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# Copyright 2020 Huawei Technologies Co., Ltd |
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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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"""Test summary function of ops params valid check.""" |
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import os |
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import tempfile |
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import shutil |
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from enum import Enum |
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import numpy as np |
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import pytest |
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import mindspore.nn as nn |
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from mindspore.common.tensor import Tensor |
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from mindspore.ops import operations as P |
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from mindspore.train.summary.summary_record import SummaryRecord |
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class SummaryEnum(Enum): |
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"""Summary enum.""" |
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IMAGE = P.ImageSummary.__name__ |
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SCALAR = P.ScalarSummary.__name__ |
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TENSOR = P.TensorSummary.__name__ |
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HISTOGRAM = P.HistogramSummary.__name__ |
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class SummaryNet(nn.Cell): |
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"""Summary net definition.""" |
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def __init__(self, summary_type, tag, data): |
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super(SummaryNet, self).__init__() |
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self.tag = tag |
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self.data = data |
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self.summary_fn = getattr(P, summary_type)() |
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self.one = Tensor(np.array([1]).astype(np.float32)) |
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self.add = P.Add() |
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def construct(self): |
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self.summary_fn(self.tag, self.data) |
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return self.add(self.one, self.one) |
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class TestSummaryOps: |
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"""Test summary operators.""" |
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summary_dir = '' |
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@classmethod |
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def run_case(cls, net): |
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""" run_case """ |
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net.set_train() |
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steps = 10 |
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with SummaryRecord(cls.summary_dir) as test_writer: |
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for i in range(1, steps): |
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net() |
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test_writer.record(i) |
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@classmethod |
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def setup_class(cls): |
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"""Run before class.""" |
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if not os.path.exists(cls.summary_dir): |
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cls.summary_dir = tempfile.mkdtemp(suffix='_summary') |
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@classmethod |
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def teardown_class(cls): |
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"""Run after class.""" |
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if os.path.exists(cls.summary_dir): |
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shutil.rmtree(cls.summary_dir) |
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@pytest.mark.parametrize( |
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"summary_type, value", |
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[ |
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(SummaryEnum.SCALAR.value, Tensor(1)), |
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(SummaryEnum.SCALAR.value, Tensor(np.array([1]))), |
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(SummaryEnum.IMAGE.value, Tensor(np.array([[[[1], [2], [3], [4]]]]))), |
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(SummaryEnum.TENSOR.value, Tensor(np.array([[1], [2], [3], [4]]))), |
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(SummaryEnum.HISTOGRAM.value, Tensor(np.array([[1], [2], [3], [4]]))), |
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]) |
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def test_summary_success(self, summary_type, value): |
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"""Test summary success with valid tag and valid data.""" |
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net = SummaryNet(summary_type, tag='tag', data=value) |
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TestSummaryOps.run_case(net) |
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@pytest.mark.parametrize( |
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"summary_type", |
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[ |
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SummaryEnum.SCALAR.value, |
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SummaryEnum.IMAGE.value, |
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SummaryEnum.HISTOGRAM.value, |
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SummaryEnum.TENSOR.value |
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]) |
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def test_summary_tag_is_none(self, summary_type): |
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"""Test summary tag is None, all summary operator validation rules are consistent.""" |
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net = SummaryNet(summary_type, tag=None, data=Tensor(0)) |
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with pytest.raises(TypeError): |
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TestSummaryOps.run_case(net) |
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@pytest.mark.parametrize( |
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"summary_type", |
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[ |
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SummaryEnum.SCALAR.value, |
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SummaryEnum.IMAGE.value, |
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SummaryEnum.HISTOGRAM.value, |
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SummaryEnum.TENSOR.value |
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]) |
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def test_summary_tag_is_empty_string(self, summary_type): |
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"""Test summary tag is a empty string, all summary operator validation rules are consistent.""" |
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net = SummaryNet(summary_type, tag='', data=Tensor(0)) |
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with pytest.raises(ValueError): |
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TestSummaryOps.run_case(net) |
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@pytest.mark.parametrize("tag", [123, True, Tensor(0)]) |
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def test_summary_tag_is_not_string(self, tag): |
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"""Test summary tag is not a string, all summary operator validation rules are consistent.""" |
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# All summary operator validation rules are consistent, so we only test scalar summary. |
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net = SummaryNet(SummaryEnum.SCALAR.value, tag=tag, data=Tensor(0)) |
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with pytest.raises(TypeError): |
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TestSummaryOps.run_case(net) |
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@pytest.mark.parametrize("value", [123, True, 'data']) |
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def test_summary_value_type_invalid(self, value): |
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"""Test the type of summary value is invalid, all summary operator validation rules are consistent.""" |
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# All summary operator validation rules are consistent, so we only test scalar summary. |
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net = SummaryNet(SummaryEnum.SCALAR.value, tag='tag', data=value) |
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with pytest.raises(TypeError): |
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TestSummaryOps.run_case(net) |
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@pytest.mark.parametrize( |
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"summary_type, value", |
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[ |
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(SummaryEnum.IMAGE.value, Tensor(np.array([1, 2]))), |
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(SummaryEnum.SCALAR.value, Tensor(np.array([1, 2]))), |
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(SummaryEnum.TENSOR.value, Tensor(0)), |
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(SummaryEnum.HISTOGRAM.value, Tensor(0)) |
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]) |
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def test_value_shape_invalid(self, summary_type, value): |
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"""Test invalid shape of every summary operators.""" |
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net = SummaryNet(summary_type, tag='tag', data=value) |
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with pytest.raises(ValueError): |
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TestSummaryOps.run_case(net) |
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