ThresholdedRelu#
ThresholdedRelu - 10#
Version
name: ThresholdedRelu (GitHub)
domain: main
since_version: 10
function: False
support_level: SupportType.COMMON
shape inference: True
This version of the operator has been available since version 10.
Summary
ThresholdedRelu takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the rectified linear function, y = x for x > alpha, y = 0 otherwise, is applied to the tensor elementwise.
Attributes
alpha: Threshold value Default value is
1.0.
Inputs
X (heterogeneous) - T: Input tensor
Outputs
Y (heterogeneous) - T: Output tensor
Type Constraints
T in ( tensor(double), tensor(float), tensor(float16) ): Constrain input and output types to float tensors.
Examples
default
default_alpha = 1.0
node = onnx.helper.make_node(
'ThresholdedRelu',
inputs=['x'],
outputs=['y']
)
x = np.random.randn(3, 4, 5).astype(np.float32)
y = np.clip(x, default_alpha, np.inf)
y[y == default_alpha] = 0
expect(node, inputs=[x], outputs=[y],
name='test_thresholdedrelu_default')