# 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.
# ============================================================================
"""Defines sparse operators with functional form."""
from ..operations.sparse_ops import DenseToCSRSparseMatrix, CSRSparseMatrixToSparseTensor
from ..operations.array_ops import GatherNd
from ...common import CSRTensor, COOTensor, Tensor
from ...common import dtype as mstype
from ..composite.multitype_ops._constexpr_utils import raise_value_error, raise_type_error
gather_nd = GatherNd()
dense_to_csr = DenseToCSRSparseMatrix()
csr_sparse_matrix_to_sparse_tensor = CSRSparseMatrixToSparseTensor()
batch_csr_pointers_empty = Tensor([0, -1], dtype=mstype.int32)
[docs]def dense_to_sparse_coo(tensor):
"""
Convert a Tensor to COOTensor.
Note:
Only 2-D tensor is supported for now.
Args:
tensor: A dense tensor, must be 2-D.
Returns:
COOTensor, a 2-D coo_tensor, containing:
indices: the positions of all non-zero values of the input.
values: the non-zero values of the dense tensor.
shape: the shape of the coo_tensor, length is 2.
Raises:
TypeError: If input is not a tensor.
ValueError: If input tensor is not 2-D.
Supported Platforms:
``GPU``
Examples:
>>> from mindspore import Tensor
>>> import mindspore as ms
>>> x = Tensor([[1, 0], [-5, 0]], ms.float32)
>>> output = ops.dense_to_sparse_coo(x)
>>> print(output)
"""
if not isinstance(tensor, Tensor):
raise_type_error("For functional operator dense_to_sparse_coo, input argument must be a Tensor.")
if len(tensor.shape) != 2:
raise_value_error("Currently only support 2-D Tensor when converting to COOTensor.")
indices = tensor.nonzero().astype("int32")
values = gather_nd(tensor, indices)
return COOTensor(indices, values, tensor.shape)
[docs]def dense_to_sparse_csr(tensor):
"""
Convert a Tensor to CSRTensor.
Note:
Only 2-D tensor is supported for now.
Args:
tensor: A dense tensor, must be 2-D.
Returns:
CSRTensor, a 2-D csr_tensor, containing:
indptr: indicates the start and end point for `values` in each row.
indices: the column positions of all non-zero values of the input.
values: the non-zero values of the dense tensor.
shape: the shape of the csr_tensor, length is 2.
Raises:
TypeError: If input is not a tensor.
ValueError: If input tensor is not 2-D.
Supported Platforms:
``GPU``
Examples:
>>> from mindspore import Tensor
>>> import mindspore as ms
>>> x = Tensor([[1, 0], [-5, 0]], ms.float32)
>>> output = ops.dense_to_sparse_csr(x)
>>> print(output)
"""
if not isinstance(tensor, Tensor):
raise_type_error("For functional operator dense_to_sparse_csr, input argument must be a Tensor.")
if len(tensor.shape) != 2:
raise_value_error("Currently only support 2-D Tensor when converting to CSRTensor.")
indices = tensor.nonzero().astype("int32")
_, _, indptr, indices, values = dense_to_csr(tensor, indices)
return CSRTensor(indptr, indices, values, tensor.shape)
[docs]def csr_to_coo(tensor):
"""
Converts a CSRTensor to COOTensor.
Note:
Only 2-D CSRTensor is supported for now.
Args:
tensor: A CSRTensor, must be 2-D.
Returns:
2D COOTensor, the input tensor stored in COO format.
Raises:
TypeError: If input is not a COOTensor.
ValueError: If input tensor is not 2-D.
Supported Platforms:
``GPU``
Examples:
>>> from mindspore import Tensor, CSRTensor
>>> indptr = Tensor([0, 1, 2]).astype("int32")
>>> indices = Tensor([0, 1]).astype("int32")
>>> values = Tensor([2, 1]).astype("float32")
>>> shape = (2, 4)
>>> x = CSRTensor(indptr, indices, values, shape)
>>> output = ops.csr_to_coo(x)
>>> print(output)
"""
if not isinstance(tensor, CSRTensor):
raise_type_error("For functional operator csr_to_coo, input argument must be a CSRTensor.")
if len(tensor.shape) != 2:
raise_value_error("Currently only support 2-D CSRTensor when converting to COOTensor.")
shape = tensor.shape
indices, values, _ = csr_sparse_matrix_to_sparse_tensor(Tensor(shape, dtype=mstype.int32), batch_csr_pointers_empty,
tensor.indptr, tensor.indices, tensor.values)
return COOTensor(indices, values, shape)
__all__ = [
'dense_to_sparse_coo',
'dense_to_sparse_csr',
'csr_to_coo'
]
__all__.sort()