Merge pull request #989 from zihaomu:qgemm_and_squeeze_opset13_onnximporter

testdata/dnn/onnx/data/README.md

+### OpenCV: Open Source Computer Vision Library
+
+This repository contains extra data for the OpenCV library.
+
+#### Resources
+* Homepage: http://opencv.org
+* Docs: http://docs.opencv.org
+* Q&A forum: https://forum.opencv.org
+  * previous forum (read only): http://answers.opencv.org
+* Issue tracking: https://github.com/opencv/opencv/issues
+
+#### Contributing
+
+Please read before starting work on a pull request: https://github.com/opencv/opencv/wiki/How_to_contribute
+
+Summary of guidelines:
+
+* One pull request per issue;
+* Choose the right base branch;
+* Include tests and documentation;
+* Clean up "oops" commits before submitting;
+* Follow the coding style guide.

testdata/dnn/onnx/generate_onnx_models.py

@@ -774,6 +774,7 @@ input = Variable(torch.randn(3, 1, 2, 4))
 model = Squeeze()
 model.eval()
 save_data_and_model("squeeze", input, model)
+save_data_and_model("squeeze_axes_op13", input, model, version=13)
 
 class Div(nn.Module):
 

testdata/dnn/onnx/generate_quantized_onnx_models.py

@@ -269,4 +269,13 @@ model = nn.Sequential(
                 nn.Linear(84, 10)
                 )
 input = Variable(torch.randn(1, 3, 32, 32))
-quantize_and_save_model("quantized_constant", input, model, wt_type="int8", per_channel=True)
\ No newline at end of file
+quantize_and_save_model("quantized_constant", input, model, wt_type="int8", per_channel=True)
+
+class Gemm(nn.Module):
+    def forward(self, x):
+        mat1 =torch.ones(3, 3)
+        return torch.mm(x, mat1)
+
+input = Variable(torch.randn(1, 3))
+model = Gemm()
+quantize_and_save_model("quantized_gemm", input, model, act_type="int8", wt_type="int8", per_channel=False)
\ No newline at end of file