tract-linalg 0.23.0-dev.4

Tiny, no-nonsense, self contained, TensorFlow and ONNX inference
Documentation 
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use crate::Ops;
use crate::frame::mmm::ImplementationQuality::ManuallyOptimized;
use crate::pack::PackedFormat;

const NEON: fn() -> bool = || crate::arm32::has_neon();

MMMExternKernel!(armv7neon_mmm_f32_8x4_cortexa7 <f32>( 8, 4)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_8x4_cortexa9 <f32>( 8, 4)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_8x4_generic  <f32>( 8, 4)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_8x6_cortexa7 <f32>( 8, 6)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_8x6_cortexa9 <f32>( 8, 6)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_8x6_generic  <f32>( 8, 6)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_8x1_generic  <f32>( 8, 1)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_32x1_cortexa7<f32>(32, 1)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_32x1_cortexa9<f32>(32, 1)@(16, 4) where(NEON) quality(ManuallyOptimized));
MMMExternKernel!(armv7neon_mmm_f32_32x1_generic <f32>(32, 1)@(16, 4) where(NEON) quality(ManuallyOptimized));

MMMExternKernel!(armv7neon_mmm_i32_8x4<i32>(8, 4)@(32, 4) where(NEON)
  packing[1] = i8i8 => |k| k.with_packing(PackedFormat::new(DatumType::I8, 8, 32), PackedFormat::new(DatumType::I8, 4, 32));
  quality(ManuallyOptimized)
  store(i8)
);

MMMExternKernel!(armv7neon_mmm_i32_32x1<i32>(32, 1)@(32, 4) where(NEON)
  packing[1] = i8i8 => |k| k.with_packing(PackedFormat::new(DatumType::I8, 32, 32), PackedFormat::new(DatumType::I8, 1, 4));
  quality(ManuallyOptimized)
  store(i8)
);

pub fn plug(ops: &mut Ops) {
    ops.mmm_impls.extend_from_slice(&[
        armv7neon_mmm_f32_8x4_cortexa7.mmm(),
        armv7neon_mmm_f32_8x4_cortexa9.mmm(),
        armv7neon_mmm_f32_8x4_generic.mmm(),
        armv7neon_mmm_f32_8x6_cortexa7.mmm(),
        armv7neon_mmm_f32_8x6_cortexa9.mmm(),
        armv7neon_mmm_f32_8x6_generic.mmm(),
        armv7neon_mmm_f32_8x1_generic.mmm(),
        armv7neon_mmm_f32_32x1_cortexa7.mmm(),
        armv7neon_mmm_f32_32x1_cortexa9.mmm(),
        armv7neon_mmm_f32_32x1_generic.mmm(),
    ]);
}

sigmoid_impl!(f32, armv7neon_sigmoid_f32_4n, 4, 4, crate::arm32::has_neon());
tanh_impl!(f32, armv7neon_tanh_f32_4n, 4, 4, crate::arm32::has_neon());