add Linear and NoOp ops to support more Kaldi Components(layers) (#660)

tools/python/transform/onnx_converter.py

@@ -108,6 +108,7 @@ OnnxSupportedOps = [
     'ImageScaler',
     # 'InstanceNormalization',
     # 'LRN',
+    'Linear',
     'LSTM',
     'LstmNonlinear',
     'LeakyRelu',
@@ -127,6 +128,7 @@ OnnxSupportedOps = [
     'Mul',
     # 'Multinomial',
     'Neg',
+    'NoOp',
     'Normalize',
     # 'Not',
     'Offset',
@@ -357,6 +359,7 @@ class OnnxConverter(base_converter.ConverterInterface):
             OnnxOpType.IfDefined.name: self.convert_ifdefined,
             OnnxOpType.ImageScaler.name: self.convert_imagescaler,
             OnnxOpType.LeakyRelu.name: self.convert_activation,
+            OnnxOpType.Linear.name: self.convert_affine,
             OnnxOpType.LogSoftmax.name: self.convert_softmax,
             OnnxOpType.LpNormalization: self.convert_lpnormalization,
             OnnxOpType.LstmNonlinear.name: self.convert_lstm_nonlinear,
@@ -367,6 +370,7 @@ class OnnxConverter(base_converter.ConverterInterface):
             OnnxOpType.Min.name: self.convert_eltwise,
             OnnxOpType.Mul.name: self.convert_eltwise,
             OnnxOpType.Neg.name: self.convert_eltwise,
+            OnnxOpType.NoOp.name: self.convert_identity,
             OnnxOpType.Normalize: self.convert_normalize,
             OnnxOpType.Offset.name: self.convert_subsample,
             OnnxOpType.Pad.name: self.convert_pad,