thresholded_relu¶

paddle.fluid.layers. thresholded_relu ( x, threshold=None ) [源代码] ¶

逐元素计算 ThresholdedRelu激活函数。

\[\begin{split}out = \left\{\begin{matrix} x, &if x > threshold\\ 0, &otherwise \end{matrix}\right.\end{split}\]

参数¶

x (Variable) -ThresholdedRelu Op 的输入，多维 Tensor 或 LoDTensor，数据类型为 float32，float64。

threshold (float，可选)-激活函数的 threshold 值，如 threshold 值为 None，则其值为 1.0。

返回¶

多维 Tensor 或 LoDTensor，数据类型为 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¶

          # 静态图使用
import numpy as np
from paddle import fluid

x = fluid.data(name="x", shape=(-1, 3), dtype="float32")
y = fluid.layers.thresholded_relu(x, threshold=0.1)

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([[ 0.21134382, -1.1805999 ,  0.32876605],
#        [-1.2210793 , -0.7365624 ,  1.0013918 ]], dtype=float32)
y_np
# array([[ 0.21134382, -0.        ,  0.32876605],
#        [-0.        , -0.        ,  1.0013918 ]], dtype=float32)

         

          # declarative mode
import numpy as np
from paddle import fluid

x = fluid.data(name="x", shape=(-1, 3), dtype="float32")
y = fluid.layers.thresholded_relu(x, threshold=0.1)

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([[ 0.21134382, -1.1805999 ,  0.32876605],
#        [-1.2210793 , -0.7365624 ,  1.0013918 ]], dtype=float32)
y_np
# array([[ 0.21134382, -0.        ,  0.32876605],
#        [-0.        , -0.        ,  1.0013918 ]], dtype=float32)

         