# 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)