Ilya Churaev
0c9abf43a9
* Updated copyright headers
* Revert "Fixed linker warnings in docs snippets on Windows (#15119)"
This reverts commit 372699ec49.
218 lines
8.9 KiB
Python
218 lines
8.9 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import pytest
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from common.layer_test_class import check_ir_version
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from common.onnx_layer_test_class import OnnxRuntimeLayerTest
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from unit_tests.utils.graph import build_graph
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class TestPad(OnnxRuntimeLayerTest):
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def create_net(self, shape, mode, pads, value, ir_version, opset=None):
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"""
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ONNX net IR net
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Input->Pad->Output => Input->Pad
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"""
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#
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# Create ONNX model
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#
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import onnx
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from onnx import helper
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from onnx import TensorProto
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_pads = np.array(pads).reshape([2, -1])
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output_shape = (np.array(shape) + _pads[0, :] + _pads[1, :]).tolist()
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input = helper.make_tensor_value_info('input', TensorProto.FLOAT, shape)
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output = helper.make_tensor_value_info('output', TensorProto.FLOAT, output_shape)
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nodes = []
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if opset is not None and opset < 11:
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args = dict(pads=pads)
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if mode:
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args['mode'] = mode
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if value:
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args['value'] = value
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node_def = onnx.helper.make_node(
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'Pad',
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inputs=['input'],
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outputs=['pad'],
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**args
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)
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nodes.append(node_def)
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else:
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node_pads_def = helper.make_node(
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'Constant',
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inputs=[],
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outputs=['pads'],
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value=helper.make_tensor(
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name='const_tensor',
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data_type=TensorProto.INT64,
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dims=[len(pads)],
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vals=pads,
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),
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)
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inputs = ['input', 'pads']
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if value is not None:
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node_value_def = helper.make_node(
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'Constant',
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inputs=[],
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outputs=['value'],
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value=helper.make_tensor(
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name='const_tensor',
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data_type=TensorProto.FLOAT,
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dims=[],
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vals=[value],
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),
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)
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inputs.append('value')
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nodes.append(node_value_def)
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args = dict()
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if mode:
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args['mode'] = mode
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node_def = onnx.helper.make_node(
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'Pad',
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inputs=inputs,
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outputs=['pad'],
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**args
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)
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nodes.extend([node_pads_def, node_def])
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sigmoid_def = onnx.helper.make_node(
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'Elu',
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inputs=['pad'],
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outputs=['output']
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)
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nodes.append(sigmoid_def)
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# Create the graph (GraphProto)
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graph_def = helper.make_graph(
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nodes,
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'test_model',
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[input],
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[output],
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)
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# Create the model (ModelProto)
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args = dict(producer_name='test_model')
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if opset:
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args['opset_imports'] = [helper.make_opsetid("", opset)]
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onnx_net = helper.make_model(graph_def, **args)
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#
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# Create reference IR net
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#
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ref_net = None
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if check_ir_version(10, None, ir_version):
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nodes_attributes = {
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'input': {'kind': 'op', 'type': 'Parameter'},
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'input_data': {'shape': shape, 'kind': 'data'},
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'pads_begin_indata': {'value': _pads[0, :], 'kind': 'data'},
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'pads_begin': {'kind': 'op', 'type': 'Const'},
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'pads_begin_data': {'shape': [len(_pads[0, :])], 'kind': 'data'},
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'pads_end_indata': {'value': _pads[1, :], 'kind': 'data'},
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'pads_end': {'kind': 'op', 'type': 'Const'},
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'pads_end_data': {'shape': [len(_pads[1, :])], 'kind': 'data'},
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'node': {'kind': 'op', 'type': 'Pad', 'pad_mode': 'constant' if not mode else mode},
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'node_data': {'shape': output_shape, 'kind': 'data'},
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'elu': {'kind': 'op', 'type': 'Elu'},
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'elu_data': {'shape': output_shape, 'kind': 'data'},
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'result': {'kind': 'op', 'type': 'Result'}
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}
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edges = [('input', 'input_data'),
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('input_data', 'node'),
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('pads_begin_indata', 'pads_begin'),
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('pads_begin', 'pads_begin_data'),
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('pads_begin_data', 'node'),
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('pads_end_indata', 'pads_end'),
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('pads_end', 'pads_end_data'),
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('pads_end_data', 'node'),
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('node', 'node_data'),
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('node_data', 'elu'),
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('elu', 'elu_data'),
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('elu_data', 'result')
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]
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if mode in (None, "constant"):
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nodes_attributes.update({'const_node_indata': {'value': value, 'kind': 'data'},
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'const_node': {'kind': 'op', 'type': 'Const'},
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'const_node_data': {'shape': None, 'kind': 'data'}
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})
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edges += [('const_node_indata', 'const_node'),
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('const_node', 'const_node_data'),
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('const_node_data', 'node')
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]
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ref_net = build_graph(nodes_attributes, edges)
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return onnx_net, ref_net
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test_data_precommit = [
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pytest.param(dict(shape=[6, 8, 10, 12], pads=[1, 2, 3, 4, 5, 6, 7, 8]),
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marks=pytest.mark.skip(reason="Skipped until fixed")),
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pytest.param(dict(shape=[8, 10, 12, 14, 16], pads=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
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marks=pytest.mark.skip(reason="Skipped until fixed"))]
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test_data = [dict(shape=[10, 12], pads=[1, 1, 1, 1]),
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dict(shape=[10, 12], pads=[1, 2, 3, 4]),
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dict(shape=[8, 10, 12], pads=[0, 0, 1, 0, 0, 1]),
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dict(shape=[8, 10, 12], pads=[1, 2, 3, 4, 5, 6]),
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dict(shape=[6, 8, 10, 12], pads=[0, 0, 1, 1, 0, 0, 1, 1]),
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dict(shape=[6, 8, 10, 12], pads=[0, 0, 1, 2, 0, 0, 3, 4]),
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dict(shape=[6, 8, 10, 12], pads=[1, 1, 1, 1, 1, 1, 1, 1]),
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dict(shape=[6, 8, 10, 12], pads=[1, 2, 3, 4, 5, 6, 7, 8]),
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dict(shape=[8, 10, 12, 14, 16], pads=[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]),
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dict(shape=[8, 10, 12, 14, 16], pads=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10])]
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@pytest.mark.parametrize("params", test_data)
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@pytest.mark.parametrize("mode_value", [(None, None),
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(None, 0.5),
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('constant', None),
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('constant', 0.5),
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('reflect', None),
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('edge', None)])
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@pytest.mark.nightly
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def test_pad_opset_9(self, params, mode_value, ie_device, precision, ir_version, temp_dir,
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use_old_api):
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mode, value = mode_value
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self._test(
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*self.create_net(**params, mode=mode, value=value, ir_version=ir_version, opset=9),
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ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
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@pytest.mark.parametrize("params", test_data_precommit)
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@pytest.mark.parametrize("mode_value", [(None, None),
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(None, 0.5),
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('constant', None),
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('constant', 0.5),
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('reflect', None),
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('edge', None)])
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@pytest.mark.precommit
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def test_pad_opset_latest_precommit(self, params, mode_value, ie_device, precision, ir_version,
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temp_dir, use_old_api):
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mode, value = mode_value
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self._test(*self.create_net(**params, mode=mode, value=value, ir_version=ir_version),
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ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
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@pytest.mark.parametrize("params", test_data)
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@pytest.mark.parametrize("mode_value", [(None, None),
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(None, 0.5),
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('constant', None),
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('constant', 0.5),
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('reflect', None),
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('edge', None)])
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@pytest.mark.nightly
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def test_pad_opset_latest(self, params, mode_value, ie_device, precision, ir_version, temp_dir,
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use_old_api):
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mode, value = mode_value
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self._test(*self.create_net(**params, mode=mode, value=value, ir_version=ir_version),
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ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
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