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NNlib update to latest version for HiFi1 build #17994

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1b4a548
NNlib update to latest version for HiFi1 build
dijopaul Mar 7, 2026
12079c4
HiFi1 build - fix lint error
dijopaul Mar 8, 2026
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4 changes: 2 additions & 2 deletions backends/cadence/aot/functions_hifi.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -286,12 +286,12 @@
- func: cadence::im2row.out(Tensor input, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride, Tensor in_zero_point, bool channel_last=False, *, Tensor(a!) out) -> Tensor(a!)
kernels:
- arg_meta: null
kernel_name: impl::HiFi::native::im2row_out
kernel_name: impl::HiFi::im2row_out

- func: cadence::im2row.per_tensor_out(Tensor input, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride, int in_zero_point, bool channel_last=False, *, Tensor(a!) out) -> Tensor(a!)
kernels:
- arg_meta: null
kernel_name: impl::HiFi::native::im2row_per_tensor_out
kernel_name: impl::HiFi::im2row_per_tensor_out

- func: cadence::quantize_per_tensor.out(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)
variants: function
Expand Down
12 changes: 1 addition & 11 deletions backends/cadence/hifi/kernels/CMakeLists.txt
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Expand Up @@ -8,25 +8,15 @@
add_library(
cadence_kernels
kernels.cpp
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/matmul_asym8uxasym8u_asym8u.cpp
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_broadcast_32.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_concat_32.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_add_f32_broadcast.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_atan2_f32.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_clamp_f32_broadcast.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_div_f32_broadcast.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_div_mode_f32_broadcast.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_fmod_broadcast_f32.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_greater_lesser_equal_f32.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_im2row.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_logicalxor_bool_bool.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_minimum_maximum_f32.c
${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_pow_f32.c
${EXECUTORCH_ROOT}/backends/cadence/hifi/third-party/nnlib/xa_nn_elm_remainder_broadcast_f32.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_im2row.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_transpose_32.c
)
# Let files say "include <executorch/path/to/header.h>".
set(_common_include_directories
Expand Down
157 changes: 0 additions & 157 deletions backends/cadence/hifi/kernels/kernels.h
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Original file line number Diff line number Diff line change
Expand Up @@ -18,41 +18,9 @@ using executorch::runtime::Result;

/* Potential NNLIB function/APIs */

extern "C" WORD32 xa_nn_broadcast_32_32(
WORD32* __restrict__ p_out,
const int* const out_shape,
WORD32* __restrict__ p_in,
const int* const in_shape,
int num_dims);

extern "C" WORD32 xa_nn_concat_32_32(
WORD32* __restrict__ p_out,
const WORD32* const p_out_shape,
const WORD32** pp_inps,
const WORD32* const* pp_inps_shape,
WORD32 num_out_dims,
WORD32 num_inp,
WORD32 num_inp_dims,
WORD32 axis);

extern "C" WORD32 xa_nn_elm_add_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" void
xa_nn_elm_atan2_f32(FLOAT32* z, const FLOAT32* y, const FLOAT32* x, WORD32 N);

extern "C" WORD32 xa_nn_elm_clamp_f32xf32xf32_f32(
FLOAT32* __restrict__ p_out,
const FLOAT32* __restrict__ p_inp,
const FLOAT32* __restrict__ p_min,
const FLOAT32* __restrict__ p_max,
WORD32 num_elm);

extern "C" WORD32 xa_nn_elm_clamp_broadcast_4D_f32Xf32xf32_f32(
FLOAT32* __restrict__ p_out,
const WORD32* const p_out_shape,
Expand All @@ -63,14 +31,6 @@ extern "C" WORD32 xa_nn_elm_clamp_broadcast_4D_f32Xf32xf32_f32(
const FLOAT32* __restrict__ p_max,
const WORD32* const p_max_shape);

extern "C" WORD32 xa_nn_elm_div_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_div_mode_f32xf32_f32(
FLOAT32* __restrict__ p_out,
const FLOAT32* __restrict__ p_inp1,
Expand All @@ -87,22 +47,6 @@ extern "C" WORD32 xa_nn_elm_div_mode_broadcast_4D_f32xf32_f32(
const WORD32* const p_inp2_shape,
WORD32 mode);

extern "C" WORD32 xa_nn_elm_greater_lesser_equal_f32xf32_f32(
WORD8* __restrict__ p_out,
const FLOAT32* __restrict__ p_inp1,
const FLOAT32* __restrict__ p_inp2,
WORD32 num_elm,
WORD32 kernel_type);

extern "C" WORD32 xa_nn_elm_greater_lesser_equal_broadcast_4D_f32xf32_f32(
WORD8* __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,
WORD32 kernel_type);

extern "C" WORD32 xa_nn_elm_fmod_f32xf32_f32(
FLOAT32* __restrict__ p_out,
const FLOAT32* __restrict__ p_inp1,
Expand All @@ -123,42 +67,6 @@ extern "C" WORD32 xa_nn_elm_logicalxor_boolxbool_bool(
const WORD8* __restrict__ p_inp2,
WORD32 num_elm);

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);

extern "C" WORD32 xa_nn_elm_mul_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" void xa_nn_elm_pow_f32(
FLOAT32* __restrict__ z,
const FLOAT32* __restrict__ x,
Expand All @@ -179,23 +87,6 @@ extern "C" WORD32 xa_nn_elm_remainder_broadcast_4D_f32xf32_f32(
const FLOAT32* __restrict__ p_inp2,
const WORD32* const p_inp2_shape);

extern "C" WORD32 xa_nn_elm_where_f32xf32_f32(
FLOAT32* __restrict__ p_out,
const FLOAT32* __restrict__ p_inp1,
const FLOAT32* __restrict__ p_inp2,
const unsigned char* __restrict__ p_condition,
WORD32 num_elm);

extern "C" WORD32 xa_nn_elm_where_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,
const unsigned char* __restrict__ p_condition,
const WORD32* const p_condition_shape);

extern "C" WORD32 xa_nn_im2row_quantized(
const WORD8* __restrict__ data_im,
const WORD32 in_zero_point,
Expand Down Expand Up @@ -229,60 +120,12 @@ extern "C" WORD32 xa_nn_reduce_mean_4D_f32_f32(
WORD32 num_axis_dims,
void* __restrict__ p_scratch_in);

extern "C" WORD32 xa_nn_transpose_32_32(
WORD32* __restrict__ p_out,
const WORD32* const p_out_shape,
const WORD32* __restrict__ p_inp,
const WORD32* const p_inp_shape,
const WORD32* __restrict__ p_permute_vec,
WORD32 num_out_dims,
WORD32 num_inp_dims);

namespace impl {
namespace HiFi {
namespace kernels {

void* allocate_temp_memory(KernelRuntimeContext& ctx, size_t size);

void memcpy(void* dst, const void* src, size_t num_bytes);

WORD32 matmul_asym8uxasym8u_asym8u(
UWORD8* __restrict__ p_out, // output uint8 matrix
const UWORD8* __restrict__ p_mat1, // weight uint8 matrix
const UWORD8* __restrict__ p_vec1, // input uint8 matrix
const WORD32* __restrict__ p_bias, // bias int32 vec
WORD32 rows, // rows of p_mat1
WORD32 cols1, // columns of p_mat1
WORD32 row_stride1, // row stride of p_mat1
WORD32 vec_count, // rows of p_mat2
WORD32 vec_offset, // vec_offset of p_mat2.
WORD32 out_offset, // out_offset, i.e., offset of next output element
WORD32 out_stride, // out_stride, i.e., stride to go to next output row
WORD32 mat1_zero_bias, // zero_point of p_mat1
WORD32 vec1_zero_bias, // zero_point of p_vec1
const WORD32* __restrict__ out_multiplier,
const WORD32* __restrict__ out_shift,
WORD32 out_zero_bias,
bool per_channel_quantized = false); // per-channel quantized weight

WORD32 xa_nn_matmul_asym8uxasym8u_asym8u(
UWORD8* __restrict__ p_out,
const UWORD8* __restrict__ p_mat1,
const UWORD8* __restrict__ p_mat2,
const WORD32* __restrict__ p_bias,
WORD32 rows,
WORD32 cols,
WORD32 row_stride,
WORD32 vec_count,
WORD32 vec_offset,
WORD32 out_offset,
WORD32 out_stride,
WORD32 mat1_zero_bias,
WORD32 vec1_zero_bias,
WORD32 out_multiplier,
WORD32 out_shift,
WORD32 out_zero_bias);

template <typename T>
T quantize(const float x, float scale, int32_t zero_point);

Expand Down
8 changes: 4 additions & 4 deletions backends/cadence/hifi/operators/op_clamp.cpp
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Expand Up @@ -155,13 +155,13 @@ Tensor& clamp_Tensor_out(
inp_shape[i + off_inp] = in.size(i);
}

WORD32 ret_val = xa_nn_elm_minimum_broadcast_4D_f32xf32_f32(
WORD32 ret_val = xa_nn_elm_min_4D_Bcast_f32xf32_f32(
out_data, out_shape, inp_data, inp_shape, max_data, max_shape);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);

} else {
WORD32 ret_val = xa_nn_elm_minimum_f32xf32_f32(
WORD32 ret_val = xa_nn_elm_min_f32xf32_f32(
out_data, inp_data, max_data, out.numel());

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
Expand Down Expand Up @@ -192,13 +192,13 @@ Tensor& clamp_Tensor_out(
min_shape[i + off_min] = min.size(i);
for (int i = 0; i < inp_dim; i++)
inp_shape[i + off_inp] = in.size(i);
WORD32 ret_val = xa_nn_elm_maximum_broadcast_4D_f32xf32_f32(
WORD32 ret_val = xa_nn_elm_max_4D_Bcast_f32xf32_f32(
out_data, out_shape, inp_data, inp_shape, min_data, min_shape);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);

} else {
WORD32 ret_val = xa_nn_elm_maximum_f32xf32_f32(
WORD32 ret_val = xa_nn_elm_max_f32xf32_f32(
out_data, inp_data, min_data, out.numel());

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
Expand Down
8 changes: 4 additions & 4 deletions backends/cadence/hifi/operators/op_eq.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -94,15 +94,15 @@ Tensor& eq_Tensor_out(
for (int i = 0; i < b.dim(); i++)
inp2_shape[i + off_b] = b.size(i);

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, 4);
WORD32 ret_val = xa_nn_elm_compare_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, COMPARE_EQUAL);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
} else {
int num_elm = out.numel();

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, 4);
WORD32 ret_val = xa_nn_elm_compare_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, COMPARE_EQUAL);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
}
Expand Down
8 changes: 4 additions & 4 deletions backends/cadence/hifi/operators/op_ge.cpp
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Expand Up @@ -94,15 +94,15 @@ Tensor& ge_Tensor_out(
for (int i = 0; i < b.dim(); i++)
inp2_shape[i + off_b] = b.size(i);

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, 0);
WORD32 ret_val = xa_nn_elm_compare_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, COMPARE_GREATEREQUAL);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
} else {
int num_elm = out.numel();

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, 0);
WORD32 ret_val = xa_nn_elm_compare_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, COMPARE_GREATEREQUAL);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
}
Expand Down
8 changes: 4 additions & 4 deletions backends/cadence/hifi/operators/op_gt.cpp
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Expand Up @@ -96,15 +96,15 @@ Tensor& gt_Tensor_out(
for (int i = 0; i < b.dim(); i++)
inp2_shape[i + off_b] = b.size(i);

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, 1);
WORD32 ret_val = xa_nn_elm_compare_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, COMPARE_GREATER);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
} else {
int num_elm = out.numel();

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, 1);
WORD32 ret_val = xa_nn_elm_compare_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, COMPARE_GREATER);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
}
Expand Down
8 changes: 4 additions & 4 deletions backends/cadence/hifi/operators/op_le.cpp
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Expand Up @@ -95,15 +95,15 @@ Tensor& le_Tensor_out(
for (int i = 0; i < b.dim(); i++)
inp2_shape[i + off_b] = b.size(i);

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, 2);
WORD32 ret_val = xa_nn_elm_compare_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, COMPARE_LESSEREQUAL);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
} else {
int num_elm = out.numel();

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, 2);
WORD32 ret_val = xa_nn_elm_compare_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, COMPARE_LESSEREQUAL);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
}
Expand Down
8 changes: 4 additions & 4 deletions backends/cadence/hifi/operators/op_lt.cpp
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Expand Up @@ -93,15 +93,15 @@ Tensor& lt_Tensor_out(
for (int i = 0; i < b.dim(); i++)
inp2_shape[i + off_b] = b.size(i);

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, 3);
WORD32 ret_val = xa_nn_elm_compare_broadcast_4D_f32xf32_f32(
p_out, out_shape, p_inp1, inp1_shape, p_inp2, inp2_shape, COMPARE_LESSER);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
} else {
int num_elm = out.numel();

WORD32 ret_val = xa_nn_elm_greater_lesser_equal_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, 3);
WORD32 ret_val = xa_nn_elm_compare_f32xf32_f32(
p_out, p_inp1, p_inp2, num_elm, COMPARE_LESSER);

ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out);
}
Expand Down
4 changes: 2 additions & 2 deletions backends/cadence/hifi/operators/op_maximum.cpp
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Expand Up @@ -141,10 +141,10 @@ Tensor& maximum_out(
for (int i = 0; i < b.dim(); i++)
inp2_shape[i + off_b] = b.size(i);

xa_nn_elm_maximum_broadcast_4D_f32xf32_f32(
xa_nn_elm_max_4D_Bcast_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());
xa_nn_elm_max_f32xf32_f32(out_data, a_data, b_data, out.numel());
}
return out;
}
Expand Down
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