forked from mindspore-Ecosystem/mindspore
247 lines
10 KiB
Python
247 lines
10 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 numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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import mindspore as ms
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from mindspore.ops.operations.sparse_ops import SparseAdd
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class SparseAddNet(nn.Cell):
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def __init__(self):
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super().__init__()
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self.sparse_add = SparseAdd()
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def construct(self, a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh):
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return self.sparse_add(a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh)
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def sparse_add_same_indices(value_type, thresh_type, np_type, thresh_value):
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a_indices = Tensor([[0, 1], [1, 2]], ms.int64)
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a_values = Tensor([1, 2], value_type)
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a_shape = Tensor([3, 4], ms.int64)
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b_indices = Tensor([[0, 1], [1, 2]], ms.int64)
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b_values = Tensor([1, 2], value_type)
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b_shape = Tensor([3, 4], ms.int64)
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thresh = Tensor(thresh_value, thresh_type)
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sparse_add = SparseAddNet()
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sum_indices, sum_value, sum_shape = sparse_add(a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh)
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ground_truth_indices = np.array([[0, 1], [1, 2]], np.int64)
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ground_truth_value = np.array([2, 4], np_type)
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ground_truth_shape = np.array([3, 4], np.int64)
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assert np.allclose(sum_indices.asnumpy(), ground_truth_indices)
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assert np.allclose(sum_value.asnumpy(), ground_truth_value)
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assert np.allclose(sum_shape.asnumpy(), ground_truth_shape)
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def sparse_add_left_same_indices(value_type, thresh_type, np_type, thresh_value):
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a_indices = Tensor([[0, 1], [1, 2]], ms.int64)
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a_values = Tensor([1, 2], value_type)
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a_shape = Tensor([3, 4], ms.int64)
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b_indices = Tensor([[0, 1], [1, 3]], ms.int64)
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b_values = Tensor([1, 2], value_type)
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b_shape = Tensor([3, 4], ms.int64)
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thresh = Tensor(thresh_value, thresh_type)
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sparse_add = SparseAddNet()
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sum_indices, sum_value, sum_shape = sparse_add(a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh)
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ground_truth_indices = np.array([[0, 1], [1, 2], [1, 3]], np.int64)
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ground_truth_value = np.array([2, 2, 2], np_type)
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ground_truth_shape = np.array([3, 4], np.int64)
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assert np.allclose(sum_indices.asnumpy(), ground_truth_indices)
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assert np.allclose(sum_value.asnumpy(), ground_truth_value)
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assert np.allclose(sum_shape.asnumpy(), ground_truth_shape)
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def sparse_add_right_same_indices(value_type, thresh_type, np_type, thresh_value):
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a_indices = Tensor([[0, 1], [1, 3]], ms.int64)
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a_values = Tensor([1, 2], value_type)
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a_shape = Tensor([3, 4], ms.int64)
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b_indices = Tensor([[1, 2], [1, 3]], ms.int64)
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b_values = Tensor([1, 2], value_type)
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b_shape = Tensor([3, 4], ms.int64)
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thresh = Tensor(thresh_value, thresh_type)
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sparse_add = SparseAddNet()
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sum_indices, sum_value, sum_shape = sparse_add(a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh)
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ground_truth_indices = np.array([[0, 1], [1, 2], [1, 3]], np.int64)
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ground_truth_value = np.array([1, 1, 4], np_type)
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ground_truth_shape = np.array([3, 4], np.int64)
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assert np.allclose(sum_indices.asnumpy(), ground_truth_indices)
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assert np.allclose(sum_value.asnumpy(), ground_truth_value)
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assert np.allclose(sum_shape.asnumpy(), ground_truth_shape)
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def sparse_add_no_same_indices(value_type, thresh_type, np_type, thresh_value):
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a_indices = Tensor([[0, 1], [1, 3]], ms.int64)
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a_values = Tensor([1, 2], value_type)
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a_shape = Tensor([3, 4], ms.int64)
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b_indices = Tensor([[1, 2], [2, 2]], ms.int64)
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b_values = Tensor([1, 2], value_type)
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b_shape = Tensor([3, 4], ms.int64)
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thresh = Tensor(thresh_value, thresh_type)
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sparse_add = SparseAddNet()
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sum_indices, sum_value, sum_shape = sparse_add(a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh)
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ground_truth_indices = np.array([[0, 1], [1, 2], [1, 3], [2, 2]], np.int64)
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ground_truth_value = np.array([1, 1, 2, 2], np_type)
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ground_truth_shape = np.array([3, 4], np.int64)
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assert np.allclose(sum_indices.asnumpy(), ground_truth_indices)
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assert np.allclose(sum_value.asnumpy(), ground_truth_value)
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assert np.allclose(sum_shape.asnumpy(), ground_truth_shape)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_sparse_add_float32():
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"""
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Feature: Sparse add ops
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Description: test float32 value input
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Expectation: Output matching expected values
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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value_type = ms.float32
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thresh_type = ms.float32
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np_type = np.float32
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sparse_add_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 1)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_sparse_add_float64():
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"""
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Feature: Sparse add ops
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Description: test float64 value input
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Expectation: Output matching expected values
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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value_type = ms.float64
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thresh_type = ms.float64
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np_type = np.float64
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sparse_add_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 1)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_sparse_add_int8():
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"""
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Feature: Sparse add ops
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Description: test int8 value input
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Expectation: Output matching expected values
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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value_type = ms.int8
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thresh_type = ms.int8
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np_type = np.int8
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sparse_add_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 1)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_sparse_add_int16():
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"""
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Feature: Sparse add ops
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Description: test int16 value input
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Expectation: Output matching expected values
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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value_type = ms.int16
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thresh_type = ms.int16
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np_type = np.int16
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sparse_add_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 1)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_sparse_add_int32():
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"""
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Feature: Sparse add ops
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Description: test int32 value input
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Expectation: Output matching expected values
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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value_type = ms.int32
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thresh_type = ms.int32
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np_type = np.int32
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sparse_add_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 1)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_sparse_add_int64():
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"""
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Feature: Sparse add ops
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Description: test int64 value input
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Expectation: Output matching expected values
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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value_type = ms.int64
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thresh_type = ms.int64
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np_type = np.int64
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sparse_add_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_left_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_right_same_indices(value_type, thresh_type, np_type, 1)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 0)
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sparse_add_no_same_indices(value_type, thresh_type, np_type, 1)
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