def __init__(self):
self.convs = [
conv.Convolver(0, 0, 1, 1),
conv.Convolver(2, 2, 1, 1),
]
self.poolings = [
conv.Pooler(2, 2, 2, 2, 0, 0, conv.pool_op.max),
conv.Pooler(3, 3, 3, 3, 0, 0, conv.pool_op.max)
]
def __init__(self):
self.convs = [
co.Convolver(0, 0, 4, 4), # conv1
co.Convolver(2, 2, 1, 1), # conv2
co.Convolver(1, 1, 1, 1), # conv3
co.Convolver(1, 1, 1, 1), # conv4
co.Convolver(1, 1, 1, 1) # conv5
]
self.poolings = [
co.Pooler(3, 3, 2, 2, co.pool_op.max), # pool1
co.Pooler(3, 3, 2, 2, co.pool_op.max), # pool2
co.Pooler(3, 3, 2, 2, co.pool_op.max) # pool5
]
def __init__(self, params):
super(ConvConnection, self).__init__(params)
self.conv_params = params.convolution_param
self.convolver = co.Convolver(self.conv_params.pad,
self.conv_params.pad,
self.conv_params.stride,
self.conv_params.stride)
def __init__(self, params):
super(ConvConnection, self).__init__(params)
self.conv_params = params.convolution_param
self.convolver = co.Convolver(self.conv_params.pad,
self.conv_params.pad,
self.conv_params.stride,
self.conv_params.stride)
self.convolution_param = params.convolution_param
self.num_output = params.convolution_param.num_output
self.group = params.convolution_param.group
#TODO: hack, we don't want to slice agian to use it into bp as a parameter
self.group_data = []
self.group_filter = []
self.group_bias = []
import owl import owl.conv as co import numpy as np import demo_common x = owl.randn([227, 227, 3, 256], 0.0, 1) w = owl.randn([11, 11, 3, 96], 0.0, 0.1) b = owl.zeros([96]) conv = co.Convolver(pad_h=0, pad_w=0, stride_v=4, stride_h=4) y = conv.ff(x, w, b) print y.to_numpy() print y.shape ex = conv.bp(y, w) print ex.to_numpy() print ex.shape
