add ops.arccos, ops.absolute, tensor.arccos, tensor.absolute st

tests/st/ops/test_absolute.py

@@ -0,0 +1,47 @@
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+import numpy as np
+import pytest
+import mindspore as ms
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore import ops
+
+
+class Net(nn.Cell):
+    def construct(self, x):
+        return ops.absolute(x)
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.platform_arm_cpu
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
+@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
+def test_absolute(mode):
+    """
+    Feature: absolute
+    Description: Verify the result of absolute
+    Expectation: success
+    """
+    ms.set_context(mode=mode)
+    x = Tensor(np.array([-1.0, 1.0, 0.0]), ms.float32)
+    net = Net()
+    output = net(x)
+    expect_output = np.array([1., 1., 0.], dtype=np.float32)
+    assert np.allclose(output.asnumpy(), expect_output)

tests/st/ops/test_arccos.py

@@ -0,0 +1,47 @@
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+import numpy as np
+import pytest
+import mindspore as ms
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore import ops
+
+
+class Net(nn.Cell):
+    def construct(self, x):
+        return ops.arccos(x)
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.platform_arm_cpu
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
+@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
+def test_arccos(mode):
+    """
+    Feature: arccos
+    Description: Verify the result of arccos
+    Expectation: success
+    """
+    ms.set_context(mode=mode)
+    x = Tensor(np.array([0.74, 0.04, 0.30, 0.56]), ms.float32)
+    net = Net()
+    output = net(x)
+    expect_output = np.array([0.737726, 1.5307857, 1.2661036, 0.9764105], dtype=np.float32)
+    assert np.allclose(output.asnumpy(), expect_output)

tests/st/tensor/test_absolute.py

@@ -0,0 +1,46 @@
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+import numpy as np
+import pytest
+import mindspore as ms
+import mindspore.nn as nn
+from mindspore import Tensor
+
+
+class Net(nn.Cell):
+    def construct(self, x):
+        return x.absolute()
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.platform_arm_cpu
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
+@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
+def test_tensor_absolute(mode):
+    """
+    Feature: tensor.absolute
+    Description: Verify the result of absolute
+    Expectation: success
+    """
+    ms.set_context(mode=mode)
+    x = Tensor(np.array([-1.0, 1.0, 0.0]), ms.float32)
+    net = Net()
+    output = net(x)
+    expect_output = np.array([1., 1., 0.], dtype=np.float32)
+    assert np.allclose(output.asnumpy(), expect_output)

tests/st/tensor/test_arccos.py

@@ -0,0 +1,46 @@
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+import numpy as np
+import pytest
+import mindspore as ms
+import mindspore.nn as nn
+from mindspore import Tensor
+
+
+class Net(nn.Cell):
+    def construct(self, x):
+        return x.arccos()
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.platform_arm_cpu
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
+@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
+def test_tensor_arccos(mode):
+    """
+    Feature: tensor.arccos
+    Description: Verify the result of arccos
+    Expectation: success
+    """
+    ms.set_context(mode=mode)
+    x = Tensor(np.array([0.74, 0.04, 0.30, 0.56]), ms.float32)
+    net = Net()
+    output = net(x)
+    expect_output = np.array([0.737726, 1.5307857, 1.2661036, 0.9764105], dtype=np.float32)
+    assert np.allclose(output.asnumpy(), expect_output)