.. _cn_api_fluid_layers_erf: erf ------------------------------- .. py:function:: paddle.fluid.layers.erf(x) 逐元素计算 Erf 激活函数。更多细节请参考 `Error function `_ 。 .. math:: out = \frac{2}{\sqrt{\pi}} \int_{0}^{x}e^{- \eta^{2}}d\eta 参数: - **x** (Variable) - Erf Op 的输入,多维 Tensor 或 LoDTensor,数据类型为 float16, float32 或 float64。 返回: - 多维 Tensor 或 LoDTensor, 数据类型为 float16, float32 或 float64, 和输入 x 的数据类型相同,形状和输入 x 相同。 返回类型: - Variable **代码示例**: .. code-block:: python # declarative mode import numpy as np from paddle import fluid x = fluid.data(name="x", shape=(-1, 3), dtype="float32") y = fluid.layers.erf(x) place = fluid.CPUPlace() exe = fluid.Executor(place) start = fluid.default_startup_program() main = fluid.default_main_program() data = np.random.randn(2, 3).astype("float32") exe.run(start) y_np, = exe.run(main, feed={"x": data}, fetch_list=[y]) data # array([[ 0.4643714 , -1.1509596 , 1.2538221 ], # [ 0.34369683, 0.27478245, 1.1805398 ]], dtype=float32) y_np # array([[ 0.48863927, -0.8964121 , 0.9237998 ], # [ 0.37307587, 0.30242872, 0.9049887 ]], dtype=float32) .. code-block:: python # imperative mode import numpy as np from paddle import fluid import paddle.fluid.dygraph as dg data = np.random.randn(2, 3).astype("float32") place = fluid.CPUPlace() with dg.guard(place) as g: x = dg.to_variable(data) y = fluid.layers.erf(x) y_np = y.numpy() data # array([[ 0.4643714 , -1.1509596 , 1.2538221 ], # [ 0.34369683, 0.27478245, 1.1805398 ]], dtype=float32) y_np # array([[ 0.48863927, -0.8964121 , 0.9237998 ], # [ 0.37307587, 0.30242872, 0.9049887 ]], dtype=float32)