util.py 文件源码

def res5b_2_res5c_branch2a(res5b_res5b_relu_0_split_0, conv_params, bn_params):
    assert res5b_res5b_relu_0_split_0.ndim == 4
    res5c_branch2a = conv2d(input=res5b_res5b_relu_0_split_0, filters=conv_params['res5c_branch2a_0'], border_mode='valid', filter_flip=False)
    bn5c_branch2a = (res5c_branch2a - bn_params['bn5c_branch2a_0'].dimshuffle('x', 0, 'x', 'x')) / tensor.sqrt(bn_params['bn5c_branch2a_1'].dimshuffle('x', 0, 'x', 'x') + numpy.float32(1e-5))
    scale5c_branch2a = bn5c_branch2a * bn_params['scale5c_branch2a_0'].dimshuffle('x', 0, 'x', 'x') + bn_params['scale5c_branch2a_1'].dimshuffle('x', 0, 'x', 'x')
    res5c_branch2a_relu = tensor.nnet.relu(scale5c_branch2a, alpha=0.0)

    return res5c_branch2a_relu