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activation.py
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activation.py
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# 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.
__all__ = []
from paddle import _C_ops, in_dynamic_mode
def relu(x, name=None):
"""
sparse relu activation.
.. math::
out = max(x, 0)
Parameters:
x (Tensor): The input Sparse Tensor with data type float32, float64.
name (str, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
Returns:
A Sparse Tensor with the same data type and shape as ``x`` .
Examples:
.. code-block:: python
import paddle
import numpy as np
from paddle.fluid.framework import _test_eager_guard
with _test_eager_guard():
dense_x = paddle.to_tensor(np.array([-2, 0, 1]).astype('float32'))
sparse_x = dense_x.to_sparse_coo(1)
out = paddle.sparse.functional.relu(sparse_x)
"""
assert in_dynamic_mode(), "Currently, Sparse API only support dynamic mode"
if x.is_sparse_coo():
return _C_ops.final_state_sparse_coo_relu(x)
elif x.is_sparse_csr():
return _C_ops.final_state_sparse_csr_relu(x)
else:
raise ValueError("Currently, sparse.relu only support the input of SparseCooTensor or SparseCsrTensor")
def sqrt(x, name=None):
"""
sparse sqrt activation.
.. math::
out = sqrt(x)
Parameters:
x (Tensor): The input Sparse Tensor with data type float32, float64.
name (str, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
Returns:
A Sparse Tensor with the same data type and shape as ``x`` .
Examples:
.. code-block:: python
import paddle
import numpy as np
from paddle.fluid.framework import _test_eager_guard
with _test_eager_guard():
dense_x = paddle.to_tensor(np.array([-2, 0, 1]).astype('float32'))
sparse_x = dense_x.to_sparse_coo(1)
out = paddle.sparse.functional.sqrt(sparse_x)
"""
assert in_dynamic_mode(), "Currently, Sparse API only support dynamic mode"
if x.is_sparse_coo():
return _C_ops.final_state_sparse_coo_sqrt(x)
elif x.is_sparse_csr():
return _C_ops.final_state_sparse_csr_sqrt(x)
else:
raise ValueError("Currently, sparse.sqrt only support the input of SparseCooTensor or SparseCsrTensor")