bilinear¶

paddle.nn.functional. bilinear ( x1, x2, weight, bias=None, name=None ) [source]

This layer performs bilinear on two inputs. See api_nn_Bilinear for details and output shape.

Parameters

• x1 (Tensor) – the first input tensor, it’s data type should be float32, float64.

• x2 (Tensor) – the second input tensor, it’s data type should be float32, float64.

• weight (Parameter) – The learnable weights of this layer, shape is [out_features, in1_features, in2_features].

• bias (Parameter, optional) – The learnable bias(Bias) of this layer, shape is [1, out_features]. If it is set to None, no bias will be added to the output units. The default value is None.

• name (str, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name. Default: None.

Returns

A 2-D Tensor of shape [batch_size, out_features].

Return type

Tensor

Examples

import paddle
import numpy
import paddle.nn.functional as F

x1 = numpy.random.random((5, 5)).astype('float32')
x2 = numpy.random.random((5, 4)).astype('float32')
w = numpy.random.random((1000, 5, 4)).astype('float32')
b = numpy.random.random((1, 1000)).astype('float32')

result = F.bilinear(paddle.to_tensor(x1), paddle.to_tensor(x2), paddle.to_tensor(w), paddle.to_tensor(b))           # result shape [5, 1000]