Ruslan Nugmanov
236778aeec
* refactor of renaming libraries in layer tests * 1. adds check for old API and new FE usafe 2. refactor of api_2 arg * fix for tf_NMS test preprocessing * take libs path from LD_LIBRARY_PATH env * convert str to Path object * use wheels path to libs * print lib paths * print lib paths * use ov_frontend_path env * also check if file to rename exists * removes redundant prints * copy instead of rename * 1. copy instead of rename 2. adds some details to readme
310 lines
12 KiB
Python
310 lines
12 KiB
Python
# Copyright (C) 2018-2022 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import pytest
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from common.onnx_layer_test_class import OnnxRuntimeLayerTest
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class TestFlatten(OnnxRuntimeLayerTest):
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def create_flatten_net(self, axis, input_shape, dim, ir_version, opset=None):
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"""
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ONNX net IR net
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Input->Flatten->Output => Input->Reshape
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"""
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#
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# Create ONNX model
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#
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# TODO: possible move all imports to separate func?
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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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input = helper.make_tensor_value_info('input', TensorProto.FLOAT, input_shape)
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output = helper.make_tensor_value_info('output', TensorProto.FLOAT, dim)
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node_flatten_def = onnx.helper.make_node(
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'Flatten',
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inputs=['input'],
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outputs=['output'],
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axis=axis,
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)
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# Create the graph (GraphProto)
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graph_def = helper.make_graph(
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[node_flatten_def],
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'test_flatten_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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# Please, spesify 'type': 'Input' for inpit node
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# Moreover, do not forget to validate ALL layer attributes!!!
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#
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ref_net = None
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return onnx_net, ref_net
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def create_flatten_net_const(self, axis, input_shape, dim, ir_version, opset=None):
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"""
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ONNX net IR net
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Input->Flatten->Concat->Output => Input->Concat
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Input-' Const-'
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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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import numpy as np
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concat_axis = 0
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concat_output_shape = dim.copy()
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concat_output_shape[concat_axis] *= 2
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input = helper.make_tensor_value_info('input', TensorProto.FLOAT, dim)
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output = helper.make_tensor_value_info('output', TensorProto.FLOAT, concat_output_shape)
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const_number = np.prod(input_shape)
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constant = np.random.randint(-127, 127, const_number).astype(np.float)
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node_const_def = onnx.helper.make_node(
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'Constant',
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inputs=[],
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outputs=['const'],
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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=input_shape,
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vals=constant,
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),
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)
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node_flatten_def = onnx.helper.make_node(
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'Flatten',
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inputs=['const'],
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outputs=['flatten_output'],
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axis=axis,
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)
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node_concat_def = onnx.helper.make_node(
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'Concat',
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inputs=['input', 'flatten_output'],
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outputs=['output'],
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axis=concat_axis
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)
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# Create the graph (GraphProto)
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graph_def = helper.make_graph(
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[node_const_def, node_flatten_def, node_concat_def],
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'test_flatten_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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# Please, spesify 'type': 'Input' for inpit node
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# Moreover, do not forget to validate ALL layer attributes!!!
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#
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ref_net = None
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return onnx_net, ref_net
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test_data_3D = [
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dict(axis=0, input_shape=[1, 3, 224], dim=[1, 672]),
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dict(axis=-3, input_shape=[1, 3, 224], dim=[1, 672]),
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dict(axis=1, input_shape=[1, 3, 224], dim=[1, 672]),
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dict(axis=-2, input_shape=[1, 3, 224], dim=[1, 672]),
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dict(axis=2, input_shape=[2, 3, 224], dim=[6, 224]),
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dict(axis=-1, input_shape=[2, 3, 224], dim=[6, 224]),
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dict(axis=3, input_shape=[3, 3, 224], dim=[2016, 1])
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]
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test_data_4D_precommit = [
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dict(axis=1, input_shape=[1, 3, 224, 224], dim=[1, 150528]),
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dict(axis=-3, input_shape=[1, 3, 224, 224], dim=[1, 150528])
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]
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test_data_4D = [
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dict(axis=0, input_shape=[1, 3, 224, 224], dim=[1, 150528]),
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dict(axis=-4, input_shape=[1, 3, 224, 224], dim=[1, 150528]),
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dict(axis=1, input_shape=[1, 3, 224, 224], dim=[1, 150528]),
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dict(axis=-3, input_shape=[1, 3, 224, 224], dim=[1, 150528]),
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dict(axis=2, input_shape=[2, 3, 224, 224], dim=[6, 50176]),
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dict(axis=-2, input_shape=[2, 3, 224, 224], dim=[6, 50176]),
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dict(axis=3, input_shape=[3, 3, 224, 224], dim=[2016, 224]),
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dict(axis=-1, input_shape=[3, 3, 224, 224], dim=[2016, 224]),
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dict(axis=4, input_shape=[4, 3, 224, 224], dim=[602112, 1])
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]
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test_data_5D_precommit = [
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dict(axis=-5, input_shape=[1, 3, 9, 224, 224], dim=[1, 1354752]),
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dict(axis=5, input_shape=[4, 3, 9, 224, 224], dim=[5419008, 1])]
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test_data_5D = [
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dict(axis=0, input_shape=[1, 3, 9, 224, 224], dim=[1, 1354752]),
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dict(axis=-5, input_shape=[1, 3, 9, 224, 224], dim=[1, 1354752]),
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dict(axis=1, input_shape=[1, 3, 9, 224, 224], dim=[1, 1354752]),
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dict(axis=-4, input_shape=[1, 3, 9, 224, 224], dim=[1, 1354752]),
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dict(axis=2, input_shape=[2, 3, 9, 224, 224], dim=[6, 451584]),
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dict(axis=-3, input_shape=[2, 3, 9, 224, 224], dim=[6, 451584]),
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dict(axis=3, input_shape=[3, 3, 9, 224, 224], dim=[81, 50176]),
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dict(axis=-2, input_shape=[3, 3, 9, 224, 224], dim=[81, 50176]),
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dict(axis=4, input_shape=[3, 3, 9, 224, 224], dim=[18144, 224]),
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dict(axis=-1, input_shape=[3, 3, 9, 224, 224], dim=[18144, 224]),
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dict(axis=5, input_shape=[4, 3, 9, 224, 224], dim=[5419008, 1])
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]
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@pytest.mark.parametrize("params", test_data_3D)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_3D(self, params, opset, ie_device, precision, ir_version, temp_dir, use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net(**params, ir_version=ir_version, opset=opset),
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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_3D)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_3D_const(self, params, opset, ie_device, precision, ir_version, temp_dir,
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use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net_const(**params, ir_version=ir_version, opset=opset),
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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_4D)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_4D(self, params, opset, ie_device, precision, ir_version, temp_dir, use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net(**params, ir_version=ir_version, opset=opset),
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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_4D_precommit)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.precommit
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def test_flatten_4D_precommit(self, params, opset, ie_device, precision, ir_version, temp_dir,
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use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net(**params, ir_version=ir_version, opset=opset),
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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_4D_precommit)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_4D_const_precommit(self, params, opset, ie_device, precision, ir_version,
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temp_dir, use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net_const(**params, ir_version=ir_version, opset=opset),
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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_4D)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_4D_const(self, params, opset, ie_device, precision, ir_version, temp_dir,
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use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net_const(**params, ir_version=ir_version, opset=opset),
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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_5D_precommit)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_5D_precommit(self, params, opset, ie_device, precision, ir_version, temp_dir,
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use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net(**params, ir_version=ir_version, opset=opset),
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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_5D)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_5D(self, params, opset, ie_device, precision, ir_version, temp_dir, use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net(**params, ir_version=ir_version, opset=opset),
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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_5D_precommit)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_5D_const_precommit(self, params, opset, ie_device, precision, ir_version,
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temp_dir, use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net_const(**params, ir_version=ir_version, opset=opset),
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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_5D)
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@pytest.mark.parametrize("opset", [6, 9])
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@pytest.mark.nightly
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def test_flatten_5D_const(self, params, opset, ie_device, precision, ir_version, temp_dir,
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use_old_api):
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# negative axis not allowed by onnx spec for flatten-1 and flatten-9
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if params['axis'] < 0:
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self.skip_framework = True
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else:
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self.skip_framework = False
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self._test(*self.create_flatten_net_const(**params, ir_version=ir_version, opset=opset),
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ie_device, precision, ir_version, temp_dir=temp_dir, use_old_api=use_old_api)
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