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openvino/tests/layer_tests/onnx_tests/test_prelu.py
Ilya Churaev 0c9abf43a9 Updated copyright headers (#15124)
* Updated copyright headers

* Revert "Fixed linker warnings in docs snippets on Windows (#15119)"

This reverts commit 372699ec49.
2023-01-16 11:02:17 +04:00

152 lines
6.2 KiB
Python

# Copyright (C) 2018-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from unit_tests.utils.graph import build_graph
class TestPRelu(OnnxRuntimeLayerTest):
def create_net(self, shape, slope_shape, precision, ir_version, opset=None):
"""
ONNX net IR net
Input->PRelu->Output => Input->PReLU
"""
#
# Create ONNX model
#
import onnx
from onnx import helper
from onnx import TensorProto
input = helper.make_tensor_value_info('input', TensorProto.FLOAT, shape)
output = helper.make_tensor_value_info('output', TensorProto.FLOAT, shape)
const = np.random.randn(*slope_shape).astype(np.float32)
node_slope_def = onnx.helper.make_node(
'Constant',
inputs=[],
outputs=['slope'],
value=helper.make_tensor(
name='const_tensor',
data_type=TensorProto.FLOAT,
dims=const.shape,
vals=const.flatten(),
),
)
node_def = onnx.helper.make_node(
'PRelu',
inputs=['input', 'slope'],
outputs=['output']
)
# Create the graph (GraphProto)
graph_def = helper.make_graph(
[node_slope_def, node_def],
'test_model',
[input],
[output],
)
# Create the model (ModelProto)
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
#
# Create reference IR net
#
ref_net = None
if check_ir_version(10, None, ir_version):
nodes_attributes = {
'input': {'kind': 'op', 'type': 'Parameter'},
'input_data': {'shape': shape, 'kind': 'data'},
'weights_indata': {'kind': 'data', 'value': const.flatten()},
'weights': {'kind': 'op', 'type': 'Const'},
'weights_data': {'kind': 'data', 'shape': [len(const.flatten())]},
'node': {'kind': 'op', 'type': 'PReLU'},
'node_data': {'shape': shape, 'kind': 'data'},
'result': {'kind': 'op', 'type': 'Result'}
}
ref_net = build_graph(nodes_attributes,
[('input', 'input_data'),
('input_data', 'node'),
('weights_indata', 'weights'),
('weights', 'weights_data'),
('weights_data', 'node'),
('node', 'node_data'),
('node_data', 'result')
])
return onnx_net, ref_net
# Note: IE only support slopes of one element or of size equal to number of channels.
test_data_shared_channels = [
dict(shape=[10, 12], slope_shape=[12]),
dict(shape=[8, 10, 12], slope_shape=[10, 1]),
dict(shape=[6, 8, 10, 12], slope_shape=[8, 1, 1]),
dict(shape=[4, 6, 8, 10, 12], slope_shape=[6, 1, 1, 1])]
test_data_scalar_precommit = [
dict(shape=[2, 4, 6, 8], slope_shape=[1]),
dict(shape=[2, 4, 6, 8, 10], slope_shape=[1])
]
test_data_scalar = [
dict(shape=[10, 12], slope_shape=[1]),
dict(shape=[8, 10, 12], slope_shape=[1]),
dict(shape=[6, 8, 10, 12], slope_shape=[1]),
dict(shape=[4, 6, 8, 10, 12], slope_shape=[1])]
test_data_precommit = [dict(shape=[8, 10, 12], slope_shape=[12])]
@pytest.mark.parametrize("params", test_data_scalar)
@pytest.mark.nightly
def test_prelu_opset7_scalar(self, params, ie_device, precision, ir_version, temp_dir, use_old_api):
self._test(*self.create_net(**params, precision=precision, opset=7, ir_version=ir_version),
ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
@pytest.mark.parametrize("params", test_data_shared_channels)
@pytest.mark.nightly
def test_prelu_opset7_shared_channels(self, params, ie_device, precision, ir_version, temp_dir,
use_old_api):
self._test(*self.create_net(**params, precision=precision, opset=7, ir_version=ir_version),
ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
@pytest.mark.parametrize("params", test_data_precommit)
@pytest.mark.precommit
def test_prelu_shared_channels_precommit(self, params, ie_device, precision, ir_version,
temp_dir, use_old_api):
self._test(*self.create_net(**params, precision=precision, ir_version=ir_version),
ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
@pytest.mark.parametrize("params", test_data_scalar_precommit)
@pytest.mark.precommit
def test_prelu_scalar_precommit(self, params, ie_device, precision, ir_version, temp_dir,
use_old_api):
self._test(*self.create_net(**params, precision=precision, ir_version=ir_version),
ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
@pytest.mark.parametrize("params", test_data_scalar)
@pytest.mark.nightly
def test_prelu_scalar(self, params, ie_device, precision, ir_version, temp_dir, use_old_api):
self._test(*self.create_net(**params, precision=precision, ir_version=ir_version),
ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
@pytest.mark.parametrize("params", test_data_shared_channels)
@pytest.mark.nightly
def test_prelu_shared_channels(self, params, ie_device, precision, ir_version, temp_dir, use_old_api):
self._test(*self.create_net(**params, precision=precision, ir_version=ir_version),
ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)