x2paddle/op_mapper/onnx2paddle/opset_legacy.py

@@ -1637,29 +1637,70 @@ class OpSet():
             "transpose_x": trans_a,
             "transpose_y": trans_b,
         }
-        self.paddle_graph.add_layer(
-            'paddle.matmul',
-            inputs=matmul_inputs,
-            outputs=[val_mm],
-            **attr_matmul)
-        self.paddle_graph.add_layer(
-            "paddle.scale", inputs={"x": val_mm}, outputs=[val_mm], scale=alpha)
-
-        if beta != 0:
-            if beta == 1.:
-                add_inputs = {"x": val_mm, "y": val_c.name}
+        if abs(alpha - 1.0) < 1e-5:
+            if abs(beta - 0.0) < 1e-5:
                 self.paddle_graph.add_layer(
-                    "paddle.add", inputs=add_inputs, outputs=[node.name])
+                    'paddle.matmul',
+                    inputs=matmul_inputs,
+                    outputs=[node.name],
+                    **attr_matmul)
             else:
-                var_beta = node.name + '_beta'
+                self.paddle_graph.add_layer(
+                    'paddle.matmul',
+                    inputs=matmul_inputs,
+                    outputs=[val_mm],
+                    **attr_matmul)
+                if abs(beta - 1.0) < 1e-5:
+                    add_inputs = {"x": val_mm, "y": val_c.name}
+                    self.paddle_graph.add_layer(
+                        "paddle.add", inputs=add_inputs, outputs=[node.name])
+                else:
+                    var_beta = node.name + '_beta'
+                    self.paddle_graph.add_layer(
+                        "paddle.scale",
+                        inputs={"x": val_c.name},
+                        outputs=[var_beta],
+                        scale=beta)
+                    add_inputs = {"x": val_mm, "y": var_beta}
+                    self.paddle_graph.add_layer(
+                        "paddle.add", inputs=add_inputs, outputs=[node.name])
+        else:
+            if abs(beta - 0.0) < 1e-5:
+                self.paddle_graph.add_layer(
+                    'paddle.matmul',
+                    inputs=matmul_inputs,
+                    outputs=[val_mm],
+                    **attr_matmul)
                 self.paddle_graph.add_layer(
                     "paddle.scale",
-                    inputs={"x": val_c.name},
-                    outputs=[var_beta],
-                    scale=beta)
-                add_inputs = {"x": val_mm, "y": var_beta}
+                    inputs={"x": val_mm},
+                    outputs=[node.name],
+                    scale=alpha)
+            else:
                 self.paddle_graph.add_layer(
-                    "paddle.add", inputs=add_inputs, outputs=[node.name])
+                    'paddle.matmul',
+                    inputs=[matmul_inputs],
+                    outputs=[val_mm],
+                    **attr_matmul)
+                self.paddle_graph.add_layer(
+                    "paddle.scale",
+                    inputs={"x": val_mm},
+                    outputs=[val_mm],
+                    scale=alpha)
+                if abs(beta - 1.0) < 1e-5:
+                    add_inputs = {"x": val_mm, "y": val_c.name}
+                    self.paddle_graph.add_layer(
+                        "paddle.add", inputs=add_inputs, outputs=[node.name])
+                else:
+                    var_beta = node.name + '_beta'
+                    self.paddle_graph.add_layer(
+                        "paddle.scale",
+                        inputs={"x": val_c.name},
+                        outputs=[var_beta],
+                        scale=beta)
+                    add_inputs = {"x": val_mm, "y": var_beta}
+                    self.paddle_graph.add_layer(
+                        "paddle.add", inputs=add_inputs, outputs=[node.name])
 
     @print_mapping_info
     def Sum(self, node):

x2paddle/project_convertor/pytorch/torch2paddle/io.py

@@ -169,7 +169,7 @@ class DataLoader(paddle.io.DataLoader):
             timeout=timeout,
             worker_init_fn=worker_init_fn)
         if sampler is not None:
-            seld.batch_sampler.sampler = sampler
+            self.batch_sampler.sampler = sampler
 
 
 class DistributedSampler(paddle.io.DistributedBatchSampler):