Install onnxoptimizer

.github/scripts/audioset/AT/run.sh

@@ -2,6 +2,8 @@
 
 set -ex
 
+python3 -m pip install onnxoptimizer
+
 log() {
   # This function is from espnet
   local fname=${BASH_SOURCE[1]##*/}

.github/scripts/docker/Dockerfile

@@ -49,6 +49,7 @@ RUN pip install --no-cache-dir \
       multi_quantization \
       numba \
       numpy \
+      onnxoptimizer \
       onnx \
       onnxmltools \
       onnxruntime \

docker/torch1.12.1-cuda11.3.dockerfile

@@ -55,6 +55,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch1.13.0-cuda11.6.dockerfile

@@ -55,6 +55,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch1.9.0-cuda10.2.dockerfile

@@ -69,6 +69,7 @@ RUN pip uninstall -y tqdm && \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.0.0-cuda11.7.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.1.0-cuda11.8.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.1.0-cuda12.1.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.2.0-cuda11.8.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.2.0-cuda12.1.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.2.1-cuda11.8.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.2.1-cuda12.1.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.2.2-cuda11.8.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

docker/torch2.2.2-cuda12.1.dockerfile

@@ -56,6 +56,7 @@ RUN pip install --no-cache-dir \
       onnx \
       onnxruntime \
       onnxmltools \
+      onnxoptimizer \
       multi_quantization \
       typeguard \
       numpy \

egs/audioset/AT/zipformer/export-onnx.py

@@ -38,6 +38,7 @@ from typing import Dict
 
 import k2
 import onnx
+import onnxoptimizer
 import torch
 import torch.nn as nn
 from onnxruntime.quantization import QuantType, quantize_dynamic
@@ -234,12 +235,13 @@ def export_audio_tagging_model_onnx(
 
 
 def optimize_model(filename):
-    # see https://github.com/microsoft/onnxruntime/issues/1899#issuecomment-534806537
-    from onnx import optimizer
-
+    # see
+    # https://github.com/microsoft/onnxruntime/issues/1899#issuecomment-534806537
+    # and
+    # https://github.com/onnx/onnx/issues/582#issuecomment-937788108
     passes = ["extract_constant_to_initializer", "eliminate_unused_initializer"]
     onnx_model = onnx.load(filename)
-    optimized_model = optimizer.optimize(onnx_model, passes)
+    optimized_model = onnxoptimizer.optimize(onnx_model, passes)
     onnx.save(optimized_model, filename)
 
 

requirements.txt

@@ -8,8 +8,9 @@ pypinyin==0.50.0
 tensorboard
 typeguard
 dill
-onnx==1.15.0
-onnxruntime==1.16.3
+onnx>=1.15.0
+onnxruntime>=1.16.3
+onnxoptimizer
 
 # style check session:
 black==22.3.0