From 581cf078b6383d3845f19608fbd8010ed11982cb Mon Sep 17 00:00:00 2001 From: Nishak Date: Mon, 14 Oct 2024 04:21:42 -0700 Subject: [PATCH] Adding minimum and maximum operators --- backends/cadence/aot/functions_hifi.yaml | 12 +- backends/cadence/hifi/kernels/CMakeLists.txt | 4 +- backends/cadence/hifi/kernels/kernels.h | 24 + .../cadence/hifi/operators/CMakeLists.txt | 2 + .../cadence/hifi/operators/op_maximum.cpp | 172 ++++ .../cadence/hifi/operators/op_minimum.cpp | 171 ++++ .../nnlib/xa_nn_elm_minimum_maximum_f32.c | 847 ++++++++++++++++++ 7 files changed, 1229 insertions(+), 3 deletions(-) create mode 100644 backends/cadence/hifi/operators/op_maximum.cpp create mode 100644 backends/cadence/hifi/operators/op_minimum.cpp create mode 100644 backends/cadence/hifi/third-party/nnlib/xa_nn_elm_minimum_maximum_f32.c diff --git a/backends/cadence/aot/functions_hifi.yaml b/backends/cadence/aot/functions_hifi.yaml index 582bf178bff..f08618272d2 100644 --- a/backends/cadence/aot/functions_hifi.yaml +++ b/backends/cadence/aot/functions_hifi.yaml @@ -62,10 +62,20 @@ - arg_meta: null kernel_name: torch::executor::full_out +- op: maximum.out + kernels: + - arg_meta: null + kernel_name: impl::HiFi::maximum_out + - op: mean.out kernels: - arg_meta: null - kernel_name: impl::HiFi::mean_dim_out + kernel_name: impl::HiFi::mean_dim_out + +- op: minimum.out + kernels: + - arg_meta: null + kernel_name: impl::HiFi::minimum_out - op: mul.out kernels: diff --git a/backends/cadence/hifi/kernels/CMakeLists.txt b/backends/cadence/hifi/kernels/CMakeLists.txt index 90cd814e1e5..26572138483 100644 --- a/backends/cadence/hifi/kernels/CMakeLists.txt +++ b/backends/cadence/hifi/kernels/CMakeLists.txt @@ -15,8 +15,8 @@ add_library( ${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_mul_f32_broadcast.c ${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_where_f32xf32_f32.c ${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_reduce_32_32.c + ${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_minimum_maximum_f32.c ) - # Let files say "include ". set(_common_include_directories ${EXECUTORCH_ROOT}/..) @@ -28,7 +28,7 @@ target_include_directories( ${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/nnlib-hifi4/xa_nnlib/include/nnlib ${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/nnlib-hifi4/xa_nnlib/include ${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/nnlib-hifi4/xa_nnlib/algo/ndsp/hifi4/include/ - ${_common_include_directories} + ${_common_include_directories} ) target_link_libraries(cadence_kernels PRIVATE xa_nnlib) diff --git a/backends/cadence/hifi/kernels/kernels.h b/backends/cadence/hifi/kernels/kernels.h index 7601d969447..3788f2cbcbd 100644 --- a/backends/cadence/hifi/kernels/kernels.h +++ b/backends/cadence/hifi/kernels/kernels.h @@ -77,6 +77,30 @@ extern "C" WORD32 xa_nn_elm_where_broadcast_4D_f32xf32_f32(FLOAT32 * __restrict_ const unsigned char *__restrict__ p_condition, const WORD32 *const p_condition_shape); +extern "C" WORD32 xa_nn_elm_maximum_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const FLOAT32 * __restrict__ p_inp1, + const FLOAT32 * __restrict__ p_inp2, + WORD32 num_elm); + +extern "C" WORD32 xa_nn_elm_maximum_broadcast_4D_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const WORD32 *const p_out_shape, + const FLOAT32 * __restrict__ p_inp1, + const WORD32 *const p_inp1_shape, + const FLOAT32 * __restrict__ p_inp2, + const WORD32 *const p_inp2_shape); + +extern "C" WORD32 xa_nn_elm_minimum_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const FLOAT32 * __restrict__ p_inp1, + const FLOAT32 * __restrict__ p_inp2, + WORD32 num_elm); + +extern "C" WORD32 xa_nn_elm_minimum_broadcast_4D_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const WORD32 *const p_out_shape, + const FLOAT32 * __restrict__ p_inp1, + const WORD32 *const p_inp1_shape, + const FLOAT32 * __restrict__ p_inp2, + const WORD32 *const p_inp2_shape); + namespace impl { namespace HiFi { namespace kernels { diff --git a/backends/cadence/hifi/operators/CMakeLists.txt b/backends/cadence/hifi/operators/CMakeLists.txt index 0bd117771f9..c33eff2eda6 100644 --- a/backends/cadence/hifi/operators/CMakeLists.txt +++ b/backends/cadence/hifi/operators/CMakeLists.txt @@ -22,7 +22,9 @@ endif() set(_aten_ops__srcs "${EXECUTORCH_ROOT}/backends/cadence/hifi/operators/op_add.cpp" "${EXECUTORCH_ROOT}/backends/cadence/hifi/operators/op_div.cpp" + "${EXECUTORCH_ROOT}/backends/cadence/hifi/operators/op_maximum.cpp" "${EXECUTORCH_ROOT}/backends/cadence/hifi/operators/op_mean.cpp" + "${EXECUTORCH_ROOT}/backends/cadence/hifi/operators/op_minimum.cpp" "${EXECUTORCH_ROOT}/backends/cadence/hifi/operators/op_mul.cpp" "${EXECUTORCH_ROOT}/backends/cadence/hifi/operators/op_sigmoid.cpp" "${EXECUTORCH_ROOT}/backends/cadence/hifi/operators/op_sub.cpp" diff --git a/backends/cadence/hifi/operators/op_maximum.cpp b/backends/cadence/hifi/operators/op_maximum.cpp new file mode 100644 index 00000000000..bac9968b418 --- /dev/null +++ b/backends/cadence/hifi/operators/op_maximum.cpp @@ -0,0 +1,172 @@ +/* + * Copyright (c) Meta Platforms, Inc. and affiliates. + * All rights reserved. + * + * This source code is licensed under the BSD-style license found in the + * LICENSE file in the root directory of this source tree. + */ + +#include +#include +#include +#include +#include + +using exec_aten::ScalarType; +using exec_aten::Tensor; +using executorch::runtime::can_cast; +using executorch::runtime::CppTypeToScalarType; +using torch::executor::Error; +using executorch::aten::RuntimeContext; + +namespace impl { +namespace HiFi { +namespace native { +namespace { + +template < + bool can_cast, + typename CTYPE_A, + typename CTYPE_B, + typename CTYPE_IN, + typename CTYPE_OUT> +struct MaximumInner; + +template < + typename CTYPE_A, + typename CTYPE_B, + typename CTYPE_IN, + typename CTYPE_OUT> +struct MaximumInner { + static void run(const Tensor& a, const Tensor& b, Tensor& out) { + apply_binary_elementwise_fn( + // NOLINTNEXTLINE(facebook-hte-ConstantArgumentPassByValue) + [](const CTYPE_A val_a, const CTYPE_B val_b) { + CTYPE_IN a_casted = static_cast(val_a); + CTYPE_IN b_casted = static_cast(val_b); + CTYPE_IN value = torch::executor::native::utils::max_override(a_casted, b_casted); + + return static_cast(value); + }, + a, + b, + out); + } +}; + +struct ReportCanCastBug { + static void run(const Tensor&, const Tensor&, Tensor&) { + ET_DCHECK_MSG(false, "BUG: canCast should have been checked above"); + } +}; + +template < + typename CTYPE_A, + typename CTYPE_B, + typename CTYPE_IN, + typename CTYPE_OUT> +struct MaximumInner + : public ReportCanCastBug {}; + +} // namespace + +Tensor& maximum_out( + RuntimeContext& ctx, + const Tensor& a, + const Tensor& b, + Tensor& out) { + (void)ctx; + + ET_KERNEL_CHECK( + ctx, + resize_to_broadcast_target_size(a, b, out) == Error::Ok, + InvalidArgument, + out); + + constexpr int kNnlibMaxDim = 4; /*fallback if broadcast and dim > 4 */ + + ScalarType a_type = a.scalar_type(); + ScalarType b_type = b.scalar_type(); + ScalarType common_type = promoteTypes(a_type, b_type, /*half_to_float*/ true); + ScalarType out_type = out.scalar_type(); + + ET_KERNEL_CHECK(ctx, canCast(common_type, out_type), InvalidArgument, out); + + bool optimized = 1; + /*find broadcast*/ + bool a_is_broadcasted = !out.sizes().equals(a.sizes()); + bool b_is_broadcasted = !out.sizes().equals(b.sizes()); + bool broadcast = (a_is_broadcasted || b_is_broadcasted); + + int max_dim = a.dim() > b.dim() ? a.dim() : b.dim(); + max_dim = out.dim() > max_dim ? out.dim() : max_dim; + + if((a_type != ScalarType::Float) || (b_type != ScalarType::Float)) + optimized = 0; + if((broadcast == 1) && (max_dim > kNnlibMaxDim)) + optimized = 0; + + if(optimized) + { + float* a_data = a.mutable_data_ptr(); + float* b_data = b.mutable_data_ptr(); + float* out_data = out.mutable_data_ptr(); + + if(broadcast == 1) + { + int out_shape[kNnlibMaxDim]; + int inp1_shape[kNnlibMaxDim]; + int inp2_shape[kNnlibMaxDim]; + + for(int i = 0; i < kNnlibMaxDim; i++) + { + out_shape[i] = 1; + inp1_shape[i] = 1; + inp2_shape[i] = 1; + } + + int off_o = kNnlibMaxDim - out.dim(); + int off_a = kNnlibMaxDim - a.dim(); + int off_b = kNnlibMaxDim - b.dim(); + + for(int i = 0; i < out.dim(); i++){ + out_shape[i+off_o] = out.size(i);} + + for(int i = 0; i < a.dim(); i++) + inp1_shape[i+off_a] = a.size(i); + + for(int i = 0; i < b.dim(); i++) + inp2_shape[i+off_b] = b.size(i); + + xa_nn_elm_maximum_broadcast_4D_f32xf32_f32(out_data, out_shape, a_data, inp1_shape, b_data, inp2_shape); + } + else + { + xa_nn_elm_maximum_f32xf32_f32(out_data, a_data, b_data, out.numel()); + } + } + else + { + ET_SWITCH_REALHB_TYPES(a_type, ctx, "maximum.out", CTYPE_A, [&]() { + ET_SWITCH_REALHB_TYPES(b_type, ctx, "maximum.out", CTYPE_B, [&]() { + using CTYPE_IN = typename torch::executor:: + promote_types::type; + ET_DCHECK(CppTypeToScalarType::value == common_type); + ET_SWITCH_REALHB_TYPES(out_type, ctx, "maximum.out", CTYPE_OUT, [&]() { + MaximumInner< + can_cast::value, + CTYPE_A, + CTYPE_B, + CTYPE_IN, + CTYPE_OUT>::run(a, b, out); + }); + }); + }); + } + + return out; +} + +} // namespace native +} // namespace HiFi +} // namespace impl diff --git a/backends/cadence/hifi/operators/op_minimum.cpp b/backends/cadence/hifi/operators/op_minimum.cpp new file mode 100644 index 00000000000..61afb666083 --- /dev/null +++ b/backends/cadence/hifi/operators/op_minimum.cpp @@ -0,0 +1,171 @@ +/* + * Copyright (c) Meta Platforms, Inc. and affiliates. + * All rights reserved. + * + * This source code is licensed under the BSD-style license found in the + * LICENSE file in the root directory of this source tree. + */ + +#include +#include +#include +#include +#include + +using exec_aten::ScalarType; +using exec_aten::Tensor; +using executorch::runtime::can_cast; +using executorch::runtime::CppTypeToScalarType; +using torch::executor::Error; +using executorch::aten::RuntimeContext; + +namespace impl { +namespace HiFi { +namespace native { +namespace { + +template < + bool can_cast, + typename CTYPE_A, + typename CTYPE_B, + typename CTYPE_IN, + typename CTYPE_OUT> +struct MinimumInner; + +template < + typename CTYPE_A, + typename CTYPE_B, + typename CTYPE_IN, + typename CTYPE_OUT> +struct MinimumInner { + static void run(const Tensor& a, const Tensor& b, Tensor& out) { + apply_binary_elementwise_fn( + // NOLINTNEXTLINE(facebook-hte-ConstantArgumentPassByValue) + [](const CTYPE_A val_a, const CTYPE_B val_b) { + CTYPE_IN a_casted = static_cast(val_a); + CTYPE_IN b_casted = static_cast(val_b); + CTYPE_IN value = torch::executor::native::utils::min_override(a_casted, b_casted); + + return static_cast(value); + }, + a, + b, + out); + } +}; + +struct ReportCanCastBug { + static void run(const Tensor&, const Tensor&, Tensor&) { + ET_DCHECK_MSG(false, "BUG: canCast should have been checked above"); + } +}; + +template < + typename CTYPE_A, + typename CTYPE_B, + typename CTYPE_IN, + typename CTYPE_OUT> +struct MinimumInner + : public ReportCanCastBug {}; + +} // namespace + +Tensor& minimum_out( + RuntimeContext& ctx, + const Tensor& a, + const Tensor& b, + Tensor& out) { + (void)ctx; + + ET_KERNEL_CHECK( + ctx, + resize_to_broadcast_target_size(a, b, out) == Error::Ok, + InvalidArgument, + out); + + constexpr int kNnlibMaxDim = 4; /*fallback if broadcast and dim > 4 */ + + ScalarType a_type = a.scalar_type(); + ScalarType b_type = b.scalar_type(); + ScalarType common_type = promoteTypes(a_type, b_type, /*half_to_float*/ true); + ScalarType out_type = out.scalar_type(); + + ET_KERNEL_CHECK(ctx, canCast(common_type, out_type), InvalidArgument, out); + + bool optimized = 1; + /*find broadcast*/ + const bool a_is_broadcasted = !out.sizes().equals(a.sizes()); + const bool b_is_broadcasted = !out.sizes().equals(b.sizes()); + const bool broadcast = (a_is_broadcasted || b_is_broadcasted); + + int max_dim = a.dim() > b.dim() ? a.dim() : b.dim(); + max_dim = out.dim() > max_dim ? out.dim() : max_dim; + + if((a_type != ScalarType::Float) || (b_type != ScalarType::Float)) + optimized = 0; + if((broadcast == 1) && (max_dim > kNnlibMaxDim)) + optimized = 0; + + if(optimized) + { + float* a_data = a.mutable_data_ptr(); + float* b_data = b.mutable_data_ptr(); + float* out_data = out.mutable_data_ptr(); + + if(broadcast == 1) + { + int out_shape[kNnlibMaxDim]; + int inp1_shape[kNnlibMaxDim]; + int inp2_shape[kNnlibMaxDim]; + + for(int i = 0; i < kNnlibMaxDim; i++) + { + out_shape[i] = 1; + inp1_shape[i] = 1; + inp2_shape[i] = 1; + } + + int off_o = kNnlibMaxDim - out.dim(); + int off_a = kNnlibMaxDim - a.dim(); + int off_b = kNnlibMaxDim - b.dim(); + + for(int i = 0; i < out.dim(); i++){ + out_shape[i+off_o] = out.size(i);} + + for(int i = 0; i < a.dim(); i++) + inp1_shape[i+off_a] = a.size(i); + + for(int i = 0; i < b.dim(); i++) + inp2_shape[i+off_b] = b.size(i); + + xa_nn_elm_minimum_broadcast_4D_f32xf32_f32(out_data, out_shape, a_data, inp1_shape, b_data, inp2_shape); + } + else + { + xa_nn_elm_minimum_f32xf32_f32(out_data, a_data, b_data, out.numel()); + } + } + else + { + ET_SWITCH_REALHB_TYPES(a_type, ctx, "minimum.out", CTYPE_A, [&]() { + ET_SWITCH_REALHB_TYPES(b_type, ctx, "minimum.out", CTYPE_B, [&]() { + using CTYPE_IN = typename torch::executor:: + promote_types::type; + ET_DCHECK(CppTypeToScalarType::value == common_type); + ET_SWITCH_REALHB_TYPES(out_type, ctx, "minimum.out", CTYPE_OUT, [&]() { + MinimumInner< + can_cast::value, + CTYPE_A, + CTYPE_B, + CTYPE_IN, + CTYPE_OUT>::run(a, b, out); + }); + }); + }); + } + return out; +} + +} // namespace native +} // namespace HiFi +} // namespace impl diff --git a/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_minimum_maximum_f32.c b/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_minimum_maximum_f32.c new file mode 100644 index 00000000000..3af93fc00c1 --- /dev/null +++ b/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_minimum_maximum_f32.c @@ -0,0 +1,847 @@ +/******************************************************************************* +* Copyright (c) 2018-2024 Cadence Design Systems, Inc. +* +* Permission is hereby granted, free of charge, to any person obtaining +* a copy of this software and associated documentation files (the +* "Software"), to use this Software with Cadence processor cores only and +* not with any other processors and platforms, subject to +* the following conditions: +* +* The above copyright notice and this permission notice shall be included +* in all copies or substantial portions of the Software. +* +* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF +* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. +* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY +* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, +* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE +* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + +******************************************************************************/ +#include "nnlib-hifi4/xa_nnlib/include/xa_type_def.h" +#include "nnlib-hifi4/xa_nnlib/algo/common/include/xa_nnlib_common_fpu.h" +#include "nnlib-hifi4/xa_nnlib/algo/common/include/xa_nn_common.h" +#include "nnlib-hifi4/xa_nnlib/algo/common/include/xa_nnlib_err_chk.h" +#include "nnlib-hifi4/xa_nnlib/algo/kernels/basic/hifi4/xa_nn_basic_state.h" +#include "nnlib-hifi4/xa_nnlib/include/nnlib/xa_nnlib_kernels_api.h" + +#if !HAVE_VFPU +DISCARD_FUN_FOR_NONVOID_RETURN( + WORD32, xa_nn_elm_maximum_f32xf32_f32, + ( + FLOAT32 *p_out, + const FLOAT32 *p_inp1, + const FLOAT32 *p_inp2, + WORD32 num_elm + ) + ) +#else +WORD32 xa_nn_elm_maximum_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const FLOAT32 * __restrict__ p_inp1, + const FLOAT32 * __restrict__ p_inp2, + WORD32 num_elm) +{ + + /* NULL pointer checks */ + XA_NNLIB_ARG_CHK_PTR(p_out, -1); + XA_NNLIB_ARG_CHK_PTR(p_inp1, -1); + XA_NNLIB_ARG_CHK_PTR(p_inp2, -1); + /* Pointer alignment checks */ + XA_NNLIB_ARG_CHK_ALIGN(p_out, sizeof(FLOAT32), -1); + XA_NNLIB_ARG_CHK_ALIGN(p_inp1, sizeof(FLOAT32), -1); + XA_NNLIB_ARG_CHK_ALIGN(p_inp2, sizeof(FLOAT32), -1); + /* Basic Parameter checks */ + XA_NNLIB_ARG_CHK_COND((num_elm <= 0), -1); + + int i; + xtfloatx2 *inp1 = (xtfloatx2 *)p_inp1; + xtfloatx2 *inp2 = (xtfloatx2 *)p_inp2; + xtfloatx2 *out = (xtfloatx2 *)p_out; + xtfloatx2 x1, x2, y; + unsigned char con1, con2; + xtbool2 con = int32_rtor_xtbool2(0x00000003); + + if(((((unsigned)p_out)&7) == 0) && ((((unsigned)p_inp1)&7) == 0) && ((((unsigned)p_inp2)&7) == 0)) + { + for(i=0;i < num_elm>>1;i++) + { + XT_LSX2IP(x1, inp1, 2*sizeof(FLOAT32)); + XT_LSX2IP(x2, inp2, 2*sizeof(FLOAT32)); + y = XT_MAX_SX2(x2, x1); + XT_SSX2IP( y, out, 2*sizeof(FLOAT32)); + } + } + else + { + ae_valign inp1_a, inp2_a, out_a; + + inp1_a = XT_LASX2PP(inp1); + inp2_a = XT_LASX2PP(inp2); + out_a = AE_ZALIGN64(); + /* Each iteration of loop is independent so safe to use concurrent pragma */ +#pragma concurrent + for(i=0;i < num_elm>>1;i++) + { + XT_LASX2IP(x1, inp1_a, inp1); + XT_LASX2IP(x2, inp2_a, inp2); + y = XT_MAX_SX2(x2, x1); + XT_SASX2IP(y, out_a, out); + } + XT_SASX2POSFP(out_a, out); + } + // Remainder Loop + if (num_elm & 1) + { + xtfloat a1, a2, a; + XT_LSIP(a1, (xtfloat *)inp1, 0); + XT_LSIP(a2, (xtfloat *)inp2, 0); + a = XT_MAX_S(a1, a2); + XT_SSI(a, (xtfloat *)out, 0); + } + return 0; +} +#endif + +#if HAVE_VFPU +static void internal_elm_maximum_broadcast_2D_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const FLOAT32 * __restrict__ p_inp1, + const FLOAT32 * __restrict__ p_inp2, + WORD32 out_lc, + WORD32 in_lc, + xtbool sign_flag) +{ + int i, j; + + xtfloatx2 * __restrict__ p_a = (xtfloatx2 *)p_inp1; + xtfloatx2 * __restrict__ p_b = (xtfloatx2 *)p_inp2; + xtfloatx2 *__restrict__ p_c = (xtfloatx2 *)p_out; + + int num_simd2_ops; + int num_scalar_ops; + + if(out_lc) + { + num_simd2_ops = in_lc >> 1; + num_scalar_ops = in_lc & 1; + } + else + { + num_simd2_ops = (in_lc >> 2) << 1; + num_scalar_ops = in_lc & 3; + } + + xtfloatx2 x1, x2, y; + xtfloat a0, b0, c0; + + for(i = 0; i < out_lc; i++) + { + p_a = (xtfloatx2 *)&p_inp1[i * in_lc]; + p_b = (xtfloatx2 *)p_inp2; + p_c = (xtfloatx2 *)&p_out[i * in_lc]; + if(((((unsigned)p_a)&7) == 0) && ((((unsigned)p_b)&7) == 0) && ((((unsigned)p_c)&7) == 0)) + { + for(j = 0; j < num_simd2_ops; j++) + { + XT_LSX2IP(x1, p_a, 2 * sizeof(FLOAT32)); + XT_LSX2IP(x2, p_b, 2 * sizeof(FLOAT32)); + y = XT_MAX_SX2(x2, x1); + XT_SSX2IP(y, p_c, 2 * sizeof(FLOAT32)); + } + } + else + { + ae_valign vinp1, vinp2, out_a = AE_ZALIGN64(); + vinp1 = XT_LASX2PP(p_a); + vinp2 = XT_LASX2PP(p_b); + for(j = 0; j < num_simd2_ops; j++) + { + XT_LASX2IP(x1, vinp1, p_a); + XT_LASX2IP(x2, vinp2, p_b); + y = XT_MAX_SX2(x2, x1); + XT_SASX2IP(y, out_a, p_c); + } + XT_SASX2POSFP(out_a, (xtfloatx2 *)p_c); + } + if(num_scalar_ops !=0) + { + XT_LSIP(a0, (xtfloat *)p_a, sizeof(FLOAT32)); + XT_LSIP(b0, (xtfloat *)p_b, sizeof(FLOAT32)); + c0 = XT_MAX_S(b0, a0); + XT_SSI(c0, (xtfloat *)p_c, 0); + } + } +} + +static void internal_elm_maximum_broadcast_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const FLOAT32 * __restrict__ p_inp1, + const FLOAT32 * __restrict__ p_inp2, + WORD32 num_elm, + xtbool sign_flag) +{ + int i; + xtfloatx2 * __restrict__ p_a = (xtfloatx2 *)p_inp1; + xtfloatx2 * __restrict__ p_b = (xtfloatx2 *)p_inp2; + xtfloatx2 *__restrict__ p_c = (xtfloatx2 *)p_out; + + const int num_simd2_ops = num_elm >> 1; + const int num_scalar_ops = num_elm & 1; + + xtfloat a0_7, out; + xtfloatx2 x1, x2, y; + x2 = XT_LSI((xtfloat *)p_b, 0); + + if(((((unsigned)p_a)&7) == 0) && ((((unsigned)p_c)&7) == 0)) + { + for(i=0; i p_inp2_shape[i] ? p_inp1_shape[i] : p_inp2_shape[i]))) + { + return -1; + } + } + + WORD32 inp1_strides[4], inp2_strides[4]; + inp1_strides[3] = 1; + inp2_strides[3] = 1; + for(i = 2; i >= 0; i--) + { + ae_int32x2 d_str, d_shape; + d_str = AE_MOVDA32X2(inp1_strides[i + 1], inp2_strides[i + 1]); + d_shape = AE_MOVDA32X2(p_inp1_shape[i + 1], p_inp2_shape[i + 1]); + d_str = AE_MULP32X2(d_str, d_shape); + inp1_strides[i] = AE_MOVAD32_H(d_str); + inp2_strides[i] = AE_MOVAD32_L(d_str); + } + + int need_broadcast = 0; + int inp1_const = 1, inp2_const = 1; + for(i = 0; i < 4; i++) + { + if(p_inp1_shape[i] != p_inp2_shape[i]) + { + if(p_inp1_shape[i] == 1) + inp1_strides[i] = 0; + else + inp2_strides[i] = 0; + + need_broadcast = 1; + } + if(p_inp1_shape[i] != 1) + inp1_const &= 0; + if(p_inp2_shape[i] != 1) + inp2_const &= 0; + } + int itr0, itr1, itr2; + + FLOAT32 *p_out_tmp = p_out; + const FLOAT32 *__restrict__ p_inp1_tmp = p_inp1; + const FLOAT32 *__restrict__ p_inp2_tmp = p_inp2; + if(need_broadcast == 0) + { + sign_flag = 0; + internal_elm_maximum_broadcast_2D_f32xf32_f32( + p_out, + p_inp1, + p_inp2, + 1, + p_out_shape[0] * inp1_strides[0], + sign_flag); + } + else if(inp1_strides[3] == inp2_strides[3]) + { + WORD32 in_lc, out_lc; + sign_flag = 0; + in_lc = p_out_shape[2] * p_out_shape[3]; + out_lc = 1; + if(inp1_strides[2] == 0) + { + const FLOAT32 *tmp; + tmp = p_inp1_tmp; p_inp1_tmp = p_inp2_tmp; p_inp2_tmp = tmp; + sign_flag = 1; + int tmp_strides[2]; + tmp_strides[0] = inp1_strides[0]; + tmp_strides[1] = inp1_strides[1]; + + inp1_strides[0] = inp2_strides[0]; + inp1_strides[1] = inp2_strides[1]; + + inp2_strides[0] = tmp_strides[0]; + inp2_strides[1] = tmp_strides[1]; + in_lc = p_out_shape[3]; + out_lc = p_out_shape[2]; + } + else if(inp2_strides[2] == 0) + { + in_lc = p_out_shape[3]; + out_lc = p_out_shape[2]; + } + + for(itr0 = 0; itr0 < p_out_shape[0]; itr0++) + { + const FLOAT32 *__restrict__ p_inp1_tmp0 = p_inp1_tmp; + const FLOAT32 *__restrict__ p_inp2_tmp0 = p_inp2_tmp; + for(itr1 = 0; itr1 < p_out_shape[1]; itr1++) + { + internal_elm_maximum_broadcast_2D_f32xf32_f32( + p_out_tmp, + p_inp1_tmp0, + p_inp2_tmp0, + out_lc, + in_lc, + sign_flag); + p_out_tmp += in_lc * out_lc; + p_inp1_tmp0 += inp1_strides[1]; + p_inp2_tmp0 += inp2_strides[1]; + } + p_inp1_tmp += inp1_strides[0]; + p_inp2_tmp += inp2_strides[0]; + } + } + else if(inp1_const == 1 || inp2_const == 1) + { + sign_flag = 0; + if(inp1_strides[3] == 0) + { + sign_flag = 1; + const FLOAT32 *tmp; + tmp = p_inp1_tmp; p_inp1_tmp = p_inp2_tmp; p_inp2_tmp = tmp; + } + internal_elm_maximum_broadcast_f32xf32_f32( + p_out_tmp, + p_inp1_tmp, + p_inp2_tmp, + p_out_shape[0] * p_out_shape[1] * p_out_shape[2] * p_out_shape[3], + sign_flag); + } + else + { + sign_flag = 0; + if(inp1_strides[3] == 0) + { + const FLOAT32 *tmp; + tmp = p_inp1_tmp; p_inp1_tmp = p_inp2_tmp; p_inp2_tmp = tmp; + sign_flag = 1; + int tmp_strides[3]; + tmp_strides[0] = inp1_strides[0]; + tmp_strides[1] = inp1_strides[1]; + tmp_strides[2] = inp1_strides[2]; + + inp1_strides[0] = inp2_strides[0]; + inp1_strides[1] = inp2_strides[1]; + inp1_strides[2] = inp2_strides[2]; + + inp2_strides[0] = tmp_strides[0]; + inp2_strides[1] = tmp_strides[1]; + inp2_strides[2] = tmp_strides[2]; + } + for(itr0 = 0; itr0 < p_out_shape[0]; itr0++) + { + const FLOAT32 *__restrict__ p_inp1_tmp0 = p_inp1_tmp; + const FLOAT32 *__restrict__ p_inp2_tmp0 = p_inp2_tmp; + for(itr1 = 0; itr1 < p_out_shape[1]; itr1++) + { + const FLOAT32 *__restrict__ p_inp1_tmp1 = p_inp1_tmp0; + const FLOAT32 *__restrict__ p_inp2_tmp1 = p_inp2_tmp0; + for(itr2 = 0; itr2 < p_out_shape[2]; itr2++) + { + { + internal_elm_maximum_broadcast_f32xf32_f32( + p_out_tmp, + p_inp1_tmp1, + p_inp2_tmp1, + p_out_shape[3], + sign_flag); + } + p_out_tmp += p_out_shape[3]; + p_inp1_tmp1 += inp1_strides[2]; + p_inp2_tmp1 += inp2_strides[2]; + } + p_inp1_tmp0 += inp1_strides[1]; + p_inp2_tmp0 += inp2_strides[1]; + } + p_inp1_tmp += inp1_strides[0]; + p_inp2_tmp += inp2_strides[0]; + } + } + return 0; +} +#endif + +#if !HAVE_VFPU +DISCARD_FUN_FOR_NONVOID_RETURN( + WORD32, xa_nn_elm_minimum_f32xf32_f32, + ( + FLOAT32 *p_out, + const FLOAT32 *p_inp1, + const FLOAT32 *p_inp2, + WORD32 num_elm + ) + ) +#else +WORD32 xa_nn_elm_minimum_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const FLOAT32 * __restrict__ p_inp1, + const FLOAT32 * __restrict__ p_inp2, + WORD32 num_elm) +{ + + /* NULL pointer checks */ + XA_NNLIB_ARG_CHK_PTR(p_out, -1); + XA_NNLIB_ARG_CHK_PTR(p_inp1, -1); + XA_NNLIB_ARG_CHK_PTR(p_inp2, -1); + /* Pointer alignment checks */ + XA_NNLIB_ARG_CHK_ALIGN(p_out, sizeof(FLOAT32), -1); + XA_NNLIB_ARG_CHK_ALIGN(p_inp1, sizeof(FLOAT32), -1); + XA_NNLIB_ARG_CHK_ALIGN(p_inp2, sizeof(FLOAT32), -1); + /* Basic Parameter checks */ + XA_NNLIB_ARG_CHK_COND((num_elm <= 0), -1); + + int i; + xtfloatx2 *inp1 = (xtfloatx2 *)p_inp1; + xtfloatx2 *inp2 = (xtfloatx2 *)p_inp2; + xtfloatx2 *out = (xtfloatx2 *)p_out; + xtfloatx2 x1, x2, y; + unsigned char con1, con2; + xtbool2 con = int32_rtor_xtbool2(0x00000003); + + if(((((unsigned)p_out)&7) == 0) && ((((unsigned)p_inp1)&7) == 0) && ((((unsigned)p_inp2)&7) == 0)) + { + for(i=0;i < num_elm>>1;i++) + { + XT_LSX2IP(x1, inp1, 2*sizeof(FLOAT32)); + XT_LSX2IP(x2, inp2, 2*sizeof(FLOAT32)); + y = XT_MIN_SX2(x2, x1); + XT_SSX2IP( y, out, 2*sizeof(FLOAT32)); + } + } + else + { + ae_valign inp1_a, inp2_a, out_a; + + inp1_a = XT_LASX2PP(inp1); + inp2_a = XT_LASX2PP(inp2); + out_a = AE_ZALIGN64(); + /* Each iteration of loop is independent so safe to use concurrent pragma */ +#pragma concurrent + for(i=0;i < num_elm>>1;i++) + { + XT_LASX2IP(x1, inp1_a, inp1); + XT_LASX2IP(x2, inp2_a, inp2); + y = XT_MIN_SX2(x2, x1); + XT_SASX2IP(y, out_a, out); + } + XT_SASX2POSFP(out_a, out); + } + // Remainder Loop + if (num_elm & 1) + { + xtfloat a1, a2, a; + XT_LSIP(a1, (xtfloat *)inp1, 0); + XT_LSIP(a2, (xtfloat *)inp2, 0); + a = XT_MIN_S(a1, a2); + XT_SSI(a, (xtfloat *)out, 0); + } + return 0; +} +#endif + +#if HAVE_VFPU +static void internal_elm_minimum_broadcast_2D_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const FLOAT32 * __restrict__ p_inp1, + const FLOAT32 * __restrict__ p_inp2, + WORD32 out_lc, + WORD32 in_lc, + xtbool sign_flag) +{ + int i, j; + + xtfloatx2 * __restrict__ p_a = (xtfloatx2 *)p_inp1; + xtfloatx2 * __restrict__ p_b = (xtfloatx2 *)p_inp2; + xtfloatx2 *__restrict__ p_c = (xtfloatx2 *)p_out; + + int num_simd2_ops; + int num_scalar_ops; + + if(out_lc) + { + num_simd2_ops = in_lc >> 1; + num_scalar_ops = in_lc & 1; + } + else + { + num_simd2_ops = (in_lc >> 2) << 1; + num_scalar_ops = in_lc & 3; + } + + xtfloatx2 x1, x2, y; + xtfloat a0, b0, c0; + + for(i = 0; i < out_lc; i++) + { + p_a = (xtfloatx2 *)&p_inp1[i * in_lc]; + p_b = (xtfloatx2 *)p_inp2; + p_c = (xtfloatx2 *)&p_out[i * in_lc]; + if(((((unsigned)p_a)&7) == 0) && ((((unsigned)p_b)&7) == 0) && ((((unsigned)p_c)&7) == 0)) + { + for(j = 0; j < num_simd2_ops; j++) + { + XT_LSX2IP(x1, p_a, 2 * sizeof(FLOAT32)); + XT_LSX2IP(x2, p_b, 2 * sizeof(FLOAT32)); + y = XT_MIN_SX2(x2, x1); + XT_SSX2IP(y, p_c, 2 * sizeof(FLOAT32)); + } + } + else + { + ae_valign vinp1, vinp2, out_a = AE_ZALIGN64(); + vinp1 = XT_LASX2PP(p_a); + vinp2 = XT_LASX2PP(p_b); + for(j = 0; j < num_simd2_ops; j++) + { + XT_LASX2IP(x1, vinp1, p_a); + XT_LASX2IP(x2, vinp2, p_b); + y = XT_MIN_SX2(x2, x1); + XT_SASX2IP(y, out_a, p_c); + } + XT_SASX2POSFP(out_a, (xtfloatx2 *)p_c); + } + if(num_scalar_ops !=0) + { + XT_LSIP(a0, (xtfloat *)p_a, sizeof(FLOAT32)); + XT_LSIP(b0, (xtfloat *)p_b, sizeof(FLOAT32)); + c0 = XT_MIN_S(b0, a0); + XT_SSI(c0, (xtfloat *)p_c, 0); + } + } +} + +static void internal_elm_minimum_broadcast_f32xf32_f32(FLOAT32 * __restrict__ p_out, + const FLOAT32 * __restrict__ p_inp1, + const FLOAT32 * __restrict__ p_inp2, + WORD32 num_elm, + xtbool sign_flag) +{ + int i; + xtfloatx2 * __restrict__ p_a = (xtfloatx2 *)p_inp1; + xtfloatx2 * __restrict__ p_b = (xtfloatx2 *)p_inp2; + xtfloatx2 *__restrict__ p_c = (xtfloatx2 *)p_out; + + const int num_simd2_ops = num_elm >> 1; + const int num_scalar_ops = num_elm & 1; + + xtfloat a0_7, out; + xtfloatx2 x1, x2, y; + x2 = XT_LSI((xtfloat *)p_b, 0); + + if(((((unsigned)p_a)&7) == 0) && ((((unsigned)p_c)&7) == 0)) + { + for(i=0; i p_inp2_shape[i] ? p_inp1_shape[i] : p_inp2_shape[i]))) + { + return -1; + } + } + + WORD32 inp1_strides[4], inp2_strides[4]; + inp1_strides[3] = 1; + inp2_strides[3] = 1; + for(i = 2; i >= 0; i--) + { + ae_int32x2 d_str, d_shape; + d_str = AE_MOVDA32X2(inp1_strides[i + 1], inp2_strides[i + 1]); + d_shape = AE_MOVDA32X2(p_inp1_shape[i + 1], p_inp2_shape[i + 1]); + d_str = AE_MULP32X2(d_str, d_shape); + inp1_strides[i] = AE_MOVAD32_H(d_str); + inp2_strides[i] = AE_MOVAD32_L(d_str); + } + + int need_broadcast = 0; + int inp1_const = 1, inp2_const = 1; + for(i = 0; i < 4; i++) + { + if(p_inp1_shape[i] != p_inp2_shape[i]) + { + if(p_inp1_shape[i] == 1) + inp1_strides[i] = 0; + else + inp2_strides[i] = 0; + + need_broadcast = 1; + } + if(p_inp1_shape[i] != 1) + inp1_const &= 0; + if(p_inp2_shape[i] != 1) + inp2_const &= 0; + } + int itr0, itr1, itr2; + + FLOAT32 *p_out_tmp = p_out; + const FLOAT32 *__restrict__ p_inp1_tmp = p_inp1; + const FLOAT32 *__restrict__ p_inp2_tmp = p_inp2; + if(need_broadcast == 0) + { + sign_flag = 0; + internal_elm_minimum_broadcast_2D_f32xf32_f32( + p_out, + p_inp1, + p_inp2, + 1, + p_out_shape[0] * inp1_strides[0], + sign_flag); + } + else if(inp1_strides[3] == inp2_strides[3]) + { + WORD32 in_lc, out_lc; + sign_flag = 0; + in_lc = p_out_shape[2] * p_out_shape[3]; + out_lc = 1; + if(inp1_strides[2] == 0) + { + const FLOAT32 *tmp; + tmp = p_inp1_tmp; p_inp1_tmp = p_inp2_tmp; p_inp2_tmp = tmp; + sign_flag = 1; + int tmp_strides[2]; + tmp_strides[0] = inp1_strides[0]; + tmp_strides[1] = inp1_strides[1]; + + inp1_strides[0] = inp2_strides[0]; + inp1_strides[1] = inp2_strides[1]; + + inp2_strides[0] = tmp_strides[0]; + inp2_strides[1] = tmp_strides[1]; + in_lc = p_out_shape[3]; + out_lc = p_out_shape[2]; + } + else if(inp2_strides[2] == 0) + { + in_lc = p_out_shape[3]; + out_lc = p_out_shape[2]; + } + + for(itr0 = 0; itr0 < p_out_shape[0]; itr0++) + { + const FLOAT32 *__restrict__ p_inp1_tmp0 = p_inp1_tmp; + const FLOAT32 *__restrict__ p_inp2_tmp0 = p_inp2_tmp; + for(itr1 = 0; itr1 < p_out_shape[1]; itr1++) + { + internal_elm_minimum_broadcast_2D_f32xf32_f32( + p_out_tmp, + p_inp1_tmp0, + p_inp2_tmp0, + out_lc, + in_lc, + sign_flag); + p_out_tmp += in_lc * out_lc; + p_inp1_tmp0 += inp1_strides[1]; + p_inp2_tmp0 += inp2_strides[1]; + } + p_inp1_tmp += inp1_strides[0]; + p_inp2_tmp += inp2_strides[0]; + } + } + else if(inp1_const == 1 || inp2_const == 1) + { + sign_flag = 0; + if(inp1_strides[3] == 0) + { + sign_flag = 1; + const FLOAT32 *tmp; + tmp = p_inp1_tmp; p_inp1_tmp = p_inp2_tmp; p_inp2_tmp = tmp; + } + internal_elm_minimum_broadcast_f32xf32_f32( + p_out_tmp, + p_inp1_tmp, + p_inp2_tmp, + p_out_shape[0] * p_out_shape[1] * p_out_shape[2] * p_out_shape[3], + sign_flag); + } + else + { + sign_flag = 0; + if(inp1_strides[3] == 0) + { + const FLOAT32 *tmp; + tmp = p_inp1_tmp; p_inp1_tmp = p_inp2_tmp; p_inp2_tmp = tmp; + sign_flag = 1; + int tmp_strides[3]; + tmp_strides[0] = inp1_strides[0]; + tmp_strides[1] = inp1_strides[1]; + tmp_strides[2] = inp1_strides[2]; + + inp1_strides[0] = inp2_strides[0]; + inp1_strides[1] = inp2_strides[1]; + inp1_strides[2] = inp2_strides[2]; + + inp2_strides[0] = tmp_strides[0]; + inp2_strides[1] = tmp_strides[1]; + inp2_strides[2] = tmp_strides[2]; + } + for(itr0 = 0; itr0 < p_out_shape[0]; itr0++) + { + const FLOAT32 *__restrict__ p_inp1_tmp0 = p_inp1_tmp; + const FLOAT32 *__restrict__ p_inp2_tmp0 = p_inp2_tmp; + for(itr1 = 0; itr1 < p_out_shape[1]; itr1++) + { + const FLOAT32 *__restrict__ p_inp1_tmp1 = p_inp1_tmp0; + const FLOAT32 *__restrict__ p_inp2_tmp1 = p_inp2_tmp0; + for(itr2 = 0; itr2 < p_out_shape[2]; itr2++) + { + { + internal_elm_minimum_broadcast_f32xf32_f32( + p_out_tmp, + p_inp1_tmp1, + p_inp2_tmp1, + p_out_shape[3], + sign_flag); + } + p_out_tmp += p_out_shape[3]; + p_inp1_tmp1 += inp1_strides[2]; + p_inp2_tmp1 += inp2_strides[2]; + } + p_inp1_tmp0 += inp1_strides[1]; + p_inp2_tmp0 += inp2_strides[1]; + } + p_inp1_tmp += inp1_strides[0]; + p_inp2_tmp += inp2_strides[0]; + } + } + return 0; +} +#endif \ No newline at end of file