human
Solve the following python programming problem given the following code:
def benchmark(n_imgs, n_channels, img_shape, n_filters, filter_shape, pad) : 
    print ((('
n_imgs: %i, n_channels: %i, img_shape: (%i, %i), ' % ((n_imgs, n_channels) + img_shape)) + ('n_filters: %i, filter_shape: (%i, %i), pad: %i' % (((n_filters,) + filter_shape) + (pad,))))) 
    padding = (pad, pad) 
    strides = (1, 1) 
    (img_h, img_w) = img_shape 
    (filter_h, filter_w) = filter_shape 
    convout_h = (((img_h + (2 * pad)) - filter_h) + 1) 
    convout_w = (((img_w + (2 * pad)) - filter_w) + 1) 
    imgs_bc01_shape = (n_imgs, n_channels, img_h, img_w) 
    filters_bc01_shape = (n_filters, n_channels, filter_h, filter_w) 
    imgs_bc01 = np.random.randn (n_imgs, n_channels, img_h, img_w) 
    imgs_c01b = np.transpose (imgs_bc01, (1, 2, 3, 0)) 
    filters_fc01 = np.random.randn (n_filters, n_channels, filter_h, filter_w) 
    filters_c01f = np.transpose (filters_fc01, (1, 2, 3, 0)) 
    convout_bc01 = np.random.randn (n_imgs, n_filters, convout_h, convout_w) 
    convout_c01b = np.transpose (convout_bc01, (1, 2, 3, 0)) 
    imgs_bc01_t = theano.shared (imgs_bc01.astype (theano.config.floatX)) 
    imgs_c01b_t = theano.shared (imgs_c01b.astype (theano.config.floatX)) 
    filters_fc01_t = theano.shared (filters_fc01.astype (theano.config.floatX)) 
    filters_c01f_t = theano.shared (filters_c01f.astype (theano.config.floatX)) 
    convout_bc01_t = theano.shared (convout_bc01.astype (theano.config.floatX)) 
    convout_c01b_t = theano.shared (convout_c01b.astype (theano.config.floatX)) 
    imgs_bc01_ca = ca.array (imgs_bc01) 
    filters_fc01_ca = ca.array (filters_fc01) 
    convout_bc01_ca = ca.array (convout_bc01) 
    print ('fprop') 
    convout_cc_op = FilterActs (stride = 1, partial_sum = 4, pad = pad) 
    convout_cc_expr = convout_cc_op (imgs_c01b_t, filters_c01f_t) 
    convout_cc_fun = theano.function ([], convout_cc_expr) 
    convout_cc = convout_cc_fun () 
    convout_cc = np.transpose (convout_cc, (3, 0, 1, 2)) 
    def convout_ca_fun() : 
        convout = ca.nnet.conv_bc01...

    
    

    Fix the buggy line: dfilters_cc_expr = dfilters_cc_op (imgs_c01b_t, convout_c01b_t, T.as_tensor_variable (dfilters_ca))
assistant
#Here is Python program to fix the buggy line: dfilters_cc_expr = dfilters_cc_op (imgs_c01b_t, convout_c01b_t, T.

dfilters_cc_expr = dfilters_cc_op (imgs_c01b_t, convout_c01b_t, T.as_tensor_variable (filter_shape))