test_opt.py 文件源码

def test_local_log_sum_exp2():
    # Tests if the optimization works (result is correct) around 1.0

    x = tensor3('x')
    x_val = 1.0 + numpy.random.rand(4, 3, 2).astype(config.floatX) / 10.0

    f = compile_graph_log_sum_exp(x, axis=(1,))
    naive_ret = numpy.log(numpy.sum(numpy.exp(x_val), axis=1))
    optimised_ret = f(x_val)
    assert numpy.allclose(naive_ret, optimised_ret)

    # If a transpose is applied
    transpose_op = DimShuffle((False, False), (1, 0))
    f = compile_graph_log_sum_exp(x, axis=(1,), dimshuffle_op=transpose_op)
    naive_ret = numpy.log(numpy.sum(numpy.exp(x_val), axis=1).T)
    optimised_ret = f(x_val)
    assert numpy.allclose(naive_ret, optimised_ret)