In this article Syntax Return Value Remarks Example A predefined function object that performs the modulus division operation (operator%) on its arguments.SyntaxC++ Copy template <class Type = void> struct modulus : public binary_function <Type, Type, Type> { ...
second_argument_type(deprecated in C++17)(removed in C++20)T These member types are obtained via publicly inheritingstd::binary_function<T, T, T>. (until C++11) Member functions operator() returns the remainder from the division of the first argument by the second argument ...
[docs]classLossL2(Function): [docs]@staticmethoddefforward(ctx,pred_outvar:Tensor,true_outvar:Tensor,lambda_weighting:Tensor,area:Tensor,):ctx.save_for_backward(pred_outvar,true_outvar,lambda_weighting,area)loss=pde_cpp.l2_loss_forward(pred_outvar,true_outvar,lambda_weighting,area)returnloss ...
The multiplicative operators take operands of arithmetic types. The modulus operator (%) has a stricter requirement in that its operands must be of integral type. (To get the remainder of a floating-point division, use the run-time function,fmod.) The conversions covered inStandard Conversionsare...
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In this article Syntax Return Value Remarks Example A predefined function object that performs the modulus division operation (operator%) on its arguments.SyntaxC++ Copy template <class Type = void> struct modulus : public binary_function <Type, Type, Type> { ...
[docs]classLossL2(Function): [docs]@staticmethoddefforward(ctx,pred_outvar:Tensor,true_outvar:Tensor,lambda_weighting:Tensor,area:Tensor,):ctx.save_for_backward(pred_outvar,true_outvar,lambda_weighting,area)loss=pde_cpp.l2_loss_forward(pred_outvar,true_outvar,lambda_weighting,area)returnloss ...
In this article Syntax Return Value Remarks Example A predefined function object that performs the modulus division operation (operator%) on its arguments.SyntaxC++ Copy template <class Type = void> struct modulus : public binary_function <Type, Type, Type> { ...
[docs]classLossL2(Function): [docs]@staticmethoddefforward(ctx,pred_outvar:Tensor,true_outvar:Tensor,lambda_weighting:Tensor,area:Tensor,):ctx.save_for_backward(pred_outvar,true_outvar,lambda_weighting,area)loss=pde_cpp.l2_loss_forward(pred_outvar,true_outvar,lambda_weighting,area)returnloss ...