def make_sparse_random_conv2D(num_nonzero,
                              input_space,
                              output_space,
                              kernel_shape,
                              batch_size,
                              subsample=(1, 1),
                              border_mode='valid',
                              message="",
                              rng=None):

    raise AssertionError(
        "TODO: I think this is a bug--num_nonzero "
        "determines the total number of nonzero elements in the "
        "whole kernel stack, not the number of non-zero elements per "
        "kernel. Investigate what it's meant to do."
    )

    rng = make_np_rng(rng, default_sparse_seed,
                      which_method=['randn', 'randint'])

    W = np.zeros((output_space.num_channels, input_space.num_channels,
                  kernel_shape[0], kernel_shape[1]))

    def random_coord():
        return [rng.randint(dim) for dim in W.shape]

    for i in range(num_nonzero):
        o, ch, r, c = random_coord()
        while W[o, ch, r, c] != 0:
            o, ch, r, c = random_coord()
        W[o, ch, r, c] = rng.randn()

    W = sharedX(W)

    return Cudnn2D(
        filters=W,
        batch_size=batch_size,
        input_space=input_space,
        output_axes=output_space.axes,
        subsample=subsample,
        border_mode=border_mode,
        filters_shape=W.get_value(borrow=True).shape,
        message=message
    )
Render the list of all unique package names
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/linear/cudnn2d.py/make_sparse_random_conv2D--crossover with--dataset/ETHPy150Open mathcamp/pypicloud/pypicloud/views/simple.py/simple