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Paddle/python/paddle/complex/tensor/math.py

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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# 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.
from ..helper import is_complex, is_real, complex_variable_exists
from ...fluid.framework import ComplexVariable
from ...fluid import layers
__all__ = [
'elementwise_add', 'elementwise_sub', 'elementwise_mul', 'elementwise_div'
]
def elementwise_add(x, y, axis=-1, name=None):
"""
The element-wise addition layer for complex number inputs. At least one of
inputs :attr:`x` and :attr:`y` must be a ComplexVariable. See the detailed
description for the function and other arguments
in :ref:`api_fluid_layers_elementwise_add` .
Args:
x (Variable|ComplexVariable): The first input Variable or ComplexVariable
with any number of dimensions. The supported data types include float32
and float64 when it is a Variable. Otherwise the supported data types
are complex64 or complex128.
y (Variable|ComplexVariable): The second input Variable or ComplexVariable
with any number of dimensions. The supported data types include float32
and float64 when it is a Variable. Otherwise the supported data types
are complex64 or complex128.
Examples:
.. code-block:: python
import numpy as np
import paddle
import paddle.fluid.dygraph as dg
a = np.array([[1.0+1.0j, 2.0+1.0j], [3.0+1.0j, 4.0+1.0j]])
b = np.array([[5.0+2.0j, 6.0+2.0j], [7.0+2.0j, 8.0+2.0j]])
with dg.guard():
x = dg.to_variable(a)
y = dg.to_variable(b)
out = paddle.complex.elementwise_add(x, y)
print(out.numpy())
# [[ 6.+3.j 8.+3.j]
# [10.+3.j 12.+3.j]]
"""
complex_variable_exists([x, y], "elementwise_add")
(x_real, x_imag) = (x.real, x.imag) if is_complex(x) else (x, None)
(y_real, y_imag) = (y.real, y.imag) if is_complex(y) else (y, None)
real = layers.elementwise_add(x_real, y_real, axis=axis, name=name)
if is_real(x_imag) and is_real(y_imag):
imag = layers.elementwise_add(x_imag, y_imag, axis=axis, name=name)
elif is_real(x_imag):
imag = layers.assign(x_imag)
else:
imag = layers.elementwise_add(
layers.zeros_like(x_real), y_imag, axis=axis, name=name)
return ComplexVariable(real, imag)
def elementwise_sub(x, y, axis=-1, name=None):
"""
The element-wise subtraction layer for complex number inputs. At least one of
inputs :attr:`x` and :attr:`y` must be a ComplexVariable. See the detailed
description for the function and other arguments
in :ref:`api_fluid_layers_elementwise_sub` .
Args:
x (Variable|ComplexVariable): The first input Variable or ComplexVariable
with any number of dimensions. The supported data types include float32
and float64 when it is a Variable. Otherwise the supported data types
are complex64 or complex128.
y (Variable|ComplexVariable): The second input Variable or ComplexVariable
with any number of dimensions. The supported data types include float32
and float64 when it is a Variable. Otherwise the supported data types
are complex64 or complex128.
Examples:
.. code-block:: python
import numpy as np
import paddle
import paddle.fluid.dygraph as dg
a = np.array([[1.0+1.0j, 2.0+1.0j], [3.0+1.0j, 4.0+1.0j]])
b = np.array([[5.0+2.0j, 6.0+2.0j], [7.0+2.0j, 8.0+2.0j]])
with dg.guard():
x = dg.to_variable(a)
y = dg.to_variable(b)
out = paddle.complex.elementwise_sub(x, y)
print(out.numpy())
# [[-4.-1.j -4.-1.j]
# [-4.-1.j -4.-1.j]]
"""
complex_variable_exists([x, y], "elementwise_sub")
(x_real, x_imag) = (x.real, x.imag) if is_complex(x) else (x, None)
(y_real, y_imag) = (y.real, y.imag) if is_complex(y) else (y, None)
real = layers.elementwise_sub(x_real, y_real, axis=axis, name=name)
if is_real(x_imag) and is_real(y_imag):
imag = layers.elementwise_sub(x_imag, y_imag, axis=axis, name=name)
elif is_real(x_imag):
imag = layers.assign(x_imag)
else:
imag = layers.elementwise_sub(
layers.zeros_like(x_real), y_imag, axis=axis, name=name)
return ComplexVariable(real, imag)
def elementwise_mul(x, y, axis=-1, name=None):
"""
The element-wise multiplication layer for complex number inputs. At least
one of inputs :attr:`x` and :attr:`y` must be a ComplexVariable. See the
detailed description for the function and other arguments
in :ref:`api_fluid_layers_elementwise_mul` .
Args:
x (Variable|ComplexVariable): The first input Variable or ComplexVariable
with any number of dimensions. The supported data types include float32
and float64 when it is a Variable. Otherwise the supported data types
are complex64 or complex128.
y (Variable|ComplexVariable): The second input Variable or ComplexVariable
with any number of dimensions. The supported data types include float32
and float64 when it is a Variable. Otherwise the supported data types
are complex64 or complex128.
Examples:
.. code-block:: python
import numpy as np
import paddle
import paddle.fluid.dygraph as dg
a = np.array([[1.0+1.0j, 2.0+1.0j], [3.0+1.0j, 4.0+1.0j]])
b = np.array([[5.0+2.0j, 6.0+2.0j], [7.0+2.0j, 8.0+2.0j]])
with dg.guard():
x = dg.to_variable(a)
y = dg.to_variable(b)
out = paddle.complex.elementwise_mul(x, y)
print(out.numpy())
# [[ 3. +7.j 10.+10.j]
# [19.+13.j 30.+16.j]]
"""
complex_variable_exists([x, y], "elementwise_mul")
# (a + bi)(c + di) = (ac - bd) + (bc + ad)i
(a, b) = (x.real, x.imag) if is_complex(x) else (x, None)
(c, d) = (y.real, y.imag) if is_complex(y) else (y, None)
ac = layers.elementwise_mul(a, c, axis=axis, name=name)
bd = layers.elementwise_mul(
b, d, axis=axis, name=name) if is_real(b) and is_real(d) else None
bc = layers.elementwise_mul(
b, c, axis=axis, name=name) if is_real(b) else None
ad = layers.elementwise_mul(
a, d, axis=axis, name=name) if is_real(d) else None
real = ac - bd if is_real(bd) else ac
imag = bc + ad if is_real(bc) and is_real(ad) else bc if is_real(bc) else ad
return ComplexVariable(real, imag)
def elementwise_div(x, y, axis=-1, name=None):
"""
The element-wise division layer for complex number inputs. At least one of
inputs :attr:`x` and :attr:`y` must be a ComplexVariable. See the detailed
description for the function and other arguments
in :ref:`api_fluid_layers_elementwise_div` .
Args:
x (Variable|ComplexVariable): The first input Variable or ComplexVariable
with any number of dimensions. The supported data types include float32
and float64 when it is a Variable. Otherwise the supported data types
are complex64 or complex128.
y (Variable|ComplexVariable): The second input Variable or ComplexVariable
with any number of dimensions. The supported data types include float32
and float64 when it is a Variable. Otherwise the supported data types
are complex64 or complex128.
Examples:
.. code-block:: python
import numpy as np
import paddle
import paddle.fluid.dygraph as dg
a = np.array([[1.0+1.0j, 2.0+1.0j], [3.0+1.0j, 4.0+1.0j]])
b = np.array([[5.0+2.0j, 6.0+2.0j], [7.0+2.0j, 8.0+2.0j]])
with dg.guard():
x = dg.to_variable(a)
y = dg.to_variable(b)
out = paddle.complex.elementwise_div(x, y)
print(out.numpy())
# [[0.24137931+0.10344828j 0.35 +0.05j ]
# [0.43396226+0.01886792j 0.5 +0.j ]]
"""
complex_variable_exists([x, y], "elementwise_div")
# (a + bi)/(c + di) = (a + bi)(c - di)/(c^2 + d^2)
(c, d) = (y.real, y.imag) if is_complex(y) else (y, None)
y_conj = ComplexVariable(c, -d) if is_real(d) else c
e = 1 / (layers.pow(c, 2.0) + layers.pow(d, 2.0)
) if is_real(d) else 1 / layers.pow(c, 2.0)
return elementwise_mul(
elementwise_mul(
x, y_conj, axis=axis, name=name),
e,
axis=axis,
name=name)