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fix code style (#529)
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7 files changed

+155
-158
lines changed

7 files changed

+155
-158
lines changed

‎dpnp/backend/include/dpnp_iface_random.hpp

Lines changed: 0 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -310,7 +310,6 @@ INP_DLLEXPORT void dpnp_rng_power_c(void* result, double alpha, size_t size);
310310
template <typename _DataType>
311311
INP_DLLEXPORT void dpnp_rng_rayleigh_c(void* result, _DataType scale, size_t size);
312312

313-
314313
/**
315314
* @ingroup BACKEND_RANDOM_API
316315
* @brief initializer for basic random number generator.
@@ -350,7 +349,6 @@ INP_DLLEXPORT void dpnp_rng_standard_exponential_c(void* result, size_t size);
350349
template <typename _DataType>
351350
INP_DLLEXPORT void dpnp_rng_standard_gamma_c(void* result, _DataType shape, size_t size);
352351

353-
354352
/**
355353
* @ingroup BACKEND_RANDOM_API
356354
* @brief math library implementation of random number generator (standard normal distribution)

‎dpnp/backend/kernels/dpnp_krnl_random.cpp

Lines changed: 53 additions & 59 deletions
Original file line numberDiff line numberDiff line change
@@ -92,8 +92,8 @@ void dpnp_rng_beta_c(void* result, _DataType a, _DataType b, size_t size)
9292
}
9393
else
9494
{
95-
int errcode = vdRngBeta(VSL_RNG_METHOD_BETA_CJA, get_rng_stream(), size,
96-
result1, a, b, displacement, scalefactor);
95+
int errcode =
96+
vdRngBeta(VSL_RNG_METHOD_BETA_CJA, get_rng_stream(), size, result1, a, b, displacement, scalefactor);
9797
if (errcode != VSL_STATUS_OK)
9898
{
9999
throw std::runtime_error("DPNP RNG Error: dpnp_rng_beta_c() failed.");
@@ -121,8 +121,7 @@ void dpnp_rng_binomial_c(void* result, int ntrial, double p, size_t size)
121121
}
122122
else
123123
{
124-
int errcode = viRngBinomial(VSL_RNG_METHOD_BINOMIAL_BTPE, get_rng_stream(),
125-
size, result1, ntrial, p);
124+
int errcode = viRngBinomial(VSL_RNG_METHOD_BINOMIAL_BTPE, get_rng_stream(), size, result1, ntrial, p);
126125
if (errcode != VSL_STATUS_OK)
127126
{
128127
throw std::runtime_error("DPNP RNG Error: dpnp_rng_binomial_c() failed.");
@@ -148,8 +147,7 @@ void dpnp_rng_chi_square_c(void* result, int df, size_t size)
148147
}
149148
else
150149
{
151-
int errcode = vdRngChiSquare(VSL_RNG_METHOD_CHISQUARE_CHI2GAMMA, get_rng_stream(),
152-
size, result1, df);
150+
int errcode = vdRngChiSquare(VSL_RNG_METHOD_CHISQUARE_CHI2GAMMA, get_rng_stream(), size, result1, df);
153151
if (errcode != VSL_STATUS_OK)
154152
{
155153
throw std::runtime_error("DPNP RNG Error: dpnp_rng_chi_square_c() failed.");
@@ -187,9 +185,9 @@ void dpnp_rng_f_c(void* result, const _DataType df_num, const _DataType df_den,
187185

188186
const _DataType d_zero = (_DataType(0.0));
189187

190-
_DataType shape = 0.5*df_num;
191-
_DataType scale = 2.0/df_num;
192-
_DataType *den = nullptr;
188+
_DataType shape = 0.5 * df_num;
189+
_DataType scale = 2.0 / df_num;
190+
_DataType* den = nullptr;
193191

194192
_DataType* result1 = reinterpret_cast<_DataType*>(result);
195193

@@ -204,35 +202,33 @@ void dpnp_rng_f_c(void* result, const _DataType df_num, const _DataType df_den,
204202
{
205203
throw std::runtime_error("DPNP RNG Error: dpnp_rng_f_c() failed.");
206204
}
207-
shape = 0.5*df_den;
208-
scale = 2.0/df_den;
205+
shape = 0.5 * df_den;
206+
scale = 2.0 / df_den;
209207
mkl_rng::gamma<_DataType> gamma_distribution2(shape, d_zero, scale);
210208
event_out = mkl_rng::generate(gamma_distribution2, DPNP_RNG_ENGINE, size, den);
211209
event_out.wait();
212210

213-
event_out = mkl_vm::div(DPNP_QUEUE, size, result1, den, result1, no_deps,
214-
mkl_vm::mode::ha);
211+
event_out = mkl_vm::div(DPNP_QUEUE, size, result1, den, result1, no_deps, mkl_vm::mode::ha);
215212
event_out.wait();
216213

217214
dpnp_memory_free_c(den);
218215
}
219216
else
220217
{
221-
int errcode = vdRngGamma(VSL_RNG_METHOD_GAMMA_GNORM_ACCURATE, get_rng_stream(),
222-
size, result1, shape, d_zero, scale);
218+
int errcode =
219+
vdRngGamma(VSL_RNG_METHOD_GAMMA_GNORM_ACCURATE, get_rng_stream(), size, result1, shape, d_zero, scale);
223220
if (errcode != VSL_STATUS_OK)
224221
{
225222
throw std::runtime_error("DPNP RNG Error: dpnp_rng_f_c() failed.");
226223
}
227-
den = (_DataType *) mkl_malloc(size * sizeof(_DataType), 64);
224+
den = (_DataType*)mkl_malloc(size * sizeof(_DataType), 64);
228225
if (den == nullptr)
229226
{
230227
throw std::runtime_error("DPNP RNG Error: dpnp_rng_f_c() failed.");
231228
}
232-
shape = 0.5*df_den;
233-
scale = 2.0/df_den;
234-
errcode = vdRngGamma(VSL_RNG_METHOD_GAMMA_GNORM_ACCURATE, get_rng_stream(),
235-
size, den, shape, d_zero, scale);
229+
shape = 0.5 * df_den;
230+
scale = 2.0 / df_den;
231+
errcode = vdRngGamma(VSL_RNG_METHOD_GAMMA_GNORM_ACCURATE, get_rng_stream(), size, den, shape, d_zero, scale);
236232
if (errcode != VSL_STATUS_OK)
237233
{
238234
throw std::runtime_error("DPNP RNG Error: dpnp_rng_f_c() failed.");
@@ -264,8 +260,7 @@ void dpnp_rng_gamma_c(void* result, _DataType shape, _DataType scale, size_t siz
264260
}
265261
else
266262
{
267-
int errcode = vdRngGamma(VSL_RNG_METHOD_GAMMA_GNORM, get_rng_stream(), size,
268-
result1, shape, a, scale);
263+
int errcode = vdRngGamma(VSL_RNG_METHOD_GAMMA_GNORM, get_rng_stream(), size, result1, shape, a, scale);
269264
if (errcode != VSL_STATUS_OK)
270265
{
271266
throw std::runtime_error("DPNP RNG Error: dpnp_rng_gamma_c() failed.");
@@ -343,8 +338,7 @@ void dpnp_rng_hypergeometric_c(void* result, int l, int s, int m, size_t size)
343338
}
344339
else
345340
{
346-
int errcode = viRngHypergeometric(VSL_RNG_METHOD_HYPERGEOMETRIC_H2PE, get_rng_stream(),
347-
size, result1, l, s, m);
341+
int errcode = viRngHypergeometric(VSL_RNG_METHOD_HYPERGEOMETRIC_H2PE, get_rng_stream(), size, result1, l, s, m);
348342
if (errcode != VSL_STATUS_OK)
349343
{
350344
throw std::runtime_error("DPNP RNG Error: dpnp_rng_hypergeometric_c() failed.");
@@ -386,9 +380,11 @@ void dpnp_rng_logistic_c(void* result, double loc, double scale, size_t size)
386380
auto event_out = mkl_rng::generate(distribution, DPNP_RNG_ENGINE, size, result1);
387381
event_out.wait();
388382

389-
for(size_t i = 0; i < size; i++) result1[i] = log(result1[i]/(1.0 - result1[i]));
383+
for (size_t i = 0; i < size; i++)
384+
result1[i] = log(result1[i] / (1.0 - result1[i]));
390385

391-
for(size_t i = 0; i < size; i++) result1[i] = loc + scale * result1[i];
386+
for (size_t i = 0; i < size; i++)
387+
result1[i] = loc + scale * result1[i];
392388
}
393389

394390
template <typename _DataType>
@@ -411,11 +407,7 @@ void dpnp_rng_lognormal_c(void* result, _DataType mean, _DataType stddev, size_t
411407
}
412408

413409
template <typename _DataType>
414-
void dpnp_rng_multinomial_c(void* result,
415-
int ntrial,
416-
const double* p_vector,
417-
const size_t p_vector_size,
418-
size_t size)
410+
void dpnp_rng_multinomial_c(void* result, int ntrial, const double* p_vector, const size_t p_vector_size, size_t size)
419411
{
420412
if (!size)
421413
{
@@ -438,8 +430,8 @@ void dpnp_rng_multinomial_c(void* result,
438430
}
439431
else
440432
{
441-
int errcode = viRngMultinomial(VSL_RNG_METHOD_MULTINOMIAL_MULTPOISSON, get_rng_stream(),
442-
n, result1, ntrial, p_vector_size, p_vector);
433+
int errcode = viRngMultinomial(
434+
VSL_RNG_METHOD_MULTINOMIAL_MULTPOISSON, get_rng_stream(), n, result1, ntrial, p_vector_size, p_vector);
443435
if (errcode != VSL_STATUS_OK)
444436
{
445437
throw std::runtime_error("DPNP RNG Error: dpnp_rng_multinomial_c() failed.");
@@ -478,8 +470,14 @@ void dpnp_rng_multivariate_normal_c(void* result,
478470
}
479471
else
480472
{
481-
int errcode = vdRngGaussianMV(VSL_RNG_METHOD_GAUSSIANMV_BOXMULLER2, get_rng_stream(),
482-
size1, result1, dimen, VSL_MATRIX_STORAGE_FULL, mean_vector, cov_vector );
473+
int errcode = vdRngGaussianMV(VSL_RNG_METHOD_GAUSSIANMV_BOXMULLER2,
474+
get_rng_stream(),
475+
size1,
476+
result1,
477+
dimen,
478+
VSL_MATRIX_STORAGE_FULL,
479+
mean_vector,
480+
cov_vector);
483481
if (errcode != VSL_STATUS_OK)
484482
{
485483
throw std::runtime_error("DPNP RNG Error: dpnp_rng_multivariate_normal_c() failed.");
@@ -505,8 +503,7 @@ void dpnp_rng_negative_binomial_c(void* result, double a, double p, size_t size)
505503
}
506504
else
507505
{
508-
int errcode = viRngNegbinomial(VSL_RNG_METHOD_NEGBINOMIAL_NBAR, get_rng_stream(),
509-
size, result1, a, p);
506+
int errcode = viRngNegbinomial(VSL_RNG_METHOD_NEGBINOMIAL_NBAR, get_rng_stream(), size, result1, a, p);
510507
if (errcode != VSL_STATUS_OK)
511508
{
512509
throw std::runtime_error("DPNP RNG Error: dpnp_rng_negative_binomial_c() failed.");
@@ -540,7 +537,7 @@ void dpnp_rng_pareto_c(void* result, double alpha, size_t size)
540537

541538
const _DataType d_zero = _DataType(0.0);
542539
const _DataType d_one = _DataType(1.0);
543-
_DataType neg_rec_alp = -1.0/alpha;
540+
_DataType neg_rec_alp = -1.0 / alpha;
544541

545542
_DataType* result1 = reinterpret_cast<_DataType*>(result);
546543

@@ -578,16 +575,15 @@ void dpnp_rng_power_c(void* result, double alpha, size_t size)
578575

579576
const _DataType d_zero = _DataType(0.0);
580577
const _DataType d_one = _DataType(1.0);
581-
_DataType neg_rec_alp = 1.0/alpha;
578+
_DataType neg_rec_alp = 1.0 / alpha;
582579

583580
_DataType* result1 = reinterpret_cast<_DataType*>(result);
584581

585582
mkl_rng::uniform<_DataType> distribution(d_zero, d_one);
586583
auto event_out = mkl_rng::generate(distribution, DPNP_RNG_ENGINE, size, result1);
587584
event_out.wait();
588585

589-
event_out = mkl_vm::powx(DPNP_QUEUE, size, result1, neg_rec_alp,
590-
result1, no_deps, mkl_vm::mode::ha);
586+
event_out = mkl_vm::powx(DPNP_QUEUE, size, result1, neg_rec_alp, result1, no_deps, mkl_vm::mode::ha);
591587
event_out.wait();
592588
}
593589

@@ -606,7 +602,7 @@ void dpnp_rng_rayleigh_c(void* result, _DataType scale, size_t size)
606602

607603
_DataType* result1 = reinterpret_cast<_DataType*>(result);
608604

609-
mkl_rng::exponential<_DataType> distribution(a, beta);;
605+
mkl_rng::exponential<_DataType> distribution(a, beta);
610606

611607
auto event_out = mkl_rng::generate(distribution, DPNP_RNG_ENGINE, size, result1);
612608
event_out.wait();
@@ -615,7 +611,10 @@ void dpnp_rng_rayleigh_c(void* result, _DataType scale, size_t size)
615611
// with MKL
616612
// event_out = mkl_blas::axpy(DPNP_QUEUE, size, scale, result1, 1, result1, 1);
617613
// event_out.wait();
618-
for(size_t i = 0; i < size; i++) result1[i] *= scale;
614+
for (size_t i = 0; i < size; i++)
615+
{
616+
result1[i] *= scale;
617+
}
619618
}
620619

621620
template <typename _DataType>
@@ -689,17 +688,15 @@ void dpnp_rng_standard_t_c(void* result, _DataType df, size_t size)
689688

690689
_DataType* result1 = reinterpret_cast<_DataType*>(result);
691690
const _DataType d_zero = 0.0, d_one = 1.0;
692-
_DataType shape = df/2;
693-
_DataType *sn = nullptr;
691+
_DataType shape = df / 2;
692+
_DataType* sn = nullptr;
694693

695694
if (dpnp_queue_is_cpu_c())
696695
{
697-
mkl_rng::gamma<_DataType> gamma_distribution(shape, d_zero, 1.0/shape);
698-
auto event_out = mkl_rng::generate(gamma_distribution, DPNP_RNG_ENGINE,
699-
size, result1);
696+
mkl_rng::gamma<_DataType> gamma_distribution(shape, d_zero, 1.0 / shape);
697+
auto event_out = mkl_rng::generate(gamma_distribution, DPNP_RNG_ENGINE, size, result1);
700698
event_out.wait();
701-
event_out = mkl_vm::invsqrt(DPNP_QUEUE, size, result1, result1, no_deps,
702-
mkl_vm::mode::ha);
699+
event_out = mkl_vm::invsqrt(DPNP_QUEUE, size, result1, result1, no_deps, mkl_vm::mode::ha);
703700
event_out.wait();
704701

705702
sn = reinterpret_cast<_DataType*>(dpnp_memory_alloc_c(size * sizeof(_DataType)));
@@ -712,15 +709,14 @@ void dpnp_rng_standard_t_c(void* result, _DataType df, size_t size)
712709
event_out = mkl_rng::generate(gaussian_distribution, DPNP_RNG_ENGINE, size, sn);
713710
event_out.wait();
714711

715-
event_out = mkl_vm::mul(DPNP_QUEUE, size, result1, sn, result1, no_deps,
716-
mkl_vm::mode::ha);
712+
event_out = mkl_vm::mul(DPNP_QUEUE, size, result1, sn, result1, no_deps, mkl_vm::mode::ha);
717713
dpnp_memory_free_c(sn);
718714
event_out.wait();
719715
}
720716
else
721717
{
722-
int errcode = vdRngGamma(VSL_RNG_METHOD_GAMMA_GNORM_ACCURATE, get_rng_stream(),
723-
size, result1, shape, d_zero, 1.0/shape);
718+
int errcode = vdRngGamma(
719+
VSL_RNG_METHOD_GAMMA_GNORM_ACCURATE, get_rng_stream(), size, result1, shape, d_zero, 1.0 / shape);
724720

725721
if (errcode != VSL_STATUS_OK)
726722
{
@@ -729,14 +725,13 @@ void dpnp_rng_standard_t_c(void* result, _DataType df, size_t size)
729725

730726
vmdInvSqrt(size, result1, result1, VML_HA);
731727

732-
sn = (_DataType *) mkl_malloc(size * sizeof(_DataType), 64);
728+
sn = (_DataType*)mkl_malloc(size * sizeof(_DataType), 64);
733729
if (sn == nullptr)
734730
{
735731
throw std::runtime_error("DPNP RNG Error: dpnp_rng_standard_t_c() failed.");
736732
}
737733

738-
errcode = vdRngGaussian(VSL_RNG_METHOD_GAUSSIAN_ICDF, get_rng_stream(), size, sn,
739-
d_zero, d_one);
734+
errcode = vdRngGaussian(VSL_RNG_METHOD_GAUSSIAN_ICDF, get_rng_stream(), size, sn, d_zero, d_one);
740735
if (errcode != VSL_STATUS_OK)
741736
{
742737
throw std::runtime_error("DPNP RNG Error: dpnp_rng_standard_t_c() failed.");
@@ -846,8 +841,7 @@ void func_map_init_random(func_map_t& fmap)
846841

847842
fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_NORMAL][eft_DBL][eft_DBL] = {eft_DBL,
848843
(void*)dpnp_rng_standard_normal_c<double>};
849-
fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_T][eft_DBL][eft_DBL] = {eft_DBL,
850-
(void*)dpnp_rng_standard_t_c<double>};
844+
fmap[DPNPFuncName::DPNP_FN_RNG_STANDARD_T][eft_DBL][eft_DBL] = {eft_DBL, (void*)dpnp_rng_standard_t_c<double>};
851845

852846
fmap[DPNPFuncName::DPNP_FN_RNG_UNIFORM][eft_DBL][eft_DBL] = {eft_DBL, (void*)dpnp_rng_uniform_c<double>};
853847
fmap[DPNPFuncName::DPNP_FN_RNG_UNIFORM][eft_FLT][eft_FLT] = {eft_FLT, (void*)dpnp_rng_uniform_c<float>};

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