.. _f-onnxfunction: module ``utils.onnx_function`` ============================== Short summary +++++++++++++ module ``onnxcustom.utils.onnx_function`` Onnx helper. :githublink:`%|py|6` Functions +++++++++ +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | function | truncated documentation | +======================================================================================================================+================================================================================================================================================================+ | :func:`_onnx_axpy ` | Returns the ONNX graph for function :math:`Y = f(X1, X2, \alpha) = \alpha X1 + X2`. | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_axpyw ` | Returns the ONNX graph for function :math:`Y, Z = f(X1, X2, G, \alpha, \beta) = (Y, Z)` where :math:`Z = \beta G + \alpha X1` ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_axpyw2 ` | Returns the ONNX graph for function :math:`Y, Z = f(X1, X2, G, \alpha, \beta) = (Y, Z)` where :math:`Z = \beta G + \alpha X1` ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_copy ` | Returns the ONNX graph for function :math:`Y = X`. | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_grad_loss_absolute_error ` | Returns the ONNX graph for function :math:`Y = f(X1, X2) = \lVert X1 - X2 \rVert` or :math:`Y = f(X1, X2) = \lVert (X1 - X2)w \rVert` ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_grad_loss_elastic_error ` | Returns the ONNX graph for function :math:`Y = f(X1, X2) = \beta \lVert X1 - X2 \rVert + \alpha \lVert X1 - X2 \rVert^2` ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_grad_loss_square_error ` | Returns the ONNX graph for function :math:`Y = f(X1, X2) = \lVert (X1 - X2) \rVert ^2` or :math:`Y = f(X1, X2) = \lVert (\sqrt{w}(X1 - X2) \rVert ^2 w` ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_grad_penalty_elastic_error ` | Returns the ONNX graph for function :math:`Y = f(W) = \beta \lVert W \rVert + \alpha \lVert W \rVert^2` *l1_weight* ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_grad_sigmoid_neg_log_loss_error ` | The function the raw scores from a classifier, uses the sigmoid function to compute probabilities, then the log function ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_grad_square_error ` | Returns the ONNX graph for the gradient of function :math:`Y = f(X1, X2) = \lVert X1 - X2 \rVert ^2` or :math:`Y = f(X1, X2) = \lVert X1 - X2 \rVert ^2 w` ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_linear_regression ` | Returns the ONNX graph for function :math:`Y = f(X, A, B) = A X + B`. | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_n_penalty_elastic_error ` | Returns the ONNX graph for function :math:`Y = f(W) = \beta \lVert W \rVert + \alpha \lVert W \rVert^2` *l1_weight* ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_square_error ` | Returns the ONNX graph for function :math:`Y = f(X1, X2) = \lVert X1 - X2 \rVert ^2` or :math:`Y = f(X1, X2) = \lVert X1 - X2 \rVert ^2 w` ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_update_penalty_elastic_error ` | Returns the ONNX graph for function :math:`Y = f(W) = W - 2 \beta W - \alpha sign(W)` *l1* is :math:`\beta` and ... | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`_onnx_zero ` | Returns the ONNX graph for function :math:`Y = X * 0`. | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`function_onnx_graph ` | Returns the ONNX graph corresponding to a function. | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ | :func:`get_supported_functions ` | Returns the list of supported function by :func:`function_onnx_graph`. | +----------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+ Documentation +++++++++++++ .. automodule:: onnxcustom.utils.onnx_function :members: :special-members: __init__ :show-inheritance: