forked from mindspore-Ecosystem/mindspore
214 lines
7.5 KiB
Python
214 lines
7.5 KiB
Python
# Copyright 2022 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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import pytest
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import numpy as np
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from mindspore import Tensor
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import mindspore.nn as nn
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import mindspore.context as context
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from mindspore.ops import functional as F
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from mindspore.common import dtype as mstype
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_less_lessequal_ops_infer_value_shape():
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"""
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Feature: less and less_equal operator test case.
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Description: test less and less equal infer.
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Expectation: success.
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"""
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class LessNet(nn.Cell):
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def __init__(self):
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super(LessNet, self).__init__()
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self.input_x1 = Tensor(np.array([[0, 1, 3], [2, 4, 6]]).astype(np.float32))
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self.input_x2 = Tensor(np.array([[1, 2, 4], [3, 5, 7]]).astype(np.float32))
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def construct(self):
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less_res = self.input_x1 < self.input_x2
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less_equal_res = self.input_x1 <= self.input_x2
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output = (less_res.all(), less_res.shape, less_equal_res.all(), less_equal_res.shape)
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return output
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less_net = LessNet()
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less_out, less_out_shape, less_equal_out, less_equal_out_shape = less_net()
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assert less_out
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assert less_out_shape == (2, 3)
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assert less_equal_out
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assert less_equal_out_shape == (2, 3)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_greater_greaterequal_ops_infer_value_shape():
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"""
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Feature: greater and greater_equal operator test case.
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Description: test greater and greater_equal infer.
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Expectation: success.
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"""
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class GreaterNet(nn.Cell):
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def __init__(self):
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super(GreaterNet, self).__init__()
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self.input_x1 = Tensor(np.array([[0, 1, 3], [2, 4, 6]]).astype(np.float32))
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self.input_x2 = Tensor(np.array([[1, 2, 4], [3, 5, 7]]).astype(np.float32))
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def construct(self):
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greater_res = self.input_x1 > self.input_x2
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greater_equal_res = self.input_x1 >= self.input_x2
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output = (greater_res.all(), greater_res.shape, greater_equal_res.all(), greater_equal_res.shape)
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return output
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greater_net = GreaterNet()
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greater_out, greater_out_shape, greater_equal_out, greater_equal_out_shape = greater_net()
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assert not greater_out
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assert greater_out_shape == (2, 3)
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assert not greater_equal_out
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assert greater_equal_out_shape == (2, 3)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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def test_greater_equal_functional_api_modes(mode):
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"""
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Feature: Test greater_equal functional api.
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Description: Test greater_equal functional api for Graph and PyNative modes.
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Expectation: The result match to the expect value.
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"""
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context.set_context(mode=mode, device_target="CPU")
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x = Tensor(np.array([1, 2, 3]), mstype.int32)
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y = Tensor(np.array([1, 1, 4]), mstype.int32)
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output = F.greater_equal(x, y)
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expected = np.array([True, True, False])
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np.testing.assert_array_equal(output.asnumpy(), expected)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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def test_greater_equal_tensor_api_modes(mode):
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"""
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Feature: Test greater_equal tensor api.
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Description: Test greater_equal tensor api for Graph and PyNative modes.
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Expectation: The result match to the expect value.
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"""
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context.set_context(mode=mode, device_target="CPU")
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x = Tensor(np.array([1, 2, 3]), mstype.int32)
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y = Tensor(np.array([1, 1, 4]), mstype.int32)
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output = x.greater_equal(y)
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expected = np.array([True, True, False])
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np.testing.assert_array_equal(output.asnumpy(), expected)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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def test_greater_functional_api_modes(mode):
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"""
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Feature: Test greater functional api.
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Description: Test greater functional api for Graph and PyNative modes.
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Expectation: The result match to the expect value.
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"""
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context.set_context(mode=mode, device_target="CPU")
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x = Tensor(np.array([1, 2, 3]), mstype.int32)
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y = Tensor(np.array([1, 1, 4]), mstype.int32)
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output = F.greater(x, y)
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expected = np.array([False, True, False])
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np.testing.assert_array_equal(output.asnumpy(), expected)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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def test_greater_tensor_api_modes(mode):
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"""
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Feature: Test greater tensor api.
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Description: Test greater tensor api for Graph and PyNative modes.
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Expectation: The result match to the expect value.
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"""
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context.set_context(mode=mode, device_target="CPU")
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x = Tensor(np.array([1, 2, 3]), mstype.int32)
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y = Tensor(np.array([1, 1, 4]), mstype.int32)
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output = x.greater(y)
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expected = np.array([False, True, False])
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np.testing.assert_array_equal(output.asnumpy(), expected)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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def test_le_tensor_api_modes(mode):
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"""
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Feature: Test le tensor api.
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Description: Test le tensor api for Graph and PyNative modes.
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Expectation: The result match to the expect value.
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"""
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context.set_context(mode=mode, device_target="CPU")
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x = Tensor([1, 2, 3], mstype.int32)
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y = Tensor([1, 1, 4], mstype.int32)
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output = x.le(y)
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expected = np.array([True, False, True])
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np.testing.assert_array_equal(output.asnumpy(), expected)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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def test_less_tensor_api_modes(mode):
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"""
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Feature: Test less tensor api.
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Description: Test less tensor api for Graph and PyNative modes.
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Expectation: The result match to the expect value.
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"""
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context.set_context(mode=mode, device_target="CPU")
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x = Tensor([1, 2, 3], mstype.int32)
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y = Tensor([1, 1, 4], mstype.int32)
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output = x.less(y)
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expected = np.array([False, False, True])
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np.testing.assert_array_equal(output.asnumpy(), expected)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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def test_ne_tensor_api_modes(mode):
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"""
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Feature: Test ne tensor api.
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Description: Test ne tensor api for Graph and PyNative modes.
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Expectation: The result match to the expect value.
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"""
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context.set_context(mode=mode, device_target="CPU")
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x = Tensor([1, 2, 3], mstype.float32)
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output = x.ne(2.0)
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expected = np.array([True, False, True])
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np.testing.assert_array_equal(output.asnumpy(), expected)
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