forked from mindspore-Ecosystem/mindspore
203 lines
6.6 KiB
Python
203 lines
6.6 KiB
Python
# Copyright 2021 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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"""smoke tests for CSR operations"""
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import pytest
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import numpy as np
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from mindspore import Tensor, CSRTensor, ms_function
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from mindspore.common import dtype as mstype
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from mindspore import nn, context
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context.set_context(mode=context.GRAPH_MODE)
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def compare_csr(csr1, csr2):
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assert isinstance(csr1, CSRTensor)
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assert isinstance(csr2, CSRTensor)
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assert (csr1.indptr.asnumpy() == csr2.indptr.asnumpy()).all()
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assert (csr1.indices.asnumpy() == csr2.indices.asnumpy()).all()
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assert (csr1.values.asnumpy() == csr2.values.asnumpy()).all()
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assert csr1.shape == csr2.shape
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_make_csr():
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"""
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Feature: Test CSRTensor Constructor in Graph and PyNative.
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Description: Test CSRTensor(indptr, indices, values, shape) and CSRTensor(CSRTensor)
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Expectation: Success.
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"""
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indptr = Tensor([0, 1, 2])
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indices = Tensor([0, 1])
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values = Tensor([1, 2], dtype=mstype.float32)
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shape = (2, 6)
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def test_pynative():
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return CSRTensor(indptr, indices, values, shape)
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test_graph = ms_function(test_pynative)
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csr1 = test_pynative()
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csr2 = test_graph()
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compare_csr(csr1, csr2)
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csr3 = CSRTensor(csr_tensor=csr2)
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compare_csr(csr3, csr2)
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_csr_attr():
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"""
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Feature: Test CSRTensor GetAttr in Graph and PyNative.
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Description: Test CSRTensor.indptr, CSRTensor.indices, CSRTensor.values, CSRTensor.shape.
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Expectation: Success.
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"""
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indptr = Tensor([0, 1, 2])
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indices = Tensor([0, 1])
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values = Tensor([1, 2], dtype=mstype.float32)
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shape = (2, 6)
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def test_pynative():
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csr = CSRTensor(indptr, indices, values, shape)
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return csr.indptr, csr.indices, csr.values, csr.shape
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test_graph = ms_function(test_pynative)
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csr1_tuple = test_pynative()
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csr2_tuple = test_graph()
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csr1 = CSRTensor(*csr1_tuple)
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csr2 = CSRTensor(*csr2_tuple)
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compare_csr(csr1, csr2)
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_csr_tensor_in_while():
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"""
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Feature: Test CSRTensor in while loop.
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Description: Test CSRTensor computation in while loop.
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Expectation: Success.
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"""
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class CSRTensorValuesDouble(nn.Cell):
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def construct(self, x):
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indptr = x.indptr
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indices = x.indices
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values = x.values * 2
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shape = x.shape
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return CSRTensor(indptr, indices, values, shape)
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class CSRTensorValuesAdd2(nn.Cell):
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def construct(self, x):
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indptr = x.indptr
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indices = x.indices
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values = x.values + 2
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shape = x.shape
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return CSRTensor(indptr, indices, values, shape)
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class CSRTensorWithControlWhile(nn.Cell):
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def __init__(self, shape):
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super().__init__()
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self.op1 = CSRTensorValuesDouble()
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self.op2 = CSRTensorValuesAdd2()
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self.shape = shape
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@ms_function
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def construct(self, a, b, indptr, indices, values):
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x = CSRTensor(indptr, indices, values, self.shape)
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x = self.op2(x)
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while a > b:
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x = self.op1(x)
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b = b + 1
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return x
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a = Tensor(3, mstype.int32)
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b = Tensor(0, mstype.int32)
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indptr = Tensor([0, 1, 2])
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indices = Tensor([0, 1])
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values = Tensor([1, 2], dtype=mstype.float32)
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shape = (2, 6)
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net = CSRTensorWithControlWhile(shape)
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out = net(a, b, indptr, indices, values)
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assert np.allclose(out.indptr.asnumpy(), indptr.asnumpy(), .0, .0)
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assert np.allclose(out.indices.asnumpy(), indices.asnumpy(), .0, .0)
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assert np.allclose((values.asnumpy() + 2) * 8, out.values.asnumpy(), .0, .0)
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assert shape == out.shape
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@pytest.mark.level1
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_csr_tensor_in_while_cpu():
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"""
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Feature: Test CSRTensor in while loop.
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Description: Test CSRTensor computation in while loop.
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Expectation: Success.
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"""
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class CSRTensorValuesDouble(nn.Cell):
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def construct(self, x):
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indptr = x.indptr
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indices = x.indices
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values = x.values * 2
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shape = x.shape
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return CSRTensor(indptr, indices, values, shape)
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class CSRTensorValuesAdd2(nn.Cell):
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def construct(self, x):
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indptr = x.indptr
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indices = x.indices
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values = x.values + 2
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shape = x.shape
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return CSRTensor(indptr, indices, values, shape)
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class CSRTensorWithControlWhile(nn.Cell):
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def __init__(self, shape):
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super().__init__()
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self.op1 = CSRTensorValuesDouble()
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self.op2 = CSRTensorValuesAdd2()
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self.shape = shape
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@ms_function
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def construct(self, a, b, indptr, indices, values):
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x = CSRTensor(indptr, indices, values, self.shape)
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x = self.op2(x)
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while a > b:
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x = self.op1(x)
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b = b + 1
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return x
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a = Tensor(3, mstype.int32)
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b = Tensor(0, mstype.int32)
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indptr = Tensor([0, 1, 2])
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indices = Tensor([0, 1])
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values = Tensor([1, 2], dtype=mstype.float32)
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shape = (2, 6)
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net = CSRTensorWithControlWhile(shape)
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out = net(a, b, indptr, indices, values)
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assert np.allclose(out.indptr.asnumpy(), indptr.asnumpy(), .0, .0)
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assert np.allclose(out.indices.asnumpy(), indices.asnumpy(), .0, .0)
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assert np.allclose((values.asnumpy() + 2) * 8, out.values.asnumpy(), .0, .0)
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assert shape == out.shape
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