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[PyOV] clean up in tests (#19091)

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* [PyOV] clean up in tests

* use generated model in tests

* fix ci

* return back fild

* fix ci 1

* fix ci2

* update

* move models

* return back deleted test

* move model creation from conftest

* fix ci

* fix ci
This commit is contained in:
Anastasia Kuporosova authored and GitHub committed 2023-08-30 13:40:14 +02:00
1 parent b790458da6
commit 23cad1770e
23 files changed
+383 -357
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src/bindings/python/tests/conftest.py
+4 -63
View File
@@ -5,74 +5,15 @@
import os
import pytest
from sys import platform
from openvino.runtime import Core
def get_model_with_template_extension():
core = Core()
ir = bytes(b"""<net name="Activation" version="10">
<layers>
<layer name="in1" type="Parameter" id="0" version="opset1">
<data shape="1,3,22,22" element_type="f32"/>
<output>
<port id="0" precision="FP32" names="in_data">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</output>
</layer>
<layer name="activation" id="1" type="Identity" version="extension">
<input>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</input>
<output>
<port id="2" precision="FP32" names="out_data">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</output>
</layer>
<layer name="output" type="Result" id="2" version="opset1">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="1"/>
<edge from-layer="1" from-port="2" to-layer="2" to-port="0"/>
</edges>
</net>""")
if platform == "win32":
core.add_extension(library_path="openvino_template_extension.dll")
else:
core.add_extension(library_path="libopenvino_template_extension.so")
return core, core.read_model(ir)
def model_path(is_fp16=False):
base_path = os.path.dirname(__file__)
if is_fp16:
test_xml = os.path.join(base_path, "test_utils", "utils", "test_model_fp16.xml")
test_bin = os.path.join(base_path, "test_utils", "utils", "test_model_fp16.bin")
test_xml = os.path.join(base_path, "utils", "utils", "test_model_fp16.xml")
test_bin = os.path.join(base_path, "utils", "utils", "test_model_fp16.bin")
else:
test_xml = os.path.join(base_path, "test_utils", "utils", "test_model_fp32.xml")
test_bin = os.path.join(base_path, "test_utils", "utils", "test_model_fp32.bin")
test_xml = os.path.join(base_path, "utils", "utils", "test_model_fp32.xml")
test_bin = os.path.join(base_path, "utils", "utils", "test_model_fp32.bin")
return (test_xml, test_bin)
src/bindings/python/tests/test_graph/test_manager.py
+1 -1
View File
@@ -13,7 +13,7 @@ from openvino.runtime import Core, Model
from openvino.runtime.passes import Manager, Serialize, ConstantFolding, Version
from tests.test_graph.util import count_ops_of_type
from tests.test_utils.test_utils import create_filename_for_test, compare_models
from tests.utils.helpers import create_filename_for_test, compare_models
def create_model():
shape = [100, 100, 2]
src/bindings/python/tests/test_runtime/test_compiled_model.py
+19 -18
View File
@@ -2,17 +2,18 @@
# Copyright (C) 2018-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import os
import pytest
import numpy as np
from tests.conftest import model_path
from tests.test_utils.test_utils import get_relu_model, generate_image, generate_model_and_image, generate_relu_compiled_model
from openvino import Model, Shape, Core, Tensor
from tests.utils.helpers import (
get_relu_model,
generate_image,
generate_model_and_image,
generate_relu_compiled_model,
create_filename_for_test)
from openvino import Model, Shape, Core, Tensor, serialize
from openvino.runtime import ConstOutput
test_net_xml, test_net_bin = model_path()
def test_get_property(device):
model = get_relu_model([1, 3, 32, 32])
@@ -23,9 +24,7 @@ def test_get_property(device):
def test_get_runtime_model(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
compiled_model = core.compile_model(model, device)
compiled_model = generate_relu_compiled_model(device)
runtime_model = compiled_model.get_runtime_model()
assert isinstance(runtime_model, Model)
@@ -36,8 +35,7 @@ def test_export_import(device):
if "EXPORT_IMPORT" not in core.get_property(device, "OPTIMIZATION_CAPABILITIES"):
pytest.skip(f"{core.get_property(device, 'FULL_DEVICE_NAME')} plugin due-to export, import model API isn't implemented.")
model = core.read_model(model=test_net_xml, weights=test_net_bin)
compiled_model = core.compile_model(model, device)
compiled_model = generate_relu_compiled_model(device)
user_stream = compiled_model.export_model()
@@ -46,7 +44,7 @@ def test_export_import(device):
img = generate_image()
res = new_compiled.infer_new_request({"data": img})
assert np.argmax(res[new_compiled.outputs[0]]) == 9
assert np.argmax(res[new_compiled.outputs[0]]) == 531
def test_export_import_advanced(device):
@@ -57,8 +55,7 @@ def test_export_import_advanced(device):
if "EXPORT_IMPORT" not in core.get_property(device, "OPTIMIZATION_CAPABILITIES"):
pytest.skip(f"{core.get_property(device, 'FULL_DEVICE_NAME')} plugin due-to export, import model API isn't implemented.")
model = core.read_model(model=test_net_xml, weights=test_net_bin)
compiled_model = core.compile_model(model, device)
compiled_model = generate_relu_compiled_model(device)
user_stream = io.BytesIO()
@@ -69,7 +66,7 @@ def test_export_import_advanced(device):
img = generate_image()
res = new_compiled.infer_new_request({"data": img})
assert np.argmax(res[new_compiled.outputs[0]]) == 9
assert np.argmax(res[new_compiled.outputs[0]]) == 531
@pytest.mark.parametrize("input_arguments", [[0], ["data"], []])
@@ -222,11 +219,15 @@ def test_direct_infer(device, shared_flag):
assert np.array_equal(ref[compiled_model.outputs[0]], res[compiled_model.outputs[0]])
def test_compiled_model_after_core_destroyed(device):
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_compiled_model_after_core_destroyed(request, tmp_path, device):
core = Core()
with open(test_net_bin, "rb") as f:
xml_path, bin_path = create_filename_for_test(request.node.name, tmp_path)
model = get_relu_model()
serialize(model, xml_path, bin_path)
with open(bin_path, "rb") as f:
weights = f.read()
with open(test_net_xml, "rb") as f:
with open(xml_path, "rb") as f:
xml = f.read()
model = core.read_model(model=xml, weights=weights)
compiled = core.compile_model(model, device)
src/bindings/python/tests/test_runtime/test_core.py
+67 -52
View File
@@ -16,29 +16,21 @@ from openvino import (
CompiledModel,
tensor_from_file,
compile_model,
serialize,
)
from openvino.runtime import Extension
from tests.conftest import (
model_path,
model_onnx_path,
get_model_with_template_extension,
)
from tests.test_utils.test_utils import (
from tests.utils.helpers import (
generate_image,
generate_relu_compiled_model,
get_relu_model,
plugins_path,
compare_models,
create_filename_for_test,
get_model_with_template_extension,
)
test_net_xml, test_net_bin = model_path()
test_net_onnx = model_onnx_path()
def test_compact_api_xml():
img = generate_image()
@@ -48,8 +40,12 @@ def test_compact_api_xml():
assert np.argmax(results[list(results)[0]]) == 531
def test_compact_api_xml_posix_path():
compiled_model = compile_model(Path(test_net_xml))
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_compact_api_xml_posix_path(request, tmp_path):
xml_path, _ = create_filename_for_test(request.node.name, tmp_path, True)
model = get_relu_model()
serialize(model, xml_path)
compiled_model = compile_model(Path(xml_path))
assert isinstance(compiled_model, CompiledModel)
@@ -80,33 +76,51 @@ def test_core_class(device):
assert np.allclose(results[list(results)[0]], expected_output)
def test_compile_model(device):
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_compile_model(request, tmp_path, device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
xml_path, bin_path = create_filename_for_test(request.node.name, tmp_path)
relu_model = get_relu_model()
serialize(relu_model, xml_path, bin_path)
model = core.read_model(model=xml_path, weights=bin_path)
compiled_model = core.compile_model(model, device)
assert isinstance(compiled_model, CompiledModel)
def test_compile_model_without_device():
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_compile_model_without_device(request, tmp_path):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
xml_path, bin_path = create_filename_for_test(request.node.name, tmp_path)
relu_model = get_relu_model()
serialize(relu_model, xml_path, bin_path)
model = core.read_model(model=xml_path, weights=bin_path)
compiled_model = core.compile_model(model)
assert isinstance(compiled_model, CompiledModel)
def test_read_model_from_ir():
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_read_model_from_ir(request, tmp_path):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
xml_path, bin_path = create_filename_for_test(request.node.name, tmp_path)
relu_model = get_relu_model()
serialize(relu_model, xml_path, bin_path)
model = core.read_model(model=xml_path, weights=bin_path)
assert isinstance(model, Model)
model = core.read_model(model=test_net_xml)
model = core.read_model(model=xml_path)
assert isinstance(model, Model)
def test_read_model_from_tensor():
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_read_model_from_tensor(request, tmp_path):
core = Core()
model = open(test_net_xml).read()
tensor = tensor_from_file(test_net_bin)
xml_path, bin_path = create_filename_for_test(request.node.name, tmp_path, is_xml_path=True, is_bin_path=True)
relu_model = get_relu_model()
serialize(relu_model, xml_path, bin_path)
arr = np.ones(shape=(10), dtype=np.int8)
arr.tofile(bin_path)
model = open(xml_path).read()
tensor = tensor_from_file(bin_path)
model = core.read_model(model=model, weights=tensor)
assert isinstance(model, Model)
@@ -118,48 +132,49 @@ def test_read_model_with_wrong_input():
assert "Provided python object type <class 'int'> isn't supported as 'model' argument." in str(e.value)
def test_read_model_as_path():
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_read_model_as_path(request, tmp_path):
core = Core()
model = core.read_model(model=Path(test_net_xml), weights=Path(test_net_bin))
xml_path, bin_path = create_filename_for_test(request.node.name, tmp_path, True, True)
relu_model = get_relu_model()
serialize(relu_model, xml_path, bin_path)
model = core.read_model(model=Path(xml_path), weights=Path(bin_path))
assert isinstance(model, Model)
model = core.read_model(model=test_net_xml, weights=Path(test_net_bin))
model = core.read_model(model=xml_path, weights=Path(bin_path))
assert isinstance(model, Model)
model = core.read_model(model=Path(test_net_xml))
model = core.read_model(model=Path(xml_path))
assert isinstance(model, Model)
def test_read_model_from_onnx():
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_read_model_from_buffer(request, tmp_path):
core = Core()
model = core.read_model(model=test_net_onnx)
assert isinstance(model, Model)
def test_read_model_from_onnx_as_path():
core = Core()
model = core.read_model(model=Path(test_net_onnx))
assert isinstance(model, Model)
def test_read_model_from_buffer():
core = Core()
with open(test_net_bin, "rb") as f:
xml_path, bin_path = create_filename_for_test(request.node.name, tmp_path)
relu_model = get_relu_model()
serialize(relu_model, xml_path, bin_path)
with open(bin_path, "rb") as f:
weights = f.read()
with open(model_path()[0], "rb") as f:
with open(xml_path, "rb") as f:
xml = f.read()
model = core.read_model(model=xml, weights=weights)
assert isinstance(model, Model)
def test_model_from_buffer_valid():
# request - https://docs.pytest.org/en/7.1.x/reference/reference.html#request
def test_model_from_buffer_valid(request, tmp_path):
core = Core()
with open(test_net_bin, "rb") as f:
xml_path, bin_path = create_filename_for_test(request.node.name, tmp_path)
relu_model = get_relu_model()
serialize(relu_model, xml_path, bin_path)
with open(bin_path, "rb") as f:
weights = f.read()
with open(model_path()[0], "rb") as f:
with open(xml_path, "rb") as f:
xml = f.read()
model = core.read_model(model=xml, weights=weights)
ref_model = core.read_model(model=test_net_xml, weights=test_net_bin)
ref_model = core.read_model(model=xml_path, weights=bin_path)
assert compare_models(model, ref_model)
@@ -255,7 +270,7 @@ def test_get_property_str():
def test_query_model(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
query_model = core.query_model(model=model, device_name=device)
ops_model = model.get_ordered_ops()
ops_func_names = [op.friendly_name for op in ops_model]
@@ -326,7 +341,7 @@ def test_add_extension():
core = Core()
core.add_extension(EmptyExtension())
core.add_extension([EmptyExtension(), EmptyExtension()])
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
assert isinstance(model, Model)
@@ -398,7 +413,7 @@ def test_read_model_from_buffer_no_weights():
def test_infer_new_request_return_type(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
img = generate_image()
compiled_model = core.compile_model(model, device)
res = compiled_model.infer_new_request({"data": img})
@@ -406,6 +421,6 @@ def test_infer_new_request_return_type(device):
assert isinstance(arr, np.ndarray)
assert arr.itemsize == 4
assert arr.shape == (10,)
assert arr.shape == (3, 32, 32)
assert arr.dtype == "float32"
assert arr.nbytes == 40
assert arr.nbytes == 12288
src/bindings/python/tests/test_runtime/test_infer_request.py
+21 -15
View File
@@ -27,10 +27,7 @@ from openvino.runtime import ProfilingInfo
from openvino.preprocess import PrePostProcessor
from tests import skip_need_mock_op
from tests.conftest import model_path
from tests.test_utils.test_utils import generate_image, get_relu_model
test_net_xml, test_net_bin = model_path()
from tests.utils.helpers import generate_image, get_relu_model
def create_model_with_memory(input_shape, data_type):
@@ -100,7 +97,10 @@ def abs_model_with_data(device, ov_type, numpy_dtype):
def test_get_profiling_info(device):
core = Core()
model = core.read_model(test_net_xml, test_net_bin)
param = ops.parameter([1, 3, 32, 32], np.float32, name="data")
softmax = ops.softmax(param, 1, name="fc_out")
model = Model([softmax], [param], "test_model")
core.set_property(device, {"PERF_COUNT": "YES"})
compiled_model = core.compile_model(model, device)
img = generate_image()
@@ -164,22 +164,28 @@ def test_tensor_setter(device):
def test_set_tensors(device):
core = Core()
model = core.read_model(test_net_xml, test_net_bin)
param = ops.parameter([1, 3, 32, 32], np.float32, name="data")
softmax = ops.softmax(param, 1, name="fc_out")
res = ops.result(softmax, name="res")
res.output(0).get_tensor().set_names({"res"})
model = Model([res], [param], "test_model")
compiled_model = core.compile_model(model, device)
data1 = generate_image()
tensor1 = Tensor(data1)
data2 = np.ones(shape=(1, 10), dtype=np.float32)
data2 = np.ones(shape=(1, 3, 32, 32), dtype=np.float32)
tensor2 = Tensor(data2)
data3 = np.ones(shape=(1, 3, 32, 32), dtype=np.float32)
tensor3 = Tensor(data3)
data4 = np.zeros(shape=(1, 10), dtype=np.float32)
data4 = np.zeros(shape=(1, 3, 32, 32), dtype=np.float32)
tensor4 = Tensor(data4)
request = compiled_model.create_infer_request()
request.set_tensors({"data": tensor1, "fc_out": tensor2})
request.set_tensors({"data": tensor1, "res": tensor2})
t1 = request.get_tensor("data")
t2 = request.get_tensor("fc_out")
t2 = request.get_tensor("res")
assert np.allclose(tensor1.data, t1.data, atol=1e-2, rtol=1e-2)
assert np.allclose(tensor2.data, t2.data, atol=1e-2, rtol=1e-2)
@@ -295,7 +301,7 @@ def test_inputs_outputs_property_and_method(device):
@pytest.mark.skip(reason="Sporadically failed. Need further investigation. Ticket - 95967")
def test_cancel(device):
core = Core()
model = core.read_model(test_net_xml, test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
img = generate_image()
request = compiled_model.create_infer_request()
@@ -316,7 +322,7 @@ def test_cancel(device):
@pytest.mark.parametrize("share_inputs", [True, False])
def test_start_async(device, share_inputs):
core = Core()
model = core.read_model(test_net_xml, test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
img = generate_image()
jobs = 3
@@ -482,7 +488,7 @@ def test_infer_queue(device, share_inputs):
jobs = 8
num_request = 4
core = Core()
model = core.read_model(test_net_xml, test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
infer_queue = AsyncInferQueue(compiled_model, num_request)
jobs_done = [{"finished": False, "latency": 0} for _ in range(jobs)]
@@ -563,7 +569,7 @@ def test_infer_queue_fail_on_cpp_model(device):
jobs = 6
num_request = 4
core = Core()
model = core.read_model(test_net_xml, test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
infer_queue = AsyncInferQueue(compiled_model, num_request)
@@ -585,7 +591,7 @@ def test_infer_queue_fail_on_py_model(device):
jobs = 1
num_request = 1
core = Core()
model = core.read_model(test_net_xml, test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
infer_queue = AsyncInferQueue(compiled_model, num_request)
src/bindings/python/tests/test_runtime/test_input_node.py
+15 -17
View File
@@ -4,19 +4,17 @@
import os
from ..conftest import model_path
from openvino.runtime import Input, RTMap
from openvino._pyopenvino import DescriptorTensor
import openvino.runtime.opset12 as ops
from openvino import Core, OVAny, Shape, PartialShape, Type
test_net_xml, test_net_bin = model_path()
from tests.utils.helpers import get_relu_model
def test_input_type(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
@@ -25,7 +23,7 @@ def test_input_type(device):
def test_const_output_docs(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
@@ -35,7 +33,7 @@ def test_const_output_docs(device):
def test_input_get_index(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
@@ -44,7 +42,7 @@ def test_input_get_index(device):
def test_input_element_type(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
@@ -53,36 +51,36 @@ def test_input_element_type(device):
def test_input_get_shape(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
assert str(input_node.get_shape()) == str(Shape([1, 10]))
assert str(input_node.get_shape()) == str(Shape([1, 3, 32, 32]))
def test_input_get_partial_shape(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
expected_partial_shape = PartialShape([1, 10])
expected_partial_shape = PartialShape([1, 3, 32, 32])
assert input_node.get_partial_shape() == expected_partial_shape
def test_input_get_source_output(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
name = input_node.get_source_output().get_node().get_friendly_name()
assert name == "fc_out"
assert name == "relu"
def test_input_get_tensor(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
@@ -92,7 +90,7 @@ def test_input_get_tensor(device):
def test_input_get_rt_info(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
@@ -102,7 +100,7 @@ def test_input_get_rt_info(device):
def test_input_rt_info(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
@@ -126,7 +124,7 @@ def test_input_replace_source_output(device):
def test_input_update_rt_info(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
net_input = compiled_model.output(0)
input_node = net_input.get_node().inputs()[0]
src/bindings/python/tests/test_runtime/test_memory_modes.py
+1 -1
View File
@@ -9,7 +9,7 @@ import openvino.runtime as ov
from openvino import Tensor
from openvino.runtime.op import Constant
from tests.test_utils.test_utils import generate_image
from tests.utils.helpers import generate_image
@pytest.mark.parametrize(("cls", "cls_str"), [
src/bindings/python/tests/test_runtime/test_model.py
+1 -1
View File
@@ -23,7 +23,7 @@ from openvino import (
)
from openvino.runtime import Output
from tests.test_utils.test_utils import generate_add_model, create_filename_for_test
from tests.utils.helpers import generate_add_model, create_filename_for_test
def test_test_descriptor_tensor():
src/bindings/python/tests/test_runtime/test_output_const_node.py
+12 -16
View File
@@ -3,9 +3,9 @@
# SPDX-License-Identifier: Apache-2.0
import os
import pytest
from copy import copy, deepcopy
from ..conftest import model_path
import openvino.runtime.opset12 as ops
from openvino import (
Shape,
@@ -19,16 +19,12 @@ from openvino.runtime import (
Output,
RTMap,
)
import pytest
test_net_xml, test_net_bin = model_path()
from tests.utils.helpers import get_relu_model
def test_const_output_type(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
node = compiled_model.input(0)
assert isinstance(node, ConstOutput)
@@ -36,7 +32,7 @@ def test_const_output_type(device):
def test_const_output_docs(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
node = compiled_model.input(0)
exptected_string = "openvino.runtime.ConstOutput represents port/node output."
@@ -45,7 +41,7 @@ def test_const_output_docs(device):
def test_const_output_get_index(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
node = compiled_model.input("data")
assert node.get_index() == 0
@@ -54,7 +50,7 @@ def test_const_output_get_index(device):
def test_const_output_get_element_type(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
node = compiled_model.input("data")
assert node.get_element_type() == Type.f32
@@ -63,7 +59,7 @@ def test_const_output_get_element_type(device):
def test_const_output_get_shape(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
node = compiled_model.input("data")
expected_shape = Shape([1, 3, 32, 32])
@@ -73,7 +69,7 @@ def test_const_output_get_shape(device):
def test_const_output_get_partial_shape(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
exec_net = core.compile_model(model, device)
node = exec_net.input("data")
expected_partial_shape = PartialShape([1, 3, 32, 32])
@@ -83,7 +79,7 @@ def test_const_output_get_partial_shape(device):
def test_const_output_get_target_inputs(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
outputs = compiled_model.outputs
for node in outputs:
@@ -93,7 +89,7 @@ def test_const_output_get_target_inputs(device):
def test_const_output_get_names(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
input_name = "data"
node = compiled_model.input(input_name)
@@ -107,7 +103,7 @@ def test_const_output_get_names(device):
def test_const_get_rf_info(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
output_node = compiled_model.output(0)
rt_info = output_node.get_rt_info()
@@ -116,7 +112,7 @@ def test_const_get_rf_info(device):
def test_const_output_runtime_info(device):
core = Core()
model = core.read_model(model=test_net_xml, weights=test_net_bin)
model = get_relu_model()
compiled_model = core.compile_model(model, device)
input_name = "data"
output_node = compiled_model.input(input_name)
src/bindings/python/tests/test_runtime/test_output_node.py
-1
View File
@@ -4,7 +4,6 @@
import os
from ..conftest import model_path
import openvino.runtime.opset12 as ops
from openvino import Type
src/bindings/python/tests/test_runtime/test_properties.py
+1 -1
View File
@@ -442,7 +442,7 @@ def test_properties_capability_gpu():
def test_properties_hint_model():
# Temporary imports
from tests.test_utils.test_utils import generate_add_model
from tests.utils.helpers import generate_add_model
model = generate_add_model()
src/bindings/python/tests/test_runtime/test_tensor.py
+1 -1
View File
@@ -15,7 +15,7 @@ from openvino.helpers import pack_data, unpack_data
import pytest
from tests.test_utils.test_utils import generate_image, generate_relu_compiled_model
from tests.utils.helpers import generate_image, generate_relu_compiled_model
@pytest.mark.parametrize(("ov_type", "numpy_dtype"), [
src/bindings/python/tests/test_transformations/test_compression.py
+1 -1
View File
@@ -9,7 +9,7 @@ from openvino.runtime.op import Parameter, Constant
from openvino.runtime.opset12 import add, multiply
import openvino as ov
from tests.test_utils.test_utils import create_filename_for_test
from tests.utils.helpers import create_filename_for_test
def make_constant(values, transposed):
src/bindings/python/tests/test_transformations/test_offline_api.py
+1 -1
View File
@@ -19,7 +19,7 @@ from openvino._offline_transformations import (
from openvino.runtime import Model, PartialShape, Core, serialize, save_model
import openvino.runtime as ov
from tests.test_utils.test_utils import create_filename_for_test, compare_models, _compare_models
from tests.utils.helpers import create_filename_for_test, compare_models, _compare_models
def get_relu_model():
src/bindings/python/tests/test_transformations/test_public_transformations.py
+1 -1
View File
@@ -17,7 +17,7 @@ from openvino.runtime.passes import (
)
from tests.test_transformations.utils.utils import count_ops, get_relu_model
from tests.test_utils.test_utils import create_filename_for_test, compare_models
from tests.utils.helpers import create_filename_for_test, compare_models
def get_model():
src/bindings/python/tests/test_utils/test_data_dispatch.py
+1 -3
View File
@@ -6,13 +6,11 @@ import os
import pytest
import numpy as np
from tests.conftest import model_path
from tests.test_utils.test_utils import generate_relu_compiled_model
from tests.utils.helpers import generate_relu_compiled_model
from openvino.runtime import Model, ConstOutput, Type, Shape, Core, Tensor
from openvino.runtime.utils.data_helpers import _data_dispatch
is_myriad = os.environ.get("TEST_DEVICE") == "MYRIAD"
test_net_xml, test_net_bin = model_path(is_myriad)
def _get_value(value):
src/bindings/python/tests/test_utils/test_utils.py
+9 -164
View File
@@ -2,99 +2,19 @@
# Copyright (C) 2018-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from typing import Tuple, Union, List
import os
import sys
import numpy as np
import pytest
from pathlib import Path
import openvino
import openvino.runtime.opset12 as ops
from openvino.runtime import Model, Core, Shape
from openvino.utils import deprecated
from tests.utils.helpers import compare_models, get_relu_model
def _compare_models(model_one: Model, model_two: Model, compare_names: bool = True) -> Tuple[bool, str]: # noqa: C901 the function is too complex
"""Function to compare OpenVINO model (ops names, types and shapes).
Note that the functions uses get_ordered_ops, so the topological order of ops should be also preserved.
:param model_one: The first model to compare.
:param model_two: The second model to compare.
:param compare_names: Flag to control friendly names checking. Default: True
:return: Tuple which consists of bool value (True if models are equal, otherwise False)
and string with the message to reuse for debug/testing purposes. The string value
is empty when models are equal.
"""
result = True
msg = ""
# Check friendly names of models
if compare_names and model_one.get_friendly_name() != model_two.get_friendly_name():
result = False
msg += "Friendly names of models are not equal "
msg += f"model_one: {model_one.get_friendly_name()}, model_two: {model_two.get_friendly_name()}.\n"
model_one_ops = model_one.get_ordered_ops()
model_two_ops = model_two.get_ordered_ops()
# Check overall number of operators
if len(model_one_ops) != len(model_two_ops):
result = False
msg += "Not equal number of ops "
msg += f"model_one: {len(model_one_ops)}, model_two: {len(model_two_ops)}.\n"
for i in range(len(model_one_ops)):
op_one_name = model_one_ops[i].get_friendly_name() # op from model_one
op_two_name = model_two_ops[i].get_friendly_name() # op from model_two
# Check friendly names
if (compare_names and op_one_name != op_two_name and model_one_ops[i].get_type_name() != "Constant"):
result = False
msg += "Not equal op names "
msg += f"model_one: {op_one_name}, "
msg += f"model_two: {op_two_name}.\n"
# Check output sizes
if model_one_ops[i].get_output_size() != model_two_ops[i].get_output_size():
result = False
msg += f"Not equal output sizes of {op_one_name} and {op_two_name}.\n"
for idx in range(model_one_ops[i].get_output_size()):
# Check partial shapes of outputs
op_one_partial_shape = model_one_ops[i].get_output_partial_shape(idx)
op_two_partial_shape = model_two_ops[i].get_output_partial_shape(idx)
if op_one_partial_shape != op_two_partial_shape:
result = False
msg += f"Not equal op partial shapes of {op_one_name} and {op_two_name} on {idx} index "
msg += f"model_one: {op_one_partial_shape}, "
msg += f"model_two: {op_two_partial_shape}.\n"
# Check element types of outputs
op_one_element_type = model_one_ops[i].get_output_element_type(idx)
op_two_element_type = model_two_ops[i].get_output_element_type(idx)
if op_one_element_type != op_two_element_type:
result = False
msg += f"Not equal output element types of {op_one_name} and {op_two_name} on {idx} index "
msg += f"model_one: {op_one_element_type}, "
msg += f"model_two: {op_two_element_type}.\n"
return result, msg
def compare_models(model_one: Model, model_two: Model, compare_names: bool = True):
"""Function to compare OpenVINO model (ops names, types and shapes).
:param model_one: The first model to compare.
:param model_two: The second model to compare.
:param compare_names: Flag to control friendly names checking. Default: True
:return: True if models are equal, otherwise raise an error with a report of mismatches.
"""
result, msg = _compare_models(model_one, model_two, compare_names=compare_names)
if not result:
raise RuntimeError(msg)
return result
def test_compare_functions():
try:
from openvino.test_utils import compare_functions
model = get_relu_model()
status, _ = compare_functions(model, model)
assert status
except RuntimeError:
print("openvino.test_utils.compare_functions is not available") # noqa: T201
def test_compare_models_pass():
@@ -113,63 +33,6 @@ def test_compare_models_fail():
assert "Not equal op names model_one: data, model_two: ABC." in str(e.value)
def plugins_path(device, lib_path):
plugin_xml = f"""<ie>
<plugins>
<plugin location="{lib_path}" name="{device}">
</plugin>
</plugins>
</ie>"""
with open("plugin_path.xml", "w") as f:
f.write(plugin_xml)
plugins_paths = os.path.join(os.getcwd(), "plugin_path.xml")
return plugins_paths
def generate_image(shape: Tuple = (1, 3, 32, 32), dtype: Union[str, np.dtype] = "float32") -> np.array:
np.random.seed(42)
return np.random.rand(*shape).astype(dtype)
def get_relu_model(input_shape: List[int] = None, input_dtype=np.float32) -> openvino.runtime.Model:
if input_shape is None:
input_shape = [1, 3, 32, 32]
param = ops.parameter(input_shape, input_dtype, name="data")
relu = ops.relu(param, name="relu")
model = Model([relu], [param], "test_model")
model.get_ordered_ops()[2].friendly_name = "friendly"
assert model is not None
return model
def generate_relu_compiled_model(
device,
input_shape: List[int] = None,
input_dtype=np.float32,
) -> openvino.runtime.CompiledModel:
if input_shape is None:
input_shape = [1, 3, 32, 32]
model = get_relu_model(input_shape, input_dtype)
core = Core()
return core.compile_model(model, device, {})
def generate_model_and_image(device, input_shape: List[int] = None):
if input_shape is None:
input_shape = [1, 3, 32, 32]
return (generate_relu_compiled_model(device, input_shape), generate_image(input_shape))
def generate_add_model() -> openvino._pyopenvino.Model:
param1 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data1")
param2 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data2")
add = ops.add(param1, param2)
return Model(add, [param1, param2], "TestFunction")
def test_deprecation_decorator():
@deprecated()
def deprecated_function1(param1, param2=None):
@@ -195,21 +58,3 @@ def test_deprecation_decorator():
deprecated_function3()
with pytest.warns(DeprecationWarning, match="deprecated_function4 is deprecated and will be removed in version 2025.4. Use another function instead"):
deprecated_function4()
def create_filename_for_test(test_name, tmp_path, is_xml_path=False, is_bin_path=False):
"""Return a tuple with automatically generated paths for xml and bin files.
:param test_name: Name used in generating.
:param is_xml_path: True if xml file should be pathlib.Path object, otherwise return string.
:param is_bin_path: True if bin file should be pathlib.Path object, otherwise return string.
:return: Tuple with two objects representing xml and bin files.
"""
python_version = str(sys.version_info.major) + "_" + str(sys.version_info.minor)
filename = test_name.replace("test_", "").replace("[", "_").replace("]", "_")
filename = filename + "_" + python_version
path_to_xml = tmp_path / Path(filename + ".xml")
path_to_bin = tmp_path / Path(filename + ".bin")
_xml = path_to_xml if is_xml_path else str(path_to_xml)
_bin = path_to_bin if is_bin_path else str(path_to_bin)
return (_xml, _bin)
src/bindings/python/tests/utils/helpers.py
+227
View File
@@ -0,0 +1,227 @@
# -*- coding: utf-8 -*-
# Copyright (C) 2018-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from typing import Tuple, Union, List
import os
import sys
import numpy as np
from sys import platform
from pathlib import Path
import openvino
import openvino.runtime.opset12 as ops
from openvino.runtime import Model, Core, Shape
def _compare_models(model_one: Model, model_two: Model, compare_names: bool = True) -> Tuple[bool, str]: # noqa: C901 the function is too complex
"""Function to compare OpenVINO model (ops names, types and shapes).
Note that the functions uses get_ordered_ops, so the topological order of ops should be also preserved.
:param model_one: The first model to compare.
:param model_two: The second model to compare.
:param compare_names: Flag to control friendly names checking. Default: True
:return: Tuple which consists of bool value (True if models are equal, otherwise False)
and string with the message to reuse for debug/testing purposes. The string value
is empty when models are equal.
"""
result = True
msg = ""
# Check friendly names of models
if compare_names and model_one.get_friendly_name() != model_two.get_friendly_name():
result = False
msg += "Friendly names of models are not equal "
msg += f"model_one: {model_one.get_friendly_name()}, model_two: {model_two.get_friendly_name()}.\n"
model_one_ops = model_one.get_ordered_ops()
model_two_ops = model_two.get_ordered_ops()
# Check overall number of operators
if len(model_one_ops) != len(model_two_ops):
result = False
msg += "Not equal number of ops "
msg += f"model_one: {len(model_one_ops)}, model_two: {len(model_two_ops)}.\n"
for i in range(len(model_one_ops)):
op_one_name = model_one_ops[i].get_friendly_name() # op from model_one
op_two_name = model_two_ops[i].get_friendly_name() # op from model_two
# Check friendly names
if (compare_names and op_one_name != op_two_name and model_one_ops[i].get_type_name() != "Constant"):
result = False
msg += "Not equal op names "
msg += f"model_one: {op_one_name}, "
msg += f"model_two: {op_two_name}.\n"
# Check output sizes
if model_one_ops[i].get_output_size() != model_two_ops[i].get_output_size():
result = False
msg += f"Not equal output sizes of {op_one_name} and {op_two_name}.\n"
for idx in range(model_one_ops[i].get_output_size()):
# Check partial shapes of outputs
op_one_partial_shape = model_one_ops[i].get_output_partial_shape(idx)
op_two_partial_shape = model_two_ops[i].get_output_partial_shape(idx)
if op_one_partial_shape != op_two_partial_shape:
result = False
msg += f"Not equal op partial shapes of {op_one_name} and {op_two_name} on {idx} index "
msg += f"model_one: {op_one_partial_shape}, "
msg += f"model_two: {op_two_partial_shape}.\n"
# Check element types of outputs
op_one_element_type = model_one_ops[i].get_output_element_type(idx)
op_two_element_type = model_two_ops[i].get_output_element_type(idx)
if op_one_element_type != op_two_element_type:
result = False
msg += f"Not equal output element types of {op_one_name} and {op_two_name} on {idx} index "
msg += f"model_one: {op_one_element_type}, "
msg += f"model_two: {op_two_element_type}.\n"
return result, msg
def compare_models(model_one: Model, model_two: Model, compare_names: bool = True):
"""Function to compare OpenVINO model (ops names, types and shapes).
:param model_one: The first model to compare.
:param model_two: The second model to compare.
:param compare_names: Flag to control friendly names checking. Default: True
:return: True if models are equal, otherwise raise an error with a report of mismatches.
"""
result, msg = _compare_models(model_one, model_two, compare_names=compare_names)
if not result:
raise RuntimeError(msg)
return result
def plugins_path(device, lib_path):
plugin_xml = f"""<ie>
<plugins>
<plugin location="{lib_path}" name="{device}">
</plugin>
</plugins>
</ie>"""
with open("plugin_path.xml", "w") as f:
f.write(plugin_xml)
plugins_paths = os.path.join(os.getcwd(), "plugin_path.xml")
return plugins_paths
def generate_image(shape: Tuple = (1, 3, 32, 32), dtype: Union[str, np.dtype] = "float32") -> np.array:
np.random.seed(42)
return np.random.rand(*shape).astype(dtype)
def get_model_with_template_extension():
core = Core()
ir = bytes(b"""<net name="Activation" version="10">
<layers>
<layer name="in1" type="Parameter" id="0" version="opset1">
<data shape="1,3,22,22" element_type="f32"/>
<output>
<port id="0" precision="FP32" names="in_data">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</output>
</layer>
<layer name="activation" id="1" type="Identity" version="extension">
<input>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</input>
<output>
<port id="2" precision="FP32" names="out_data">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</output>
</layer>
<layer name="output" type="Result" id="2" version="opset1">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="1"/>
<edge from-layer="1" from-port="2" to-layer="2" to-port="0"/>
</edges>
</net>""")
if platform == "win32":
core.add_extension(library_path="openvino_template_extension.dll")
else:
core.add_extension(library_path="libopenvino_template_extension.so")
return core, core.read_model(ir)
def get_relu_model(input_shape: List[int] = None, input_dtype=np.float32) -> openvino.runtime.Model:
if input_shape is None:
input_shape = [1, 3, 32, 32]
param = ops.parameter(input_shape, input_dtype, name="data")
relu = ops.relu(param, name="relu")
model = Model([relu], [param], "test_model")
model.get_ordered_ops()[2].friendly_name = "friendly"
assert model is not None
return model
def generate_relu_compiled_model(
device,
input_shape: List[int] = None,
input_dtype=np.float32,
) -> openvino.runtime.CompiledModel:
if input_shape is None:
input_shape = [1, 3, 32, 32]
model = get_relu_model(input_shape, input_dtype)
core = Core()
return core.compile_model(model, device, {})
def generate_model_and_image(device, input_shape: List[int] = None):
if input_shape is None:
input_shape = [1, 3, 32, 32]
return (generate_relu_compiled_model(device, input_shape), generate_image(input_shape))
def generate_add_model() -> openvino._pyopenvino.Model:
param1 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data1")
param2 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data2")
add = ops.add(param1, param2)
return Model(add, [param1, param2], "TestFunction")
def create_filename_for_test(test_name, tmp_path, is_xml_path=False, is_bin_path=False):
"""Return a tuple with automatically generated paths for xml and bin files.
:param test_name: Name used in generating.
:param is_xml_path: True if xml file should be pathlib.Path object, otherwise return string.
:param is_bin_path: True if bin file should be pathlib.Path object, otherwise return string.
:return: Tuple with two objects representing xml and bin files.
"""
python_version = str(sys.version_info.major) + "_" + str(sys.version_info.minor)
filename = test_name.replace("test_", "").replace("[", "_").replace("]", "_")
filename = filename + "_" + python_version
path_to_xml = tmp_path / Path(filename + ".xml")
path_to_bin = tmp_path / Path(filename + ".bin")
_xml = path_to_xml if is_xml_path else str(path_to_xml)
_bin = path_to_bin if is_bin_path else str(path_to_bin)
return (_xml, _bin)
src/bindings/python/tests/test_utils/utils/test_model.onnx → src/bindings/python/tests/utils/utils/test_model.onnx
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src/bindings/python/tests/test_utils/utils/test_model_fp16.bin → src/bindings/python/tests/utils/utils/test_model_fp16.bin
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src/bindings/python/tests/test_utils/utils/test_model_fp16.xml → src/bindings/python/tests/utils/utils/test_model_fp16.xml
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src/bindings/python/tests/test_utils/utils/test_model_fp32.bin → src/bindings/python/tests/utils/utils/test_model_fp32.bin
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src/bindings/python/tests/test_utils/utils/test_model_fp32.xml → src/bindings/python/tests/utils/utils/test_model_fp32.xml
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