Use relative import for all except main

hpvm/projects/onnx_frontend/frontend/codegen_hpvm.py

@@ -4,8 +4,8 @@ from typing import Dict, List, Tuple, Union
 
 import jinja2
 
-from graph_builder import DFG
-from graph_ir import DFGNode, TensorNode, WeightTensor
+from .graph_builder import DFG
+from .graph_ir import DFGNode, TensorNode, WeightTensor
 
 TEMPLATE_FILE = "template_hpvm.cpp"
 loader = jinja2.FileSystemLoader(searchpath=Path(__file__).parent)

hpvm/projects/onnx_frontend/frontend/codegen_tensor.py

@@ -3,8 +3,8 @@ from typing import Dict, List
 
 import jinja2
 
-from codegen_hpvm import CodeGen
-from graph_ir import DFGNode, TensorNode
+from .codegen_hpvm import CodeGen
+from .graph_ir import DFGNode, TensorNode
 
 TEMPLATE_FILE = "template_tensor.cpp"
 loader = jinja2.FileSystemLoader(searchpath=Path(__file__).parent)

hpvm/projects/onnx_frontend/frontend/graph_builder.py

@@ -6,8 +6,8 @@ from typing import Dict, Iterable, List, Optional, Tuple, Union
 import networkx as nx
 import onnx
 
-import graph_ir as g
-from onnx_attr import node_attr_to_dict
+from . import graph_ir as g
+from .onnx_attr import node_attr_to_dict
 
 GraphT = onnx.GraphProto
 NodeT = onnx.NodeProto

hpvm/projects/onnx_frontend/frontend/graph_ir.py

@@ -4,7 +4,7 @@ from typing import List, Tuple
 
 import onnx
 
-from onnx_attr import node_attr_to_dict
+from .onnx_attr import node_attr_to_dict
 
 
 class DFGNode(abc.ABC):

hpvm/projects/onnx_frontend/frontend/main.py → hpvm/projects/onnx_frontend/main.py

@@ -32,9 +32,9 @@ def compile(
     opset: Optional[int],
     hpvmc: bool,
 ):
-    from graph_builder import DFG
-    from codegen_tensor import TensorCodeGen
-    from codegen_hpvm import HpvmCodeGen
+    from frontend.graph_builder import DFG
+    from frontend.codegen_tensor import TensorCodeGen
+    from frontend.codegen_hpvm import HpvmCodeGen
 
     model = onnx.load(onnx_file)
     if opset is not None: