maxpool.py 文件源码

def compile_maxpool(output_shape, pool_size):

    X = T.tensor4()

    # compute output with both methods
    out1 = T.signal.pool.pool_2d(X, pool_size,
                                 ignore_border=True, st=None,
                                 padding=(0, 0), mode='max')

    out2 = my_pool_2d(X, pool_size,
                      ignore_border=True, st=None,
                      padding=(0, 0), mode='max')

    # compute gradient with random incoming gradient for both cases
    incoming_grad = T.as_tensor_variable(np.random.random(size=output_shape)
                                         .astype(np.float32))
    grad1 = T.grad(None, wrt=X, known_grads={out1: incoming_grad})
    grad2 = T.grad(None, wrt=X, known_grads={out2: incoming_grad})

    return theano.function([X], [out1, out2, grad1, grad2])