* Enable ngraph python tests * Refactor and unify ngraph with onnx python tests * Revert deprecated test cases * Set ngraph and onnx python tests as a one test suite execution * Change unstrict Xfails to strict ones * Update after review: - add model zoo to onnx tests, - improvements of tests * Revert mounting zoo models dir Co-authored-by: Michał Karzyński <4430709+postrational@users.noreply.github.com>
52 lines
1.9 KiB
Python
52 lines
1.9 KiB
Python
# ******************************************************************************
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# Copyright 2017-2020 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ******************************************************************************
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import numpy as np
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import ngraph as ng
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from tests.runtime import get_runtime
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from tests import xfail_issue_34323
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@xfail_issue_34323
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def test_split():
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runtime = get_runtime()
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input_tensor = ng.constant(np.array([0, 1, 2, 3, 4, 5], dtype=np.int32))
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axis = ng.constant(0, dtype=np.int64)
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splits = 3
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split_node = ng.split(input_tensor, axis, splits)
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computation = runtime.computation(split_node)
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split_results = computation()
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expected_results = np.array([[0, 1], [2, 3], [4, 5]], dtype=np.int32)
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assert np.allclose(split_results, expected_results)
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@xfail_issue_34323
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def test_variadic_split():
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runtime = get_runtime()
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input_tensor = ng.constant(np.array([[0, 1, 2, 3, 4, 5], [6, 7, 8, 9, 10, 11]], dtype=np.int32))
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axis = ng.constant(1, dtype=np.int64)
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splits = ng.constant(np.array([2, 4], dtype=np.int64))
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v_split_node = ng.variadic_split(input_tensor, axis, splits)
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computation = runtime.computation(v_split_node)
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results = computation()
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split0 = np.array([[0, 1], [6, 7]], dtype=np.int32)
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split1 = np.array([[2, 3, 4, 5], [8, 9, 10, 11]], dtype=np.int32)
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assert np.allclose(results[0], split0)
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assert np.allclose(results[1], split1)
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