fix documentation

_doc/examples/plot_export_tiny_llm_dim01_onnx.py

@@ -128,7 +128,13 @@ def validation(ep, input_sets, expected, catch_exception=True):
         ep.model_proto.SerializeToString(), providers=["CPUExecutionProvider"]
     )
     for k, v in input_sets.items():
-        feeds = make_feeds(sess, torch_deepcopy(v), use_numpy=True)
+        try:
+            feeds = make_feeds(sess, torch_deepcopy(v), use_numpy=True)
+        except Exception as e:
+            if not catch_exception:
+                raise
+            yield k, e
+            continue
         try:
             got = sess.run(None, feeds)
         except Exception as e:

_doc/examples/plot_export_tiny_llm_dim01_onnx_custom.py

@@ -146,7 +146,13 @@ def validation(onx, input_sets, expected, catch_exception=True):
         onx.SerializeToString(), providers=["CPUExecutionProvider"]
     )
     for k, v in input_sets.items():
-        feeds = make_feeds(sess, torch_deepcopy(v), use_numpy=True)
+        try:
+            feeds = make_feeds(sess, torch_deepcopy(v), use_numpy=True)
+        except Exception as e:
+            if not catch_exception:
+                raise
+            yield k, e
+            continue
         try:
             got = sess.run(None, feeds)
         except Exception as e:

onnx_diagnostic/helpers/mini_onnx_builder.py

@@ -485,7 +485,7 @@ def _unflatten(
             try:
                 return pos + 1, torch.from_numpy(outputs[pos]).to(device)
             except TypeError:
-                # it shuold be more robusts
+                # it should be more robust
                 import ml_dtypes
 
                 if outputs[pos].dtype == ml_dtypes.bfloat16:
@@ -589,7 +589,7 @@ def create_input_tensors_from_onnx_model(
 
     See example :ref:`l-plot-intermediate-results` for an example.
 
-    .. code-bloc:: python
+    .. code-block:: python
 
         import os
         from onnx_diagnostic.helpers.mini_onnx_builder import (