more fixes

microsoft · Nov 30, 2021 · e0c6970 · e0c6970
1 parent 60e84ef
commit e0c6970
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Showing 8 changed files with 11 additions and 11 deletions.
diff --git a/docs/python/inference/examples/plot_common_errors.py b/docs/python/inference/examples/plot_common_errors.py
@@ -21,7 +21,7 @@
 from onnxruntime.datasets import get_example
 
 example2 = get_example("logreg_iris.onnx")
-sess = rt.InferenceSession(example2)
+sess = rt.InferenceSession(example2, providers=rt.get_available_providers())
 
 input_name = sess.get_inputs()[0].name
 output_name = sess.get_outputs()[0].name

diff --git a/docs/python/inference/examples/plot_convert_pipeline_vectorizer.py b/docs/python/inference/examples/plot_convert_pipeline_vectorizer.py
@@ -72,7 +72,7 @@
 import onnxruntime as rt
 from onnxruntime.capi.onnxruntime_pybind11_state import InvalidArgument
 
-sess = rt.InferenceSession("pipeline_vectorize.onnx")
+sess = rt.InferenceSession("pipeline_vectorize.onnx", providers=rt.get_available_providers())
 
 import numpy
 inp, out = sess.get_inputs()[0], sess.get_outputs()[0]

diff --git a/docs/python/inference/examples/plot_load_and_predict.py b/docs/python/inference/examples/plot_load_and_predict.py
@@ -21,7 +21,7 @@
 # The model is available on github `onnx...test_sigmoid <https://github.com/onnx/onnx/tree/master/onnx/backend/test/data/node/test_sigmoid>`_.
 
 example1 = get_example("sigmoid.onnx")
-sess = rt.InferenceSession(example1)
+sess = rt.InferenceSession(example1, providers=rt.get_available_providers())
 
 #########################
 # Let's see the input name and shape.

diff --git a/docs/python/inference/examples/plot_profiling.py b/docs/python/inference/examples/plot_profiling.py
@@ -35,7 +35,7 @@ def change_ir_version(filename, ir_version=6):
 example1 = get_example("mul_1.onnx")
 onnx_model = change_ir_version(example1)
 onnx_model_str = onnx_model.SerializeToString()
-sess = rt.InferenceSession(onnx_model_str)
+sess = rt.InferenceSession(onnx_model_str, providers=rt.get_available_providers())
 input_name = sess.get_inputs()[0].name
 
 x = numpy.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=numpy.float32)
@@ -48,7 +48,7 @@ def change_ir_version(filename, ir_version=6):
 
 options = rt.SessionOptions()
 options.enable_profiling = True
-sess_profile = rt.InferenceSession(onnx_model_str, options)
+sess_profile = rt.InferenceSession(onnx_model_str, options, providers=rt.get_available_providers())
 input_name = sess.get_inputs()[0].name
 
 x = numpy.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=numpy.float32)

diff --git a/onnxruntime/test/python/onnxruntime_test_python_keras.py b/onnxruntime/test/python/onnxruntime_test_python_keras.py
@@ -68,7 +68,7 @@ def testRunModelConv(self):
 
         # runtime
         content = converted_model.SerializeToString()
-        rt = onnxrt.InferenceSession(content)
+        rt = onnxrt.InferenceSession(content, providers=onnxrt.get_available_providers())
         input = {rt.get_inputs()[0].name: x}
         actual_rt = rt.run(None, input)
         self.assertEqual(len(actual_rt), 1)

diff --git a/orttraining/tools/scripts/layer_norm_transform.py b/orttraining/tools/scripts/layer_norm_transform.py
@@ -163,11 +163,11 @@ def main():
     input_mask = np.ones((batch, sq_length), dtype=np.int64)
 
     # Do forward using the original model.
-    sess = ort.InferenceSession(model_file_path)
+    sess = ort.InferenceSession(model_file_path, providers=ort.get_available_providers())
     result = sess.run(None, {'input1': input_ids, 'input2': segment_ids, 'input3': input_mask})
 
     # Do forward using the new model.
-    new_sess = ort.InferenceSession(new_model_file_path)
+    new_sess = ort.InferenceSession(new_model_file_path, providers=ort.get_available_providers())
     new_result = new_sess.run(None, {'input1': input_ids, 'input2': segment_ids, 'input3': input_mask})
 
     # Compare the outcomes from the two models.

diff --git a/orttraining/tools/scripts/model_transform.py b/orttraining/tools/scripts/model_transform.py
@@ -298,11 +298,11 @@ def add_expand_shape(model):
 input_mask = np.ones((batch, sq_length), dtype=np.int64)
 
 # Do forward using the original model.
-sess = ort.InferenceSession(input_model_name)
+sess = ort.InferenceSession(input_model_name, providers=ort.get_available_providers())
 result = sess.run(None, {'input1': input_ids, 'input2': segment_ids, 'input3': input_mask})
 
 # Do forward using the new model.
-new_sess = ort.InferenceSession(output_model_name)
+new_sess = ort.InferenceSession(output_model_name, providers=ort.get_available_providers())
 new_result = new_sess.run(None, {'input1': input_ids, 'input2': segment_ids, 'input3': input_mask})
 
 # Compare the outcomes from the two models.

diff --git a/orttraining/tools/scripts/nv_run_pretraining.py b/orttraining/tools/scripts/nv_run_pretraining.py
@@ -528,7 +528,7 @@ def main():
                       is_model_exported = False
 
                       import onnxruntime as ort
-                      sess = ort.InferenceSession(onnx_path)
+                      sess = ort.InferenceSession(onnx_path, providers=ort.get_available_providers())
                       result = sess.run(None, {'input1': input_ids.cpu().numpy(), 'input2': segment_ids.cpu().numpy(), 'input3': input_mask.cpu().numpy()})
 
                       print('---ORT result---')