docu

Author: xadupre

_doc/index.rst

@@ -117,12 +117,12 @@ See :func:`onnx_diagnostic.helpers.string_type`.
 onnx_dtype_name
 +++++++++++++++
 
-See :func:`onnx_diagnostic.helpers.onnx_dtype_name`.
+See :func:`onnx_diagnostic.helpers.onnx_helper.onnx_dtype_name`.
 
 .. code-block:: python
 
         import onnx
-        from onnx_diagnostic.helpers import onnx_dtype_name
+        from onnx_diagnostic.helpers.onnx_helper import onnx_dtype_name
 
         itype = onnx.TensorProto.BFLOAT16
         print(onnx_dtype_name(itype))

onnx_diagnostic/helpers/onnx_helper.py

@@ -834,7 +834,7 @@ def tensor_statistics(tensor: Union[np.ndarray, TensorProto]) -> Dict[str, Union
 
         import pprint
         import numpy as np
-        from onnx_diagnostic.helper.onnx_helper import tensor_statistics
+        from onnx_diagnostic.helpers.onnx_helper import tensor_statistics
 
         t = np.random.rand(40, 50).astype(np.float16)
         pprint.pprint(tensor_statistics(t))

onnx_diagnostic/helpers/torch_helper.py

@@ -102,8 +102,6 @@ def onnx_dtype_to_torch_dtype(itype: int) -> "torch.dtype":  # noqa: F821
     :param to: onnx dtype
     :return: torch dtype
     """
-    import torch
-
     if itype == onnx.TensorProto.FLOAT:
         return torch.float32
     if itype == onnx.TensorProto.FLOAT16:
@@ -314,6 +312,9 @@ def steal_forward(
 
         import torch
         from onnx_diagnostic.helpers.torch_helper import steal_forward
+        from onnx_diagnostic.helpers.mini_onnx_builder import (
+            create_input_tensors_from_onnx_model,
+        )
 
         class SubModel(torch.nn.Module):
             def forward(self, x):
@@ -363,7 +364,11 @@ def forward(self, x, y):
             for idx, m in model.named_modules():
                 level = str(idx).split(".")
                 ll = len(level)
-                _, start_line = inspect.getsourcelines(m.forward)
+                try:
+                    _, start_line = inspect.getsourcelines(m.forward)
+                except OSError:
+                    # The code is not available.
+                    start_line = 0
                 name = f"{idx}-{m.__class__.__name__}-{start_line}"
                 models.append((f"{'  ' * ll}{name}", m))
             model = models

onnx_diagnostic/torch_models/test_helper.py

@@ -780,7 +780,7 @@ def call_torch_export_export(
 
         disc = max_diff(data["expected"], expected)
         for k, v in disc.items():
-            summary[f"disc_exported_{k}"] = v
+            summary[f"disc_exported_{k}"] = str(v)
         if verbose:
             print("[validate_model] done (exported run)")
             print(f"[validate_model] exported discrepancies={string_diff(disc)}")