Update numpy version to latest (#1094)

* Update numpy version to latest

* Update problem line to use a helper that takes care of numpy raising ValueErrors when trying to convert ragged sequences

setup.py

@@ -85,7 +85,7 @@ def _parse_requirements_file(file_path):
 
 
 _deps = [
-    "numpy>=1.16.3,<=1.21.6",
+    "numpy>=1.16.3",
     "onnx>=1.5.0,<1.15.0",
     "pydantic>=1.8.2",
     "requests>=2.0.0",

src/deepsparse/transformers/pipelines/question_answering.py

@@ -250,6 +250,7 @@ def process_inputs(
         span_engine_inputs = []
         span_extra_info = []
         num_spans = len(tokenized_example["input_ids"])
+
         for span in range(num_spans):
             span_input = [
                 numpy.array(tokenized_example[key][span])
@@ -259,7 +260,7 @@ def process_inputs(
 
             span_extra_info.append(
                 {
-                    key: numpy.array(tokenized_example[key][span])
+                    key: _convert_to_numpy_array(tokenized_example[key][span])
                     for key in tokenized_example.keys()
                     if key not in self.onnx_input_names
                 }
@@ -583,3 +584,18 @@ def _save_predictions(self, all_predictions, all_nbest_json, scores_diff_json):
             mode = "a" if os.path.exists(null_odds_file) else "w"
             with open(null_odds_file, mode) as writer:
                 writer.write(json.dumps(scores_diff_json, indent=4) + "\n")
+
+
+def _convert_to_numpy_array(array):
+    """
+    Convert a list to a numpy array. If the list contains non-numeric values,
+    convert to an array of objects.
+
+    :param array: The list to convert
+    :return: The converted numpy array
+    """
+    try:
+        return numpy.array(array)
+    except ValueError:
+        # If the array contains non-numeric values, convert to an array of objects
+        return numpy.array(array, dtype=object)