Merge branch 'fold' into 'master'

fix: Fix folding MatMul BiasAdd

See merge request applied-machine-learning/sysml/mace!1306

mace/ops/reshape.cc

@@ -169,7 +169,7 @@ void RegisterReshape(OpRegistry *op_registry) {
                          int has_data_format =
                              ProtoArgHelper::GetOptionalArg<OperatorDef, int>(
                                  *op, "has_data_format", 0);
-                         if (has_data_format) {
+                         if (has_data_format && op->input_size() == 1) {
                            return {DeviceType::CPU, DeviceType::GPU};
                          }
 
@@ -183,7 +183,8 @@ void RegisterReshape(OpRegistry *op_registry) {
                              op->output_shape(0).dims_size();
                          if (op_data_format == DataFormat::NHWC &&
                              4 == tensor_shape_info->at(input_0).size() &&
-                             (out_dims_size == 4 || out_dims_size == 2)) {
+                             (out_dims_size == 4 || out_dims_size == 2) &&
+                             op->input_size() == 1) {
                            return {DeviceType::CPU, DeviceType::GPU};
                          }
 

tools/python/transform/onnx_converter.py

@@ -604,8 +604,8 @@ class OnnxConverter(base_converter.ConverterInterface):
         for output in node.outputs:
             op.output.append(output)
             if with_shape:
+                output_shape = op.output_shape.add()
                 if output in self._graph_shapes_dict:
-                    output_shape = op.output_shape.add()
                     shape_info = self._graph_shapes_dict[output]
                     output_shape.dims.extend(shape_info)
 

tools/python/transform/transformer.py

@@ -867,7 +867,9 @@ class Transformer(base_converter.ConverterInterface):
             if (((op.type == MaceOp.Conv2D.name
                   or op.type == MaceOp.DepthwiseConv2d.name
                   or op.type == MaceOp.FullyConnected.name
-                  or op.type == MaceOp.MatMul.name)
+                  or (op.type == MaceOp.MatMul.name
+                      and self._option.device == DeviceType.CPU.value
+                      and not self._option.quantize))
                  and len(op.input) == 2)
                 or (op.type == MaceOp.Deconv2D.name
                     and ((ConverterUtil.get_arg(