Mlp.auto.h File Reference

#include <assert.h>
#include <stdlib.h>

Go to the source code of this file.

Macros
#define	__ae2f_MACRO_GENERATED   1
#define	__ae2f_MACRO_GENERATED   1
#define	__ae2f_MACRO_GENERATED   1
#define	ae2f_Ann_Mlp_c
#define	__ae2f_AnnMlpDel_C(a)
#define	__ae2f_AnnMlpMk_C(reterr, retmk, depth, szvector, szswap_opt, act, actderiv, lossderiv, deltastream, outcache, weight, bias, learningrate, learningrate_bias, offset, extra)
#define	__ae2f_AnnMlpMk_imp(reg_mk, prm_depth, pprm_szvector, propptr_szswap_opt, lppfn_act_opt, lppfn_actderiv_opt, pfn_lossderiv, propptr_deltastream_opt, propptr_outcache_opt, propptr_weight_opt, propptr_bias_opt, prm_learningrate, prm_learningrate_bias, prm_offset_opt, prm_extra_opt)
	Automatically allocates ae2f_AnnMlp and store its pointer at (reg_mk).m_mkbase.
#define	__ae2f_AnnMlpSz_imp(ret_sz, outc, weightc, depth, szswap, act, actderiv, deltastream, outcache, weight, bias)
#define	__ae2f_AnnMlpInitWithOutSz_imp(v_mlp, v_init, depth, outsz, weightsz, szvector, szswap_opt, act, actderiv, lossderiv, deltastream, outcache, weight, bias, learningrate, learningrate_bias)
#define	__ae2f_AnnMlpInit_imp(v_mlp, v_init, depth, szvector, szswap_opt, act, actderiv, lossderiv, deltastream, outcache, weight, bias, learningrate, learningrate_bias)
#define	__ae2f_AnnMlpPredictPrimal_imp(OPER_NEG, OPER_NONE, v_predict, mlp, inp, out, sz, weight, bias, outcache, act_opt)
	layer must be more than 2
#define	__ae2f_AnnMlpPredictPrimal(OPER_NEG, OPER_NONE, reterr, mlp, inp, out)
#define	__ae2f_AnnMlpPredictStream_imp(v_predict, mlp, inp, out, sz, weight, bias, outcache, act_opt)
#define	__ae2f_AnnMlpPredictStream_C(reterr, mlp, inp, out)
#define	__ae2f_AnnMlpPredict_imp(v_predict, mlp, inp, out, sz, weight, bias, outcache, act_opt)
#define	__ae2f_AnnMlpPredict_C(reterr, mlp, inp, delta)
#define	__ae2f_AnnMlpHidDeltaSingle_imp(v_single, slp, weight, delta, iidx)
#define	__ae2f_AnnMlpBwd_imp(v_tmp, v_send, slp_then, retdelta_then, deltaseed, actderiv_then, inp)
	delta to delta
#define	__ae2f_AnnMlpFollowStream_imp(v_follow, mlp, inp, delta, lenv, outstream, deltacache, weight, bias, lr_w, lr_b, actderiv)
#define	__ae2f_AnnMlpFollow_imp(v_follow, mlp, inp, delta, lenv, outstream, deltacache, weight, bias, lr_w, lr_b, actderiv)
#define	__ae2f_AnnMlpFollowPrimal_imp(OPER_NEG, OPER_NONE, v_follow, mlp, inp, delta, lenv, outstream, deltacache, weight, bias, learningrate, learningrate_bias, actderiv)
#define	__ae2f_AnnMlpFollowPrimal(OPER_NEG, OPER_NONE, reterr, mlp, inp, delta)
#define	__ae2f_AnnMlpFollow_C(reterr, mlp, inp, delta)
#define	__ae2f_AnnMlpFollowStream_C(reterr, mlp, inp, delta)
#define	__ae2f_AnnMlpTrainPrimal_imp(OPER_NEG, OPER_NONE, v_train, mlp, inp, out, out_desired, lenv, outstream, deltacache, weight, bias, learningrate, learningrate_bias, act, actderiv, lossderiv)
#define	__ae2f_AnnMlpTrainPrimal(OPER_NEG, OPER_NONE, reterr, mlp, inp, out, out_desired)
#define	__ae2f_AnnMlpTrainAutoPrimal(OPER_NEG, OPER_NONE, reterr, mlp, inp, out_desired)
#define	__ae2f_AnnMlpTrain_C(reterr, mlp, inp, out, out_desired)
#define	__ae2f_AnnMlpTrainStream_C(reterr, mlp, inp, out, out_desired)
#define	__ae2f_AnnMlpTrain_imp(v_train, mlp, inp, out, goal, lenv, outstream, deltacache, weight, bias, lr_w, lr_b, act, actderiv, lossderiv)
#define	__ae2f_AnnMlpTrainStream_imp(v_train, mlp, inp, out, goal, lenv, outstream, deltacache, weight, bias, lr_w, lr_b, act, actderiv, lossderiv)
#define	__ae2f_AnnMlpTrainAuto_C(reterr, mlp, inp, out_desired)
#define	__ae2f_AnnMlpTrainAutoStream_C(reterr, mlp, inp, out_desired)
#define	__ae2f_MACRO_GENERATED   0

Macro Definition Documentation

__ae2f_AnnMlpBwd_imp

#define __ae2f_AnnMlpBwd_imp	(		v_tmp,
			v_send,
			slp_then,
			retdelta_then,
			deltaseed,
			actderiv_then,
			inp )

Value:

{ \
    for((v_send) = (slp_then).m_outc; (v_send)--;) { \
        actderiv_then(&(v_tmp), inp, v_send, (slp_then).m_outc); \
        (retdelta_then)[v_send] = (v_tmp) * (deltaseed)[v_send]; \
    } \
}

delta to delta

tparam param

Definition at line 588 of file Mlp.auto.h.

__ae2f_AnnMlpDel_C

#define __ae2f_AnnMlpDel_C

(

a

)

Value:

free(ae2f_reinterpret_cast(void*, a))

Definition at line 38 of file Mlp.auto.h.

__ae2f_AnnMlpFollow_C

#define __ae2f_AnnMlpFollow_C	(		reterr,
			mlp,
			inp,
			delta )

Value:

    __ae2f_AnnMlpFollowPrimal(&1 ? 0 : 1,&1, reterr, mlp, inp, delta)

Definition at line 816 of file Mlp.auto.h.

__ae2f_AnnMlpFollow_imp

#define __ae2f_AnnMlpFollow_imp	(		v_follow,
			mlp,
			inp,
			delta,
			lenv,
			outstream,
			deltacache,
			weight,
			bias,
			lr_w,
			lr_b,
			actderiv )

Value:

    __ae2f_AnnMlpFollowPrimal_imp(&1 ? 0 : 1,&1, v_follow, mlp, inp, delta, lenv, outstream, deltacache, weight, bias, lr_w, lr_b, actderiv)

Definition at line 612 of file Mlp.auto.h.

__ae2f_AnnMlpFollowPrimal

#define __ae2f_AnnMlpFollowPrimal	(		OPER_NEG,
			OPER_NONE,
			reterr,
			mlp,
			inp,
			delta )

Value:

{ \
    if((reterr) && *(reterr)) {} \
    else unless((mlp) && (inp) && (delta)) { \
        assert(0 && "nullref"); \
        (reterr) && (*(reterr) |= ae2f_errGlob_PTR_IS_NULL); \
    } else { \
        ae2f_AnnMlpFollow_t v_follow; \
 \
        __ae2f_AnnMlpFollowPrimal_imp( \
                OPER_NEG, OPER_NONE \
                , v_follow \
                , *(mlp), inp, delta, (mlp)->m_sz \
                , (mlp)->m_outcache, (mlp)->m_deltastream \
                , (mlp)->m_weight \
                , (mlp)->m_bias \
                , (mlp)->m_learningrate, (mlp)->m_learningrate_bias \
                , (mlp)->m_actderiv \
                ); \
    } \
}

tparam param

Definition at line 785 of file Mlp.auto.h.

__ae2f_AnnMlpFollowPrimal_imp

#define __ae2f_AnnMlpFollowPrimal_imp	(		OPER_NEG,
			OPER_NONE,
			v_follow,
			mlp,
			inp,
			delta,
			lenv,
			outstream,
			deltacache,
			weight,
			bias,
			learningrate,
			learningrate_bias,
			actderiv )

tparam param

Definition at line 615 of file Mlp.auto.h.

__ae2f_AnnMlpFollowStream_C

#define __ae2f_AnnMlpFollowStream_C	(		reterr,
			mlp,
			inp,
			delta )

Value:

    __ae2f_AnnMlpFollowPrimal(-1, , reterr, mlp, inp, delta)

Definition at line 819 of file Mlp.auto.h.

__ae2f_AnnMlpFollowStream_imp

#define __ae2f_AnnMlpFollowStream_imp	(		v_follow,
			mlp,
			inp,
			delta,
			lenv,
			outstream,
			deltacache,
			weight,
			bias,
			lr_w,
			lr_b,
			actderiv )

Value:

    __ae2f_AnnMlpFollowPrimal_imp(-1,,v_follow, mlp, inp, delta, lenv, outstream, deltacache, weight, bias, lr_w, lr_b, actderiv)

Definition at line 608 of file Mlp.auto.h.

__ae2f_AnnMlpHidDeltaSingle_imp

#define __ae2f_AnnMlpHidDeltaSingle_imp	(		v_single,
			slp,
			weight,
			delta,
			iidx )

Value:

{ \
    (v_single).m_ret = 0; \
 \
    for((v_single).m_i = (slp).m_outc; (v_single).m_i--; ) \
    { \
        (v_single).m_ret += \
            ((weight) + (slp).m_inc * (v_single).m_i)[iidx] * (delta)[(v_single).m_i]; \
    } \
}

tparam param

Definition at line 566 of file Mlp.auto.h.

__ae2f_AnnMlpInit_imp

#define __ae2f_AnnMlpInit_imp	(		v_mlp,
			v_init,
			depth,
			szvector,
			szswap_opt,
			act,
			actderiv,
			lossderiv,
			deltastream,
			outcache,
			weight,
			bias,
			learningrate,
			learningrate_bias )

Value:

{ \
    (v_init).m_outc = 0; \
    (v_init).m_weightc = 0; \
 \
    assert((szvector) && "Size vector is null"); \
    for((v_init).m_i = (depth); (v_init).m_i--; ) { \
        assert((szvector)[(v_init).m_i] && "Zero value is permitted"); \
        (v_init).m_outc < (szvector)[(v_init).m_i] && ((v_init).m_outc = (szvector)[(v_init).m_i]); \
        if((v_init).m_i == (depth) - 1) continue; \
 \
        (v_init).m_weightc = \
            (v_init).m_weightc < (szvector)[(v_init).m_i] * (szvector)[(v_init).m_i + 1] ? \
            (szvector)[(v_init).m_i] * (szvector)[(v_init).m_i + 1] : \
            (v_init).m_weightc; \
    } \
 \
    __ae2f_AnnMlpInitWithOutSz_imp( \
            v_mlp, (v_init).m_i, depth, (v_mlp).m_outc, (v_mlp).m_weightc \
            , szvector, szswap_opt, act, actderiv, lossderiv \
            , deltastream, outcache, weight, bias, learningrate, learningrate_bias \
            ); \
}

tparam param

Definition at line 352 of file Mlp.auto.h.

__ae2f_AnnMlpInitWithOutSz_imp

#define __ae2f_AnnMlpInitWithOutSz_imp	(		v_mlp,
			v_init,
			depth,
			outsz,
			weightsz,
			szvector,
			szswap_opt,
			act,
			actderiv,
			lossderiv,
			deltastream,
			outcache,
			weight,
			bias,
			learningrate,
			learningrate_bias )

Value:

{ \
    assert((depth) >= 2 && "At lest you need input and output layer"); \
    (v_mlp).m_depth = (depth); \
    (v_mlp).m_outc = (outsz); \
    (v_mlp).m_weightc = (weightsz); \
 \
    assert((lossderiv) && "loss deriv is null"); \
    (v_mlp).m_lossderiv = lossderiv; \
 \
    (v_mlp).m_sz = (szswap_opt); \
    (v_mlp).m_act = (act); \
    (v_mlp).m_actderiv = (actderiv); \
 \
    (v_mlp).m_deltastream = deltastream; \
    (v_mlp).m_outcache = outcache; \
    (v_mlp).m_weight = weight; \
    (v_mlp).m_bias = bias; \
 \
    (v_mlp).m_learningrate = learningrate; \
    (v_mlp).m_learningrate_bias = learningrate_bias; \
 \
    if((szswap_opt) && (szswap_opt) != (szvector)) \
        for((v_init) = (depth); (v_init)--; ) { \
            (szswap_opt)[(v_init)] = (szvector)[(v_init)]; \
        } \
}

tparam param

Definition at line 303 of file Mlp.auto.h.

__ae2f_AnnMlpMk_C

#define __ae2f_AnnMlpMk_C	(		reterr,
			retmk,
			depth,
			szvector,
			szswap_opt,
			act,
			actderiv,
			lossderiv,
			deltastream,
			outcache,
			weight,
			bias,
			learningrate,
			learningrate_bias,
			offset,
			extra )

Value:

    { \
    if((reterr) && *(reterr)) {} \
    else unless((szvector) && (lossderiv) && (retmk)) \
        (reterr) && (*(reterr) |= ae2f_errGlob_PTR_IS_NULL); \
    else { \
        ae2f_AnnMlpMk_t v_mk; \
        __ae2f_AnnMlpMk_imp( \
                v_mk \
                , depth, szvector, szswap_opt \
                , act, actderiv, lossderiv \
                , deltastream, outcache, weight \
                , bias, learningrate, learningrate_bias \
                , offset, extra \
                ); \
 \
        assert(v_mk.m_mkbase && "Initialising has failed"); \
        *(retmk) = v_mk.m_mkbase; \
        unless(v_mk.m_mkbase) { \
            (reterr) && (*(reterr) |= ae2f_errGlob_ALLOC_FAILED); \
        } \
    } \
}

tparam param

Definition at line 40 of file Mlp.auto.h.

__ae2f_AnnMlpMk_imp

#define __ae2f_AnnMlpMk_imp	(		reg_mk,
			prm_depth,
			pprm_szvector,
			propptr_szswap_opt,
			lppfn_act_opt,
			lppfn_actderiv_opt,
			pfn_lossderiv,
			propptr_deltastream_opt,
			propptr_outcache_opt,
			propptr_weight_opt,
			propptr_bias_opt,
			prm_learningrate,
			prm_learningrate_bias,
			prm_offset_opt,
			prm_extra_opt )

Automatically allocates ae2f_AnnMlp and store its pointer at (reg_mk).m_mkbase.

If some parameter has <prop>, it means it's element(or value) will be handled by mlp in future.
> Which means it must be valid at least longer than a class newly allocated.
> Unless a parameter has <prop> with <init>, memory of the given parameter will not be initialised.

<reg> means it has state(which is mutable), and its memory does not require to be allocated linearly.

<opt> means its value could be '0', '\0', 0, 0x0, NULL, or nullptr.

<prm> means it could be primitive value, such as non-variable.

Parameters

[in,out]	reg_mk	<reg> Type: ae2f_reg ae2f_AnnMlpMk_t& Brief: A temporary buffer for this function.
	prm_depth	<prm> Type: const size_t Brief: Depth for this machine willing to allocate.
[in]	pprm_szvector	<ptr> <const> Type: const size_t[prm_depth] Brief: A shape of the model.
[out]	propptr_szswap_opt	<prop> <ptr> <opt> <init> Type: size_t[prm_depth]& Brief: Optional valid buffer for Mlp to store the value of pprm_szvector.
	lppfn_act_opt	<prop> <ptr> <fn> <opt> Type: ae2f_AnnActFFN_t[prm_depth]& Brief: Optional valid buffer for activation function for each layer.
	lppfn_actderiv_opt	<prop> <ptr> <fn> <opt> Type: ae2f_AnnActFFN_t[prm_depth]& Brief: Optional valid buffer for activation derivative for each layer.
	pfn_lossderiv	<fn> <ptr> <prm> Type: ae2f_AnnLossFFN_t Brief: Derivative of loss function for mlp model.
	propptr_deltastream_opt	<prop> <ptr> Type: ae2f_float_t[MAX(pprm_szvector) * ((prm_depth) - 1)]& Brief: Optional delta stream buffer.
	propptr_outcache_opt	<prop> <ptr> Type: ae2f_float_t[MAX(pprm_szvector) * ((prm_depth) - 1)]& Brief: Optional output stream buffer.
	propptr_weight_opt	<prop> <ptr> Type: ae2f_float_t[MAXWEIGHT(pprm_szvector) * ((prm_depth) - 1)] Brief: Optional weight buffer. Details: To compute MAXWEIGHT, you could find a max value of multiplications of each neighbour.
	propptr_bias_opt	<prop> <ptr> Type: ae2f_float_t[MAX(pprm_szvector) * ((prm_depth) - 1)]& Brief: Optional bias buffer.
	prm_learningrate	<prm> Type: const ae2f_float_t Brief: learning rate for weights.
	prm_learningrate_bias	<prm> Type: const ae2f_float_t Brief: learning rate for bias.
	prm_offset_opt	<prm> <opt> Type: const size_t Brief: Desired gap between structure itself and additional buffers as bytes.
	prm_extra_opt	<prm> <opt> Type: const size_t Brief: Desired extra buffer size as bytes.

tparam param

Definition at line 163 of file Mlp.auto.h.

__ae2f_AnnMlpPredict_C

#define __ae2f_AnnMlpPredict_C	(		reterr,
			mlp,
			inp,
			delta )

Value:

    __ae2f_AnnMlpPredictPrimal(&1 ? 0 : 1, &1, reterr, mlp, inp, delta)

Definition at line 563 of file Mlp.auto.h.

__ae2f_AnnMlpPredict_imp

#define __ae2f_AnnMlpPredict_imp	(		v_predict,
			mlp,
			inp,
			out,
			sz,
			weight,
			bias,
			outcache,
			act_opt )

Value:

    __ae2f_AnnMlpPredictPrimal_imp(&1 ? 0 : 1, &1, v_predict, mlp, inp, out, sz, weight, bias, outcache, act_opt)

Definition at line 560 of file Mlp.auto.h.

__ae2f_AnnMlpPredictPrimal

#define __ae2f_AnnMlpPredictPrimal	(		OPER_NEG,
			OPER_NONE,
			reterr,
			mlp,
			inp,
			out )

Value:

{ \
    if((reterr) && *(reterr)) \
        ; \
    else unless((mlp) && (inp) && (out)) { \
        assert(0 && "Null"); \
        (reterr) && (*(reterr) |= ae2f_errGlob_PTR_IS_NULL); \
    } else { \
        ae2f_AnnMlpPredict_t v_predict; \
 \
        __ae2f_AnnMlpPredictPrimal_imp( \
                OPER_NEG, OPER_NONE \
                , v_predict, *(mlp) \
                , inp, out \
                , (mlp)->m_sz, (mlp)->m_weight \
                , (mlp)->m_bias, (mlp)->m_outcache \
                , (mlp)->m_act \
                ); \
    } \
}

tparam param

Definition at line 524 of file Mlp.auto.h.

__ae2f_AnnMlpPredictPrimal_imp

#define __ae2f_AnnMlpPredictPrimal_imp	(		OPER_NEG,
			OPER_NONE,
			v_predict,
			mlp,
			inp,
			out,
			sz,
			weight,
			bias,
			outcache,
			act_opt )

layer must be more than 2

tparam param

Definition at line 397 of file Mlp.auto.h.

__ae2f_AnnMlpPredictStream_C

#define __ae2f_AnnMlpPredictStream_C	(		reterr,
			mlp,
			inp,
			out )

Value:

    __ae2f_AnnMlpPredictPrimal(-1, , reterr, mlp, inp, out)

Definition at line 557 of file Mlp.auto.h.

__ae2f_AnnMlpPredictStream_imp

#define __ae2f_AnnMlpPredictStream_imp	(		v_predict,
			mlp,
			inp,
			out,
			sz,
			weight,
			bias,
			outcache,
			act_opt )

Value:

    __ae2f_AnnMlpPredictPrimal_imp(-1, , v_predict, mlp, inp, out, sz, weight, bias, outcache, act_opt)

Definition at line 554 of file Mlp.auto.h.

__ae2f_AnnMlpSz_imp

#define __ae2f_AnnMlpSz_imp	(		ret_sz,
			outc,
			weightc,
			depth,
			szswap,
			act,
			actderiv,
			deltastream,
			outcache,
			weight,
			bias )

Value:

{ \
    assert((depth) > 2); \
 \
    (ret_sz) = sizeof(ae2f_AnnMlp) + (!(szswap)) * sizeof(size_t); \
    (ret_sz) += (sizeof(void*) * ((depth) - 1)) * (!(act) + !(actderiv)); \
    (ret_sz) += sizeof(ae2f_float_t) \
        * ((depth)) * (outc) \
        * ( \
                !(deltastream) + !(outcache) + !(bias) \
          ); \
    (ret_sz) += sizeof(ae2f_float_t) \
        * (!(weight) * (weightc) * (depth)); \
}

tparam param

Definition at line 272 of file Mlp.auto.h.

__ae2f_AnnMlpTrain_C

#define __ae2f_AnnMlpTrain_C	(		reterr,
			mlp,
			inp,
			out,
			out_desired )

Value:

    __ae2f_AnnMlpTrainPrimal(&1 ? 0 : 1, &1, reterr, mlp, inp, out, out_desired)

Definition at line 947 of file Mlp.auto.h.

__ae2f_AnnMlpTrain_imp

#define __ae2f_AnnMlpTrain_imp	(		v_train,
			mlp,
			inp,
			out,
			goal,
			lenv,
			outstream,
			deltacache,
			weight,
			bias,
			lr_w,
			lr_b,
			act,
			actderiv,
			lossderiv )

Value:

    __ae2f_AnnMlpTrainPrimal_imp(&1 ? 0 : 1, &1, v_train, mlp, inp, out, goal, lenv, outstream, deltacache, weight, bias, lr_w, lr_b, act, actderiv, lossderiv)

Definition at line 953 of file Mlp.auto.h.

__ae2f_AnnMlpTrainAuto_C

#define __ae2f_AnnMlpTrainAuto_C	(		reterr,
			mlp,
			inp,
			out_desired )

Value:

    __ae2f_AnnMlpTrainAutoPrimal(&1 ? 0 : 1, &1, reterr, mlp, inp, out_desired)

See also

__ae2f_AnnMlpTrainAutoPrimal

Definition at line 961 of file Mlp.auto.h.

__ae2f_AnnMlpTrainAutoPrimal

#define __ae2f_AnnMlpTrainAutoPrimal	(		OPER_NEG,
			OPER_NONE,
			reterr,
			mlp,
			inp,
			out_desired )

Value:

{ \
    if((reterr) && *(reterr)); \
    else unless((mlp) && (out_desired) && (inp)) { \
        assert(0 && "nullref"); \
        (reterr) && (*(reterr) |= ae2f_errGlob_PTR_IS_NULL); \
    } else { \
        ae2f_AnnMlpTrain_t v_train; \
        __ae2f_AnnMlpTrainPrimal_imp( \
                OPER_NEG, OPER_NONE \
                , v_train, *(mlp), inp \
                , &(mlp)->m_outcache[((mlp)->m_outc) * ((mlp)->m_depth - 2)] \
                , out_desired \
                , (mlp)->m_sz, (mlp)->m_outcache \
                , (mlp)->m_deltastream \
                , (mlp)->m_weight, (mlp)->m_bias \
                , (mlp)->m_learningrate, (mlp)->m_learningrate_bias \
                , (mlp)->m_act, (mlp)->m_actderiv, (mlp)->m_lossderiv \
                ); \
    } \
}

tparam param

Definition at line 915 of file Mlp.auto.h.

__ae2f_AnnMlpTrainAutoStream_C

#define __ae2f_AnnMlpTrainAutoStream_C	(		reterr,
			mlp,
			inp,
			out_desired )

Value:

    __ae2f_AnnMlpTrainAutoPrimal(-1, ae2f_NONE, reterr, mlp, inp, out_desired)

See also

__ae2f_AnnMlpTrainAutoPrimal

Definition at line 965 of file Mlp.auto.h.

__ae2f_AnnMlpTrainPrimal

#define __ae2f_AnnMlpTrainPrimal	(		OPER_NEG,
			OPER_NONE,
			reterr,
			mlp,
			inp,
			out,
			out_desired )

Value:

{ \
    if((reterr) && *(reterr)); \
    else unless((mlp) && (out) && (out_desired) && (inp)) { \
        assert(0 && "nullref"); \
        (reterr) && (*(reterr) |= ae2f_errGlob_PTR_IS_NULL); \
    } else { \
        ae2f_AnnMlpTrain_t v_train; \
        __ae2f_AnnMlpTrainPrimal_imp( \
                OPER_NEG, OPER_NONE \
                , v_train, *(mlp), inp \
                , out, out_desired \
                , (mlp)->m_sz, (mlp)->m_outcache \
                , (mlp)->m_deltastream \
                , (mlp)->m_weight, (mlp)->m_bias \
                , (mlp)->m_learningrate, (mlp)->m_learningrate_bias \
                , (mlp)->m_act, (mlp)->m_actderiv, (mlp)->m_lossderiv \
                ); \
    } \
}

tparam param

Definition at line 884 of file Mlp.auto.h.

__ae2f_AnnMlpTrainPrimal_imp

#define __ae2f_AnnMlpTrainPrimal_imp	(		OPER_NEG,
			OPER_NONE,
			v_train,
			mlp,
			inp,
			out,
			out_desired,
			lenv,
			outstream,
			deltacache,
			weight,
			bias,
			learningrate,
			learningrate_bias,
			act,
			actderiv,
			lossderiv )

tparam param

Definition at line 822 of file Mlp.auto.h.

__ae2f_AnnMlpTrainStream_C

#define __ae2f_AnnMlpTrainStream_C	(		reterr,
			mlp,
			inp,
			out,
			out_desired )

Value:

    __ae2f_AnnMlpTrainPrimal(&1 ? 0 : 1, ae2f_NONE, reterr, mlp, inp, out, out_desired)

Definition at line 950 of file Mlp.auto.h.

__ae2f_AnnMlpTrainStream_imp

#define __ae2f_AnnMlpTrainStream_imp	(		v_train,
			mlp,
			inp,
			out,
			goal,
			lenv,
			outstream,
			deltacache,
			weight,
			bias,
			lr_w,
			lr_b,
			act,
			actderiv,
			lossderiv )

Value:

    __ae2f_AnnMlpTrainPrimal_imp(-1, ae2f_NONE, v_train, mlp, inp, out, goal, lenv, outstream, deltacache, weight, bias, lr_w, lr_b, act, actderiv, lossderiv)

Definition at line 956 of file Mlp.auto.h.

__ae2f_MACRO_GENERATED [1/4]

#define __ae2f_MACRO_GENERATED   1

Definition at line 2 of file Mlp.auto.h.

__ae2f_MACRO_GENERATED [2/4]

#define __ae2f_MACRO_GENERATED   1

Definition at line 2 of file Mlp.auto.h.

__ae2f_MACRO_GENERATED [3/4]

#define __ae2f_MACRO_GENERATED   1

Definition at line 2 of file Mlp.auto.h.

__ae2f_MACRO_GENERATED [4/4]

#define __ae2f_MACRO_GENERATED   0

Definition at line 2 of file Mlp.auto.h.

ae2f_Ann_Mlp_c

#define ae2f_Ann_Mlp_c

Definition at line 36 of file Mlp.auto.h.