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ggml : same IQ4_NL quantization for CPU/CUDA/Metal (#6196)
* Make quantize_row_iq4_nl do the same thing is quantization on CUDA * Make quantize_row_iq4_nl do the same thing is quantization on CUDA This time for real. backend-ops tests pass. * Now fix test-quantize-fns --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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@ -11705,9 +11705,8 @@ static void quantize_row_iq4_nl_impl(const int super_block_size, const int block
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ggml_fp16_t * dh, uint8_t * q4, uint16_t * scales_h, uint8_t * scales_l,
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float * scales, float * weight, uint8_t * L,
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const int8_t * values,
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const float * quant_weights) {
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const int ntry = 7;
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const float * quant_weights,
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const int ntry) {
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float sigma2 = 0;
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for (int j = 0; j < super_block_size; ++j) sigma2 += x[j]*x[j];
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@ -11719,6 +11718,7 @@ static void quantize_row_iq4_nl_impl(const int super_block_size, const int block
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float max_scale = 0, amax_scale = 0;
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for (int ib = 0; ib < super_block_size/block_size; ++ib) {
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const float * xb = x + ib*block_size;
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uint8_t * Lb = L + ib*block_size;
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if (quant_weights) {
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const float * qw = quant_weights + ib*block_size;
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for (int j = 0; j < block_size; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]);
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@ -11736,12 +11736,13 @@ static void quantize_row_iq4_nl_impl(const int super_block_size, const int block
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scales[ib] = 0;
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continue;
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}
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float d = -max/values[0];
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float d = ntry > 0 ? -max/values[0] : max/values[0];
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float id = 1/d;
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float sumqx = 0, sumq2 = 0;
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for (int j = 0; j < block_size; ++j) {
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float al = id*xb[j];
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int l = best_index_int8(16, values, al);
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Lb[j] = l;
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float q = values[l];
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float w = weight[j];
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sumqx += w*q*xb[j];
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@ -11796,9 +11797,11 @@ static void quantize_row_iq4_nl_impl(const int super_block_size, const int block
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}
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} else {
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dh[0] = GGML_FP32_TO_FP16(scales[0]);
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float id = scales[0] ? 1/scales[0] : 0;
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for (int j = 0; j < super_block_size; ++j) {
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L[j] = best_index_int8(16, values, id*x[j]);
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if (ntry > 0) {
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float id = scales[0] ? 1/scales[0] : 0;
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for (int j = 0; j < super_block_size; ++j) {
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L[j] = best_index_int8(16, values, id*x[j]);
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}
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}
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}
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@ -11823,7 +11826,7 @@ size_t quantize_iq4_nl(const float * restrict src, void * restrict dst, int nrow
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for (int ibl = 0; ibl < nblock; ++ibl) {
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const float * qw = quant_weights ? quant_weights + QK4_NL*ibl : NULL;
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quantize_row_iq4_nl_impl(QK4_NL, 32, src + QK4_NL*ibl, &iq4[ibl].d, iq4[ibl].qs, &unused_h, unused_l,
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&scale, weight, L, kvalues_iq4nl, qw);
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&scale, weight, L, kvalues_iq4nl, qw, 7);
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}
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src += n_per_row;
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qrow += nblock*sizeof(block_iq4_nl);
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@ -11832,14 +11835,23 @@ size_t quantize_iq4_nl(const float * restrict src, void * restrict dst, int nrow
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}
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void quantize_row_iq4_nl(const float * restrict x, void * restrict vy, int k) {
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assert(k % QK4_NL == 0);
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block_iq4_nl * restrict y = vy;
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quantize_row_iq4_nl_reference(x, y, k);
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GGML_ASSERT(k%QK4_NL == 0);
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int nblock = k/QK4_NL;
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uint8_t L[QK4_NL];
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float weight[QK4_NL];
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uint16_t unused_h;
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uint8_t * unused_l = NULL;
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float scale;
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block_iq4_nl * iq4 = (block_iq4_nl *)vy;
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for (int ibl = 0; ibl < nblock; ++ibl) {
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quantize_row_iq4_nl_impl(QK4_NL, 32, x + QK4_NL*ibl, &iq4[ibl].d, iq4[ibl].qs, &unused_h, unused_l,
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&scale, weight, L, kvalues_iq4nl, NULL, -1);
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}
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}
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void quantize_row_iq4_nl_reference(const float * restrict x, block_iq4_nl * restrict y, int k) {
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assert(k % QK4_NL == 0);
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quantize_iq4_nl(x, y, 1, k, NULL);
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quantize_row_iq4_nl(x, y, k);
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}
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size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
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@ -11857,7 +11869,7 @@ size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int nrow
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for (int ibl = 0; ibl < nblock; ++ibl) {
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const float * qw = quant_weights ? quant_weights + QK_K*ibl : NULL;
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quantize_row_iq4_nl_impl(QK_K, 32, src + QK_K*ibl, &iq4[ibl].d, iq4[ibl].qs, &iq4[ibl].scales_h, iq4[ibl].scales_l,
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scales, weight, L, kvalues_iq4nl, qw);
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scales, weight, L, kvalues_iq4nl, qw, 7);
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}
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src += n_per_row;
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qrow += nblock*sizeof(block_iq4_xs);
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