fix issues

Author: xadupre

_unittests/ut_light_api/test_backend_export.py

@@ -19,7 +19,11 @@
     make_opsetid,
     make_tensor_value_info,
 )
-from onnx.reference.op_run import to_array_extended
+
+try:
+    from onnx.reference.op_run import to_array_extended
+except ImportError:
+    from onnx.numpy_helper import to_array as to_array_extended
 from onnx.numpy_helper import from_array, to_array
 from onnx.backend.base import Device, DeviceType
 from onnx_array_api.reference import ExtendedReferenceEvaluator

onnx_array_api/profiling.py

@@ -438,7 +438,7 @@ def add_rows(rows, d):
             if verbose and fLOG is not None:
                 fLOG(
                     "[pstats] %s=%r"
-                    % ((clean_text(k[0].replace("\\", "/")),) + k[1:], v)
+                    % (clean_text(k[0].replace("\\", "/"), *k[1:]), v)
                 )
             if len(v) < 5:
                 continue

onnx_array_api/reference/__init__.py

@@ -2,13 +2,17 @@
 import numpy as np
 from onnx import TensorProto
 from onnx.numpy_helper import from_array as onnx_from_array
-from onnx.reference.ops.op_cast import (
-    bfloat16,
-    float8e4m3fn,
-    float8e4m3fnuz,
-    float8e5m2,
-    float8e5m2fnuz,
-)
+
+try:
+    from onnx.reference.ops.op_cast import (
+        bfloat16,
+        float8e4m3fn,
+        float8e4m3fnuz,
+        float8e5m2,
+        float8e5m2fnuz,
+    )
+except ImportError:
+    bfloat16 = None
 from onnx.reference.op_run import to_array_extended
 from .evaluator import ExtendedReferenceEvaluator
 from .evaluator_yield import (
@@ -28,6 +32,8 @@ def from_array_extended(tensor: np.array, name: Optional[str] = None) -> TensorP
     :param name: name
     :return: TensorProto
     """
+    if bfloat16 is None:
+        return onnx_from_array(tensor, name)
     dt = tensor.dtype
     if dt == float8e4m3fn and dt.descr[0][0] == "e4m3fn":
         to = TensorProto.FLOAT8E4M3FN

onnx_array_api/reference/ops/op_cast_like.py

@@ -1,17 +1,23 @@
 from onnx.helper import np_dtype_to_tensor_dtype
 from onnx.onnx_pb import TensorProto
 from onnx.reference.op_run import OpRun
-from onnx.reference.ops.op_cast import (
-    bfloat16,
-    cast_to,
-    float8e4m3fn,
-    float8e4m3fnuz,
-    float8e5m2,
-    float8e5m2fnuz,
-)
+from onnx.reference.ops.op_cast import cast_to
+
+try:
+    from onnx.reference.ops.op_cast import (
+        bfloat16,
+        float8e4m3fn,
+        float8e4m3fnuz,
+        float8e5m2,
+        float8e5m2fnuz,
+    )
+except ImportError:
+    bfloat16 = None
 
 
 def _cast_like(x, y, saturate):
+    if bfloat16 is None:
+        return (cast_to(x, y.dtype, saturate),)
     if y.dtype == bfloat16 and y.dtype.descr[0][0] == "bfloat16":
         # np.uint16 == np.uint16 is True as well as np.uint16 == bfloat16
         to = TensorProto.BFLOAT16