thresholded_relu
paddle.fluid.layers.
thresholded_relu
(x, threshold=None)[源代码]
逐元素计算 ThresholdedRelu激活函数。
- 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)
- # 动态图使用
- 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.thresholded_relu(x, threshold=0.1)
- y_np = y.numpy()
- 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)