using paddleslim 2.4 api

examples/wenetspeech/asr1/local/quant.sh

@@ -1,5 +1,6 @@
 #!/bin/bash
 
+# ./local/quant.sh conf/chunk_conformer_u2pp.yaml conf/tuning/chunk_decode.yaml exp/chunk_conformer_u2pp/checkpoints/avg_10 data/wav.aishell.test.scp 
 if [ $# != 4 ];then
     echo "usage: ${0} config_path decode_config_path ckpt_path_prefix audio_scp"
     exit -1
@@ -48,6 +49,7 @@ for type in  attention_rescoring; do
     --checkpoint_path ${ckpt_prefix} \
     --opts decode.decoding_method ${type} \
     --opts decode.decode_batch_size ${batch_size} \
+    --num_utts 200 \
     --audio_scp ${audio_scp}
 
     if [ $? -ne 0 ]; then

paddlespeech/s2t/exps/u2/bin/quant.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""Evaluation for U2 model."""
+"""Quantzation U2 model."""
 import paddle
 from kaldiio import ReadHelper
 from paddleslim import PTQ
@@ -159,17 +159,12 @@ class U2Infer():
 
         # jit save
         logger.info(f"export save: {self.args.export_path}")
-        config = {
+        self.ptq.save_quantized_model(
-            'is_static': True,
+            self.model, 
-            'combine_params': True,
+            self.args.export_path, 
-            'skip_forward': True
+            postprocess=False, 
-        }
+            combine_params=True, 
-        self.ptq.save_quantized_model(self.model, self.args.export_path)
+            skip_forward=True)
-        # paddle.jit.save(
-        #     self.model,
-        #     self.args.export_path,
-        #     combine_params=True,
-        #     skip_forward=True)
 
 
 def main(config, args):
@@ -191,7 +186,7 @@ if __name__ == "__main__":
     parser.add_argument(
         "--export_path",
         type=str,
-        default='export',
+        default='export.jit.quant',
         help="path of the input audio file")
     args = parser.parse_args()
 

setup.py

@@ -75,7 +75,7 @@ base = [
     "braceexpand",
     "pyyaml",
     "pybind11",
-    "paddleslim==2.3.4",
+    "paddleslim==2.4.0",
 ]
 
 server = ["fastapi", "uvicorn", "pattern_singleton", "websockets"]