Function softplus

tensorrt_llm/functional.py:3463–3490

Add the softplus activation base on PyTorch definition. See https://pytorch.org/docs/stable/generated/torch.nn.functional.softplus.html#torch-nn-functional-softplus for a description of that function. Parameters: input : Tensor Input TensorRT LLM Tensor.

(input: Tensor, beta: float, threshold: float)

def softplus(input: Tensor, beta: float, threshold: float) -> Tensor:
    '''
    Add the softplus activation base on PyTorch definition.

    See https://pytorch.org/docs/stable/generated/torch.nn.functional.softplus.html#torch-nn-functional-softplus for a
    description of that function.

    Parameters:
        input : Tensor
            Input TensorRT LLM Tensor.
        beta : float
            The parameter for softplus computation.
        threshold : float
            The threshold for reverting to the linear function when input * beta > threshold

    Returns:
        The output tensor created by that layer.
    '''
    sf_layer = default_trtnet().add_activation(input.trt_tensor,
                                               trt.ActivationType.SOFTPLUS)
    sf_layer.alpha = 1 / beta
    sf_layer.beta = beta

    prod_tensor = input * beta
    result = prod_tensor > threshold

    return where(result, input, _create_tensor(sf_layer.get_output(0),
                                               sf_layer))


def outer(input: Tensor, vec2: Tensor) -> Tensor: