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use stable onnx.ir_version in test (#7747)

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Yufeng Li 2021-05-18 20:14:57 -07:00 committed by GitHub
parent 077e8c6b40
commit 75dbc2a35e
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GPG key ID: 4AEE18F83AFDEB23
12 changed files with 18 additions and 18 deletions
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4
onnxruntime/test/python/onnxruntime_test_python_nuphar.py
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@ -101,7 +101,7 @@ def generate_gemm_inputs_initializers(graph, config, added_inputs_initializers={
def generate_gemm_model(model_name, config):
model = onnx.ModelProto()
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
opset = model.opset_import.add()
opset.version = 11
@ -179,7 +179,7 @@ def generate_gemm_node_subgraph(scan_body, scan_node_inputs, postfix, config, ad
def generate_gemm_scan_model(model_name, config1, config2):
model = onnx.ModelProto()
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
opset = model.opset_import.add()
opset.version = 11

2
onnxruntime/test/python/quantization/test_op_gavgpool.py
View file

@ -69,7 +69,7 @@ class TestOpGlobalAveragePool(unittest.TestCase):
graph = helper.make_graph([gavgpool_node_1, expand_node, conv_node, gavgpool_node_2], graph_name,
[input_tensor], [output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)

2
onnxruntime/test/python/quantization/test_op_gemm.py
View file

@ -71,7 +71,7 @@ class TestOpGEMM(unittest.TestCase):
graph = helper.make_graph([gemm1_node, clip_node, gemm2_node], graph_name,
[input_tensor], [output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)

2
onnxruntime/test/python/quantization/test_op_maxpool.py
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@ -54,7 +54,7 @@ class TestOpMaxPool(unittest.TestCase):
graph = helper.make_graph([conv_node, identity_node, maxpool_node], 'TestOpQuantizerMaxPool_test_model',
[input_tensor], [identity_out, output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 12)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)
def test_quantize_maxpool(self):

4
onnxruntime/test/python/quantization/test_op_pad.py
View file

@ -51,7 +51,7 @@ class TestOpQuatizerPad(unittest.TestCase):
graph = helper.make_graph([pad_node], 'TestOpQuantizerPad_test_model',
[input_tensor], [output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)
@ -91,7 +91,7 @@ class TestOpQuatizerPad(unittest.TestCase):
graph = helper.make_graph([conv_node, identity_node, pad_node], 'TestOpQuantizerPad_test_model',
[input_tensor], [identity_out, output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)
def quantize_model(self, model_fp32_path, model_i8_path, data_reader=None):

2
onnxruntime/test/python/quantization/test_op_pooling.py
View file

@ -54,7 +54,7 @@ class TestOpAveragePool(unittest.TestCase):
graph = helper.make_graph([conv_node, identity_node, avgpool_node], 'TestOpQuantizerAveragePool_test_model',
[input_tensor], [identity_out, output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 12)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)
def test_quantize_avgpool(self):

2
onnxruntime/test/python/quantization/test_op_reshape.py
View file

@ -63,7 +63,7 @@ class TestOpReshape(unittest.TestCase):
graph = helper.make_graph([matmul_node, reshape_node], graph_name,
[input_tensor], [output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 11)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)

2
onnxruntime/test/python/quantization/test_op_resize.py
View file

@ -78,7 +78,7 @@ class TestOpResize(unittest.TestCase):
graph = helper.make_graph([conv_node, identity_node, resize_node], 'TestOpQuantizerResize_test_model',
[input_tensor], [identity_out, output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)
def test_quantize_resize(self):

2
onnxruntime/test/python/quantization/test_op_squeeze_unsqueeze.py
View file

@ -79,7 +79,7 @@ class TestOpSqueezeUnsqueeze(unittest.TestCase):
graph = helper.make_graph([conv1_node, conv2_node, conv3_node, squeeze1_node, squeeze2_node, add1_node, unsqueeze_node, add2_node],
'TestOpSuqeezes_test_model', [input_tensor], [output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", opset)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)
def run_quantize_squeezes_of_opset(self, opset = 13):

2
onnxruntime/test/python/quantization/test_op_transpose.py
View file

@ -58,7 +58,7 @@ class TestOpTranspose(unittest.TestCase):
graph = helper.make_graph([matmul_node, transpose_node], graph_name,
[input_tensor], [output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 11)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)

8
onnxruntime/test/python/quantization/test_qat.py
View file

@ -81,7 +81,7 @@ def generate_qat_model(model_names):
graph.initializer.add().CopyFrom(input_bias_1)
model_1 = onnx.helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model_1.ir_version = onnx.IR_VERSION
model_1.ir_version = 7 # use stable onnx ir version
onnx.save(model_1, model_names[0])
test_models.extend([model_1])
@ -153,7 +153,7 @@ def generate_qat_model(model_names):
graph.initializer.add().CopyFrom(conv_bias_1)
model_2 = onnx.helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model_2.ir_version = onnx.IR_VERSION
model_2.ir_version = 7 # use stable onnx ir version
onnx.save(model_2, model_names[1])
test_models.extend([model_2])
@ -202,7 +202,7 @@ def generate_qat_support_model(model_names, test_initializers):
graph.initializer.add().CopyFrom(init)
model_1 = onnx.ModelProto()
model_1.ir_version = onnx.IR_VERSION
model_1.ir_version = 7 # use stable onnx ir version
model_1 = onnx.helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
onnx.save(model_1, model_names[0])
@ -243,7 +243,7 @@ def generate_qat_support_model(model_names, test_initializers):
graph.initializer.add().CopyFrom(init)
model_2 = onnx.ModelProto()
model_2.ir_version = onnx.IR_VERSION
model_2.ir_version = 7 # use stable onnx ir version
model_2 = onnx.helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
onnx.save(model_1, model_names[1])

4
onnxruntime/test/python/quantization/test_qdq.py
View file

@ -56,7 +56,7 @@ class TestQDQFormatConv(TestQDQFormat):
graph = helper.make_graph([conv_node], graph_name,
[input_tensor], [output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)
@ -141,7 +141,7 @@ class TestQDQFormatConvClip(TestQDQFormat):
graph = helper.make_graph([conv_node, clip_node], graph_name,
[input_tensor], [output_tensor], initializer=initializers)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
model.ir_version = onnx.IR_VERSION
model.ir_version = 7 # use stable onnx ir version
onnx.save(model, output_model_path)