizer.optimizer import GraphOptimizer
-from x2paddle.utils import ConverterCheck
 
 from . import get_logger
 _logger = get_logger(__name__, level=logging.INFO)
 
-__all__ = ['load_inference_model', 'get_model_dir', 'load_onnx_model']
+__all__ = [
+    'load_inference_model', 'get_model_dir', 'load_onnx_model', 'export_onnx'
+]
 
 
 def load_inference_model(path_prefix,
@@ -116,24 +115,37 @@ def load_onnx_model(model_path, disable_feedback=False):
         return val_program, feed_target_names, fetch_targets
     else:
         # onnx to paddle inference model.
+        try:
+            pkg.require('x2paddle')
+        except:
+            from pip._internal import main
+            main(['install', 'x2paddle'])
+        try:
+            from x2paddle.decoder.onnx_decoder import ONNXDecoder
+            from x2paddle.op_mapper.onnx2paddle.onnx_op_mapper import ONNXOpMapper
+            from x2paddle.optimizer.optimizer import GraphOptimizer
+            from x2paddle.utils import ConverterCheck
+        except:
+            _logger.error(
+                "x2paddle is not installed, please use \"pip install x2paddle\"."
+            )
         time_info = int(time.time())
         if not disable_feedback:
             ConverterCheck(
                 task="ONNX", time_info=time_info, convert_state="Start").start()
         # check onnx installation and version
         try:
+            pkg.require('onnx')
             import onnx
             version = onnx.version.version
             v0, v1, v2 = version.split('.')
             version_sum = int(v0) * 100 + int(v1) * 10 + int(v2)
             if version_sum < 160:
-                _logger.info("[ERROR] onnx>=1.6.0 is required")
-                sys.exit(1)
+                _logger.error(
+                    "onnx>=1.6.0 is required, please use \"pip install onnx\".")
         except:
-            _logger.info(
-                "[ERROR] onnx is not installed, use \"pip install onnx==1.6.0\"."
-            )
-            sys.exit(1)
+            from pip._internal import main
+            main(['install', 'onnx==1.12.0'])
 
         # support distributed convert model
         model_idx = paddle.distributed.get_rank(
@@ -182,4 +194,30 @@ def load_onnx_model(model_path, disable_feedback=False):
         shutil.rmtree(
             os.path.join(inference_model_path, 'onnx2paddle_{}'.format(
                 model_idx)))
-        return val_program, feed_target_names, fetch_targets
\ No newline at end of file
+        return val_program, feed_target_names, fetch_targets
+
+
+def export_onnx(model_dir,
+                model_filename=None,
+                params_filename=None,
+                save_file_path='output.onnx',
+                opset_version=13,
+                deploy_backend='tensorrt'):
+    if not model_filename:
+        model_filename = 'model.pdmodel'
+    if not params_filename:
+        params_filename = 'model.pdiparams'
+    try:
+        pkg.require('paddle2onnx')
+    except:
+        from pip._internal import main
+        main(['install', 'paddle2onnx==1.0.0rc3'])
+    import paddle2onnx
+    paddle2onnx.command.c_paddle_to_onnx(
+        model_file=os.path.join(model_dir, model_filename),
+        params_file=os.path.join(model_dir, params_filename),
+        save_file=save_file_path,
+        opset_version=opset_version,
+        enable_onnx_checker=True,
+        deploy_backend=deploy_backend)
+    _logger.info('Convert model to ONNX: {}'.format(save_file_path))

requirements.txt

@@ -5,5 +5,3 @@ pillow
 pyyaml
 scikit-learn
 smac
-onnx
-x2paddle==1.3.8

tests/act/test_act_api.py

@@ -8,8 +8,8 @@ import unittest
 import numpy as np
 from paddle.io import Dataset
 from paddleslim.auto_compression import AutoCompression
-from paddleslim.auto_compression.config_helpers import load_config
-from paddleslim.auto_compression.utils.load_model import load_inference_model
+from paddleslim.common import load_config
+from paddleslim.common import load_inference_model, export_onnx
 
 
 class RandomEvalDataset(Dataset):
@@ -142,6 +142,14 @@ class TestLoadONNXModel(ACTBase):
             executor=exe,
             model_filename='model.pdmodel',
             params_filename='model.paiparams')
+        # convert onnx
+        export_onnx(
+            self.model_dir,
+            model_filename='model.pdmodel',
+            params_filename='model.paiparams',
+            save_file_path='output.onnx',
+            opset_version=13,
+            deploy_backend='tensorrt')
 
 
 if __name__ == '__main__':