Safetensors
GGUF
Turkish
llama
Llama-3
instruct
finetune
chatml
gpt4
synthetic data
distillation
function calling
json mode
axolotl
roleplaying
chat
Instructions to use tda45/TdAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use tda45/TdAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tda45/TdAI", filename="llama.cpp/models/ggml-vocab-aquila.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tda45/TdAI with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf tda45/TdAI # Run inference directly in the terminal: ./llama-cli -hf tda45/TdAI
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf tda45/TdAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf tda45/TdAI
Use Docker
docker model run hf.co/tda45/TdAI
- LM Studio
- Jan
- Ollama
How to use tda45/TdAI with Ollama:
ollama run hf.co/tda45/TdAI
- Unsloth Studio
How to use tda45/TdAI with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tda45/TdAI to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tda45/TdAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tda45/TdAI to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tda45/TdAI with Docker Model Runner:
docker model run hf.co/tda45/TdAI
- Lemonade
How to use tda45/TdAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tda45/TdAI
Run and chat with the model
lemonade run user.TdAI-{{QUANT_TAG}}List all available models
lemonade list
| // clang-format off | |
| // clang-format on | |
| template <int K> constexpr int QK_0() { | |
| if constexpr (K == 4) { | |
| return QK4_0; | |
| } | |
| if constexpr (K == 8) { | |
| return QK8_0; | |
| } | |
| return -1; | |
| } | |
| template <int K, int N> struct block { | |
| ggml_half d[N]; // deltas for N qK_0 blocks | |
| uint8_t qs[(QK_0<K>() * N * K) / 8]; // quants for N qK_0 blocks | |
| }; | |
| template <int K, int N> struct block_with_zp { | |
| ggml_half d[N]; // deltas for N qK_1 blocks | |
| uint8_t zp[N]; // zero points for N qK_1 blocks | |
| uint8_t qs[(QK_0<K>() * N * K) / 8]; // quants for N qK_1 blocks | |
| }; | |
| // control size | |
| static_assert(sizeof(block<4, 16>) == 16 * sizeof(ggml_half) + QK4_0 * 8, "wrong block<4,16> size/padding"); | |
| static_assert(sizeof(block_with_zp<4, 16>) == 16 * sizeof(ggml_half) + QK4_0 * 8 + 16 * sizeof(uint8_t), | |
| "wrong block_with_zp<4,16> size/padding"); | |
| static_assert(sizeof(block<8, 16>) == 16 * sizeof(ggml_half) + QK4_0 * 16, "wrong block<8,16> size/padding"); | |
| static_assert(sizeof(block<4, 32>) == 32 * sizeof(ggml_half) + QK4_0 * 16, "wrong block<4,32> size/padding"); | |
| static_assert(sizeof(block_with_zp<4, 32>) == 32 * sizeof(ggml_half) + QK4_0 * 16 + 32 * sizeof(uint8_t), | |
| "wrong block_with_zp<4,32> size/padding"); | |
| using block_q4_0x16 = block<4, 16>; | |
| using block_q4_1x16 = block_with_zp<4, 16>; | |
| using block_q8_0x16 = block<8, 16>; | |
| using block_q4_0x32 = block<4, 32>; | |
| using block_q4_1x32 = block_with_zp<4, 32>; | |
| using block_q8_0x32 = block<8, 32>; | |
| struct block_q4_0x32x256 { | |
| block_q4_0x32 blocks[8]; // [f16 * 32 | i4 * 32 * 32] * 8 | |
| }; | |
| struct block_q4_1x32x256 { | |
| block_q4_0x32 blocks[8]; | |
| uint8_t zps[32 * 8]; | |
| }; | |
| static block_q4_0x16 make_block_q4_0x16(block_q4_0 * in, unsigned int blck_size_interleave) { | |
| block_q4_0x16 out; | |
| GGML_ASSERT(QK4_0 / blck_size_interleave == 2); | |
| for (int i = 0; i < 16; i++) { | |
| out.d[i] = in[i].d; | |
| } | |
| for (int i = 0; i < 16; i++) { | |
| // [0, 15], in.d & 0x0F | |
| for (int j = 0; j < QK4_0 / 4; j++) { | |
| //src [b0 b16] ......... [b8 b24] ......... [b15 b31] | |
| //dst [b0 b8] ......... [b7 b15] | |
| out.qs[i * QK4_0 / 4 + j] = (in[i].qs[j] & 0x0F) | ((in[i].qs[j + QK4_0 / 4] & 0x0F) << 4); | |
| } | |
| } | |
| for (int i = 0; i < 16; i++) { | |
| // [16, 31], in.d & 0xF0 | |
| for (int j = 0; j < QK4_0 / 4; j++) { | |
| //src [b0 b16] ......... [b8 b24] ......... [b15 b31] | |
| //dst [b16 b24] ......... [b23 b31] | |
| out.qs[4 * QK4_0 + i * QK4_0 / 4 + j] = ((in[i].qs[j] & 0xF0) >> 4) | (in[i].qs[j + QK4_0 / 4] & 0xF0); | |
| } | |
| } | |
| return out; | |
| } | |
| static block_q4_1x16 make_block_q4_1x16(block_q4_1 * in, unsigned int blck_size_interleave) { | |
| block_q4_1x16 out; | |
| GGML_ASSERT(QK4_1 / blck_size_interleave == 2); | |
| for (int i = 0; i < 16; i++) { | |
| float d = GGML_FP16_TO_FP32(in[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d); | |
| float m = GGML_FP16_TO_FP32(in[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m); | |
| float mid = -std::nearbyintf(m / d); | |
| mid = std::min(15.0f, std::max(0.0f, mid)); | |
| out.d[i] = GGML_FP32_TO_FP16(d); | |
| out.zp[i] = static_cast<uint8_t>(mid); | |
| } | |
| for (int i = 0; i < 16; i++) { | |
| // [0, 15], in.d & 0x0F | |
| for (int j = 0; j < QK4_1 / 4; j++) { | |
| //src [b0 b16] ......... [b8 b24] ......... [b15 b31] | |
| //dst [b0 b8] ......... [b7 b15] | |
| out.qs[i * QK4_1 / 4 + j] = (in[i].qs[j] & 0x0F) | ((in[i].qs[j + QK4_1 / 4] & 0x0F) << 4); | |
| } | |
| } | |
| for (int i = 0; i < 16; i++) { | |
| // [16, 31], in.d & 0xF0 | |
| for (int j = 0; j < QK4_1 / 4; j++) { | |
| //src [b0 b16] ......... [b8 b24] ......... [b15 b31] | |
| //dst [b16 b24] ......... [b23 b31] | |
| out.qs[4 * QK4_1 + i * QK4_1 / 4 + j] = ((in[i].qs[j] & 0xF0) >> 4) | (in[i].qs[j + QK4_1 / 4] & 0xF0); | |
| } | |
| } | |
| return out; | |
| } | |
| static int repack_q4_0_to_q4_0_16_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_0); | |
| GGML_ASSERT(interleave_block == 16); | |
| constexpr int nrows_interleaved = 16; | |
| block_q4_0x16 * dst = (block_q4_0x16 *) t->data; | |
| const block_q4_0 * src = (const block_q4_0 *) data; | |
| block_q4_0 dst_tmp[16]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK4_0; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| dst_tmp[i] = src[x + i * nblocks]; | |
| } | |
| *dst++ = make_block_q4_0x16(dst_tmp, interleave_block); | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static int repack_q4_1_to_q4_1_16_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_1); | |
| GGML_ASSERT(interleave_block == 16); | |
| constexpr int nrows_interleaved = 16; | |
| block_q4_1x16 * dst = (block_q4_1x16 *) t->data; | |
| const block_q4_1 * src = (const block_q4_1 *) data; | |
| block_q4_1 dst_tmp[16]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK4_1; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_1)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_1 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| dst_tmp[i] = src[x + i * nblocks]; | |
| } | |
| *dst++ = make_block_q4_1x16(dst_tmp, interleave_block); | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static inline void get_scale_min_k4(int j, | |
| const uint8_t * GGML_RESTRICT q, | |
| uint8_t * GGML_RESTRICT d, | |
| uint8_t * GGML_RESTRICT m) { | |
| if (j < 4) { | |
| *d = q[j] & 63; | |
| *m = q[j + 4] & 63; | |
| } else { | |
| *d = (q[j + 4] & 0xF) | ((q[j - 4] >> 6) << 4); | |
| *m = (q[j + 4] >> 4) | ((q[j - 0] >> 6) << 4); | |
| } | |
| } | |
| static int repack_q4_k_to_q4_1_16_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_K); | |
| GGML_ASSERT(interleave_block == 16); | |
| GGML_ASSERT(QK_K / QK4_1 == 8); | |
| constexpr int nrows_interleaved = 16; | |
| block_q4_1x16 * dst = (block_q4_1x16 *) t->data; | |
| const block_q4_K * src = (const block_q4_K *) data; | |
| block_q4_1 dst_tmp[16]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK_K; | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int j = 0; j < 8; j++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| uint8_t sc, m; | |
| const float d = GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d); | |
| const float min = | |
| GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.dmin); | |
| get_scale_min_k4(j, src[x + i * nblocks].scales, &sc, &m); | |
| const float d1 = d * sc; | |
| const float m1 = min * m; | |
| dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d = GGML_FP32_TO_FP16(d1); | |
| dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m = GGML_FP32_TO_FP16(-m1); | |
| // src -> [b0, b32] [b1, b33] ... [b31, b63] | |
| // dst -> [b0, b16] [b1, b17] ... [b15, b31] [b32, b48] [b33, b49] ... [b47, b63] | |
| const uint8_t * q = src[x + i * nblocks].qs + (j / 2) * QK4_1; | |
| if (j % 2 == 0) { | |
| for (int ii = 0; ii < 16; ii++) { | |
| dst_tmp[i].qs[ii] = (q[ii] & 0x0F) | ((q[ii + 16] & 0x0F) << 4); | |
| } | |
| } else { | |
| for (int ii = 0; ii < 16; ii++) { | |
| dst_tmp[i].qs[ii] = ((q[ii] & 0xF0) >> 4) | (q[ii + 16] & 0xF0); | |
| } | |
| } | |
| } | |
| *dst++ = make_block_q4_1x16(dst_tmp, interleave_block); | |
| } | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static block_q4_0x32 make_block_q4_0x32(block_q4_0 * in, unsigned int blck_size_interleave) { | |
| block_q4_0x32 out; | |
| assert(QK4_0 / blck_size_interleave == 1); | |
| GGML_UNUSED(blck_size_interleave); | |
| for (int i = 0; i < 32; i++) { | |
| out.d[i] = in[i].d; | |
| } | |
| for (int i = 0; i < 32; i++) { | |
| // [0, 15], in.d & 0x0F | |
| for (int j = 0; j < QK4_0 / 4; j++) { | |
| //src [b0 b16] ......... [b8 b24] ......... [b15 b31] | |
| //dst [b0 b1] ......... [b14 b15] | |
| out.qs[i * QK4_0 / 2 + j] = (in[i].qs[j * 2] & 0x0F) | ((in[i].qs[j * 2 + 1] & 0x0F) << 4); | |
| } | |
| } | |
| for (int i = 0; i < 32; i++) { | |
| // [16, 31], in.d & 0xF0 | |
| for (int j = 0; j < QK4_0 / 4; j++) { | |
| //src [b0 b16] ......... [b8 b24] ......... [b15 b31] | |
| //dst [b16 b17] ......... [b30 b31] | |
| out.qs[i * QK4_0 / 2 + QK4_0 / 4 + j] = ((in[i].qs[j * 2] & 0xF0) >> 4) | (in[i].qs[j * 2 + 1] & 0xF0); | |
| } | |
| } | |
| return out; | |
| } | |
| static block_q4_1x32 make_block_q4_1x32(block_q4_1 * in, unsigned int blck_size_interleave) { | |
| block_q4_1x32 out; | |
| GGML_ASSERT(QK4_1 / blck_size_interleave == 1); | |
| GGML_UNUSED(blck_size_interleave); | |
| for (int i = 0; i < 32; i++) { | |
| float d = GGML_FP16_TO_FP32(in[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d); | |
| float m = GGML_FP16_TO_FP32(in[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m); | |
| float mid = -std::nearbyintf(m / d); | |
| mid = std::min(15.0f, std::max(0.0f, mid)); | |
| out.d[i] = GGML_FP32_TO_FP16(d); | |
| out.zp[i] = static_cast<uint8_t>(mid); | |
| } | |
| for (int i = 0; i < 32; i++) { | |
| // [0, 15], in.d & 0x0F | |
| for (int j = 0; j < QK4_1 / 4; j++) { | |
| //src [b0 b16] ......... [b8 b24] ......... [b15 b31] | |
| //dst [b0 b1] ......... [b14 b15] | |
| out.qs[i * QK4_1 / 2 + j] = (in[i].qs[j * 2] & 0x0F) | ((in[i].qs[j * 2 + 1] & 0x0F) << 4); | |
| } | |
| } | |
| for (int i = 0; i < 32; i++) { | |
| // [16, 31], in.d & 0xF0 | |
| for (int j = 0; j < QK4_1 / 4; j++) { | |
| //src [b0 b16] ......... [b8 b24] ......... [b15 b31] | |
| //dst [b16 b24] ......... [b23 b31] | |
| out.qs[i * QK4_1 / 2 + QK4_1 / 4 + j] = ((in[i].qs[j * 2] & 0xF0) >> 4) | (in[i].qs[j * 2 + 1] & 0xF0); | |
| } | |
| } | |
| return out; | |
| } | |
| static block_q8_0x32 make_block_q8_0x32(block_q8_0 * in, unsigned int blck_size_interleave) { | |
| block_q8_0x32 out; | |
| GGML_ASSERT(QK8_0 / blck_size_interleave == 1); | |
| GGML_UNUSED(blck_size_interleave); | |
| for (int i = 0; i < 32; i++) { | |
| out.d[i] = in[i].d; | |
| } | |
| for (int i = 0; i < 32; i++) { | |
| memcpy(out.qs + i * QK8_0, in[i].qs, QK8_0); | |
| } | |
| return out; | |
| } | |
| static int repack_q2_k_to_q2_k_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q2_K); | |
| GGML_ASSERT(interleave_block == 32); | |
| GGML_ASSERT(QK_K == 256); | |
| constexpr int nrows_interleaved = 32; | |
| const block_q2_K * src = (const block_q2_K *) data; | |
| auto * dst = (spacemit_kernels::nrow_block_q2_k<32> *) t->data; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK_K; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q2_K)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) { | |
| return -1; | |
| } | |
| uint8_t qs_aux[256] = { 0 }; | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| const block_q2_K * src_block = &src[(b + i) * nblocks + x]; | |
| // scale for [16, N] | |
| for (int j = 0; j < 16; j++) { | |
| auto zp_aux = (dst->scales[j * nrows_interleaved + i]) & 0xF0; | |
| dst->scales[j * nrows_interleaved + i] = (src_block->scales[j] & 0x0F) | zp_aux; | |
| } | |
| // zp for [N, 16] | |
| for (int j = 0; j < 16; j++) { | |
| auto scale_aux = (dst->scales[16 * i + j]) & 0x0F; | |
| dst->scales[16 * i + j] = (src_block->scales[j] & 0xF0) | scale_aux; | |
| } | |
| for (int k = 0; k < 4; k++) { | |
| for (int j = 0; j < 32; j++) { | |
| qs_aux[k * 32 + j] = (src_block->qs[j] >> (2 * k)) & 0x03; | |
| } | |
| } | |
| for (int k = 0; k < 4; k++) { | |
| for (int j = 0; j < 32; j++) { | |
| qs_aux[k * 32 + j + 128] = (src_block->qs[j + 32] >> (2 * k)) & 0x03; | |
| } | |
| } | |
| // from nrows_interleaved * [2 * 32byte] | |
| // to 4 * [nrows_interleaved * 16byte] | |
| for (int k = 0; k < 4; k++) { | |
| for (int j = 0; j < 16; j++) { | |
| uint8_t qs0 = qs_aux[j + k * 64]; | |
| uint8_t qs16 = qs_aux[j + 16 + k * 64]; | |
| uint8_t qs32 = qs_aux[j + 32 + k * 64]; | |
| uint8_t qs48 = qs_aux[j + 48 + k * 64]; | |
| dst->qs[(k * nrows_interleaved + i) * 16 + j] = | |
| (qs0 & 0x03) | ((qs16 & 0x03) << 2) | ((qs32 & 0x03) << 4) | ((qs48 & 0x03) << 6); | |
| } | |
| } | |
| dst->scales16[i] = src_block->GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d; | |
| dst->zeros16[i] = src_block->GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.dmin; | |
| } | |
| dst++; | |
| } | |
| } | |
| return 0; | |
| } | |
| static int repack_q3_k_to_q3_k_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q3_K); | |
| GGML_ASSERT(interleave_block == 32); | |
| GGML_ASSERT(QK_K == 256); | |
| constexpr int nrows_interleaved = 32; | |
| const uint32_t kmask1 = 0x03030303; | |
| const uint32_t kmask2 = 0x0f0f0f0f; | |
| const block_q3_K * src = (const block_q3_K *) data; | |
| auto * dst = (spacemit_kernels::nrow_block_q3_k<32> *) t->data; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK_K; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q3_K)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) { | |
| return -1; | |
| } | |
| uint32_t b_scale_aux[4] = { 0 }; | |
| uint8_t qs_aux[256] = { 0 }; | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| const block_q3_K * src_block = &src[(b + i) * nblocks + x]; | |
| uint32_t * auxs = b_scale_aux; | |
| int8_t * scale = (int8_t *) auxs; | |
| memcpy(auxs, src_block->scales, 12); | |
| uint32_t tmp = auxs[2]; | |
| auxs[2] = ((auxs[0] >> 4) & kmask2) | (((tmp >> 4) & kmask1) << 4); | |
| auxs[3] = ((auxs[1] >> 4) & kmask2) | (((tmp >> 6) & kmask1) << 4); | |
| auxs[0] = (auxs[0] & kmask2) | (((tmp >> 0) & kmask1) << 4); | |
| auxs[1] = (auxs[1] & kmask2) | (((tmp >> 2) & kmask1) << 4); | |
| for (int j = 0; j < 16; j++) { | |
| dst->scales[j * nrows_interleaved + i] = scale[j] - 32; | |
| } | |
| for (int k = 0; k < 4; k++) { | |
| for (int j = 0; j < 32; j++) { | |
| qs_aux[k * 32 + j] = (src_block->qs[j] >> (2 * k)) & 0x03; | |
| } | |
| } | |
| for (int k = 0; k < 4; k++) { | |
| for (int j = 0; j < 32; j++) { | |
| qs_aux[k * 32 + j + 128] = (src_block->qs[j + 32] >> (2 * k)) & 0x03; | |
| } | |
| } | |
| // from nrows_interleaved * [2 * 32byte] | |
| // to 4 * [nrows_interleaved * 16byte] | |
| for (int k = 0; k < 4; k++) { | |
| for (int j = 0; j < 16; j++) { | |
| uint8_t qs0 = qs_aux[j + k * 64]; | |
| uint8_t qs16 = qs_aux[j + 16 + k * 64]; | |
| uint8_t qs32 = qs_aux[j + 32 + k * 64]; | |
| uint8_t qs48 = qs_aux[j + 48 + k * 64]; | |
| dst->qs[(k * nrows_interleaved + i) * 16 + j] = | |
| (qs0 & 0x03) | ((qs16 & 0x03) << 2) | ((qs32 & 0x03) << 4) | ((qs48 & 0x03) << 6); | |
| } | |
| } | |
| //memcpy(dst->hmask + i * 32, src_block->hmask, 32); | |
| // from nrows_interleaved * [32byte] | |
| // to 16 * [nrows_interleaved * uint16_t] | |
| uint16_t * dst_mask = ((uint16_t *) dst->hmask) + i; | |
| for (int j = 0; j < 16; j++, dst_mask += nrows_interleaved) { | |
| uint8_t b_shift = j / 2; | |
| uint8_t * b_mask_col = (uint8_t *) (src_block->hmask + (j % 2) * 16); | |
| // b0 - b15 | |
| uint16_t msk_out_0 = 0; | |
| for (int k = 0; k < 8; k++) { | |
| msk_out_0 |= (uint16_t) ((b_mask_col[k] >> b_shift) & 0x01) << k; | |
| } | |
| for (int k = 8; k < 16; k++) { | |
| msk_out_0 |= (uint16_t) ((b_mask_col[k] >> b_shift) & 0x01) << k; | |
| } | |
| dst_mask[0] = msk_out_0; | |
| } | |
| dst->scales16[i] = src_block->d; | |
| } | |
| dst++; | |
| } | |
| } | |
| return 0; | |
| } | |
| static int repack_q4_0_to_q4_0_32_bl_ref(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_0); | |
| GGML_ASSERT(interleave_block == 32); // unused | |
| constexpr int nrows_interleaved = 32; | |
| block_q4_0x32 * dst = (block_q4_0x32 *) t->data; | |
| const block_q4_0 * src = (const block_q4_0 *) data; | |
| block_q4_0 dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK4_0; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| dst_tmp[i] = src[x + i * nblocks]; | |
| } | |
| *dst++ = make_block_q4_0x32(dst_tmp, interleave_block); | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static int repack_q4_0_to_q4_0_256_32_bl_ref(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_0); | |
| GGML_ASSERT(interleave_block == 32); // unused | |
| constexpr int nrows_interleaved = 32; | |
| block_q4_0x32x256 * dst = (block_q4_0x32x256 *) t->data; | |
| const block_q4_0 * src = (const block_q4_0 *) data; | |
| block_q4_0 dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK4_0; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0)); | |
| GGML_ASSERT(nblocks % 8 == 0); // for 256-block interleaving | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x += 8) { | |
| for (int j = 0; j < 8; j++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| dst_tmp[i] = src[x + j + i * nblocks]; | |
| } | |
| dst->blocks[j] = make_block_q4_0x32(dst_tmp, interleave_block); | |
| } | |
| dst++; | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static int repack_q4_0_to_q4_1_256_32_bl_ref(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_1); | |
| GGML_ASSERT(interleave_block == 32); // unused | |
| constexpr int nrows_interleaved = 32; | |
| block_q4_1x32x256 * dst = (block_q4_1x32x256 *) t->data; | |
| const block_q4_1 * src = (const block_q4_1 *) data; | |
| block_q4_1 dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK4_0; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_1)); | |
| GGML_ASSERT(nblocks % 8 == 0); // for 256-block interleaving | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x += 8) { | |
| for (int j = 0; j < 8; j++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| dst_tmp[i] = src[x + j + i * nblocks]; | |
| } | |
| block_q4_0x32 * dst_block = &dst->blocks[j]; | |
| uint8_t * dst_zp = dst->zps + j * nrows_interleaved; | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| float d = GGML_FP16_TO_FP32(dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d); | |
| float m = GGML_FP16_TO_FP32(dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m); | |
| float mid = -std::nearbyintf(m / d); | |
| mid = std::min(15.0f, std::max(0.0f, mid)); | |
| dst_block->d[i] = GGML_FP32_TO_FP16(d); | |
| dst_zp[i] = static_cast<uint8_t>(mid); | |
| } | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| for (int k = 0; k < QK4_1 / 4; k++) { | |
| dst_block->qs[i * QK4_1 / 2 + k] = | |
| (dst_tmp[i].qs[k * 2] & 0x0F) | ((dst_tmp[i].qs[k * 2 + 1] & 0x0F) << 4); | |
| } | |
| } | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| for (int k = 0; k < QK4_1 / 4; k++) { | |
| dst_block->qs[i * QK4_1 / 2 + QK4_1 / 4 + k] = | |
| ((dst_tmp[i].qs[k * 2] & 0xF0) >> 4) | (dst_tmp[i].qs[k * 2 + 1] & 0xF0); | |
| } | |
| } | |
| } | |
| dst++; | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| // RVV optimized version of repack_q4_0_to_q4_0_32_bl | |
| // Eliminates the intermediate dst_tmp buffer and vectorizes nibble repack. | |
| static int repack_q4_0_to_q4_0_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_0); | |
| GGML_ASSERT(interleave_block == 32); | |
| constexpr int nrows_interleaved = 32; | |
| constexpr int qs_bytes = QK4_0 / 2; // 16 | |
| block_q4_0x32 * dst = (block_q4_0x32 *) t->data; | |
| const block_q4_0 * src = (const block_q4_0 *) data; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK4_0; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_0 != 0) { | |
| return -1; | |
| } | |
| const ptrdiff_t row_stride = (ptrdiff_t) nblocks * sizeof(block_q4_0); | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| const block_q4_0 * col_src = src + x; | |
| // --- 1) Gather 32 scale values (ggml_half d) with stride load --- | |
| // d is at offset 0 of each block_q4_0, stride between rows = row_stride | |
| { | |
| const uint8_t * d_base = (const uint8_t *) &col_src->d; | |
| ggml_half * d_dst = dst->d; | |
| size_t remaining = 32; | |
| size_t offset = 0; | |
| while (remaining > 0) { | |
| size_t vl = __riscv_vsetvl_e16m1(remaining); | |
| vuint16m1_t vd = | |
| __riscv_vlse16_v_u16m1((const uint16_t *) (d_base + offset * row_stride), row_stride, vl); | |
| __riscv_vse16_v_u16m1((uint16_t *) (d_dst + offset), vd, vl); | |
| offset += vl; | |
| remaining -= vl; | |
| } | |
| } | |
| // --- 2) Nibble repack qs for each of the 32 rows --- | |
| // For each row i: | |
| // src qs[16]: [b0|b16] [b1|b17] ... [b15|b31] (lo nibble = b_j, hi nibble = b_{j+16}) | |
| // dst qs low 8B: (qs[2j] & 0x0F) | ((qs[2j+1] & 0x0F) << 4) for j=0..7 | |
| // dst qs high 8B: ((qs[2j] >> 4)) | (qs[2j+1] & 0xF0) for j=0..7 | |
| { | |
| const size_t vl8 = __riscv_vsetvl_e8m1(8); | |
| for (int i = 0; i < 32; i++) { | |
| const uint8_t * sq = col_src[i * nblocks].qs; | |
| uint8_t * dq = dst->qs + i * qs_bytes; | |
| // stride-2 load to separate even/odd bytes | |
| vuint8m1_t v_even = __riscv_vlse8_v_u8m1(sq, 2, vl8); // qs[0], qs[2], ..., qs[14] | |
| vuint8m1_t v_odd = __riscv_vlse8_v_u8m1(sq + 1, 2, vl8); // qs[1], qs[3], ..., qs[15] | |
| // low nibble part: (even & 0x0F) | ((odd & 0x0F) << 4) | |
| vuint8m1_t v_even_lo = __riscv_vand_vx_u8m1(v_even, 0x0F, vl8); | |
| vuint8m1_t v_odd_lo = __riscv_vand_vx_u8m1(v_odd, 0x0F, vl8); | |
| vuint8m1_t v_lo = __riscv_vor_vv_u8m1(v_even_lo, __riscv_vsll_vx_u8m1(v_odd_lo, 4, vl8), vl8); | |
| // high nibble part: (even >> 4) | (odd & 0xF0) | |
| vuint8m1_t v_even_hi = __riscv_vsrl_vx_u8m1(v_even, 4, vl8); | |
| vuint8m1_t v_odd_hi = __riscv_vand_vx_u8m1(v_odd, 0xF0, vl8); | |
| vuint8m1_t v_hi = __riscv_vor_vv_u8m1(v_even_hi, v_odd_hi, vl8); | |
| __riscv_vse8_v_u8m1(dq, v_lo, vl8); | |
| __riscv_vse8_v_u8m1(dq + 8, v_hi, vl8); | |
| } | |
| } | |
| dst++; | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static int repack_q4_1_to_q4_1_32_bl_ref(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_1); | |
| GGML_ASSERT(interleave_block == 32); // unused | |
| constexpr int nrows_interleaved = 32; | |
| block_q4_1x32 * dst = (block_q4_1x32 *) t->data; | |
| const block_q4_1 * src = (const block_q4_1 *) data; | |
| block_q4_1 dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK4_1; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_1)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_1 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| dst_tmp[i] = src[x + i * nblocks]; | |
| } | |
| *dst++ = make_block_q4_1x32(dst_tmp, interleave_block); | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| // RVV optimized version of repack_q4_1_to_q4_1_32_bl | |
| // Eliminates the intermediate dst_tmp buffer and vectorizes nibble repack + zp computation. | |
| static int repack_q4_1_to_q4_1_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_1); | |
| GGML_ASSERT(interleave_block == 32); | |
| constexpr int nrows_interleaved = 32; | |
| constexpr int qs_bytes = QK4_1 / 2; // 16 | |
| block_q4_1x32 * dst = (block_q4_1x32 *) t->data; | |
| const block_q4_1 * src = (const block_q4_1 *) data; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK4_1; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_1)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK4_1 != 0) { | |
| return -1; | |
| } | |
| const ptrdiff_t row_stride = (ptrdiff_t) nblocks * sizeof(block_q4_1); | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| const block_q4_1 * col_src = src + x; | |
| // --- 1) Gather d and m, compute zp = clamp(nearbyint(-m/d), 0, 15) --- | |
| // block_q4_1 layout: [d(f16), m(f16), qs[16]] | |
| // d is at byte offset 0, m is at byte offset 2 from each block start | |
| { | |
| const uint8_t * dm_base = (const uint8_t *) &col_src->GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d; | |
| ggml_half * d_dst = dst->d; | |
| uint8_t * zp_dst = dst->zp; | |
| size_t remaining = 32; | |
| size_t offset = 0; | |
| while (remaining > 0) { | |
| size_t vl = __riscv_vsetvl_e16m1(remaining); | |
| // stride load d (f16) from each row | |
| vuint16m1_t vd_raw = | |
| __riscv_vlse16_v_u16m1((const uint16_t *) (dm_base + offset * row_stride), row_stride, vl); | |
| __riscv_vse16_v_u16m1((uint16_t *) (d_dst + offset), vd_raw, vl); | |
| // stride load m (f16) from each row (offset +2 bytes from d) | |
| vuint16m1_t vm_raw = | |
| __riscv_vlse16_v_u16m1((const uint16_t *) (dm_base + 2 + offset * row_stride), row_stride, vl); | |
| // convert to f32 for zp computation: zp = nearbyint(-m / d) | |
| vfloat16m1_t vd_f16 = __riscv_vreinterpret_v_u16m1_f16m1(vd_raw); | |
| vfloat16m1_t vm_f16 = __riscv_vreinterpret_v_u16m1_f16m1(vm_raw); | |
| // -m / d in f16 directly (SpaceMIT X60 supports f16 arithmetic) | |
| vfloat16m1_t v_neg_m = __riscv_vfneg_v_f16m1(vm_f16, vl); | |
| vfloat16m1_t v_ratio = __riscv_vfdiv_vv_f16m1(v_neg_m, vd_f16, vl); | |
| // Convert to f32 for nearbyint, then clamp | |
| vfloat32m2_t v_ratio_f32 = __riscv_vfwcvt_f_f_v_f32m2(v_ratio, vl); | |
| // Use integer rounding: convert f32 -> int (rounds to nearest) | |
| vint32m2_t v_zp_i32 = __riscv_vfcvt_x_f_v_i32m2(v_ratio_f32, vl); | |
| // clamp to [0, 15] | |
| v_zp_i32 = __riscv_vmax_vx_i32m2(v_zp_i32, 0, vl); | |
| v_zp_i32 = __riscv_vmin_vx_i32m2(v_zp_i32, 15, vl); | |
| // narrow i32 -> u8 | |
| vint16m1_t v_zp_i16 = __riscv_vncvt_x_x_w_i16m1(v_zp_i32, vl); | |
| vint8mf2_t v_zp_i8 = __riscv_vncvt_x_x_w_i8mf2(v_zp_i16, vl); | |
| vuint8mf2_t v_zp_u8 = __riscv_vreinterpret_v_i8mf2_u8mf2(v_zp_i8); | |
| __riscv_vse8_v_u8mf2(zp_dst + offset, v_zp_u8, vl); | |
| offset += vl; | |
| remaining -= vl; | |
| } | |
| } | |
| // --- 2) Nibble repack qs for each of the 32 rows --- | |
| { | |
| const size_t vl8 = __riscv_vsetvl_e8m1(8); | |
| for (int i = 0; i < 32; i++) { | |
| const uint8_t * sq = col_src[i * nblocks].qs; | |
| uint8_t * dq = dst->qs + i * qs_bytes; | |
| // stride-2 load to separate even/odd bytes | |
| vuint8m1_t v_even = __riscv_vlse8_v_u8m1(sq, 2, vl8); | |
| vuint8m1_t v_odd = __riscv_vlse8_v_u8m1(sq + 1, 2, vl8); | |
| // low nibble part: (even & 0x0F) | ((odd & 0x0F) << 4) | |
| vuint8m1_t v_even_lo = __riscv_vand_vx_u8m1(v_even, 0x0F, vl8); | |
| vuint8m1_t v_odd_lo = __riscv_vand_vx_u8m1(v_odd, 0x0F, vl8); | |
| vuint8m1_t v_lo = __riscv_vor_vv_u8m1(v_even_lo, __riscv_vsll_vx_u8m1(v_odd_lo, 4, vl8), vl8); | |
| // high nibble part: (even >> 4) | (odd & 0xF0) | |
| vuint8m1_t v_even_hi = __riscv_vsrl_vx_u8m1(v_even, 4, vl8); | |
| vuint8m1_t v_odd_hi = __riscv_vand_vx_u8m1(v_odd, 0xF0, vl8); | |
| vuint8m1_t v_hi = __riscv_vor_vv_u8m1(v_even_hi, v_odd_hi, vl8); | |
| __riscv_vse8_v_u8m1(dq, v_lo, vl8); | |
| __riscv_vse8_v_u8m1(dq + 8, v_hi, vl8); | |
| } | |
| } | |
| dst++; | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static int repack_q4_k_to_q4_1_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q4_K); | |
| GGML_ASSERT(interleave_block == 32); | |
| GGML_ASSERT(QK_K / QK4_1 == 8); | |
| constexpr int nrows_interleaved = 32; | |
| block_q4_1x32 * dst = (block_q4_1x32 *) t->data; | |
| const block_q4_K * src = (const block_q4_K *) data; | |
| block_q4_1 dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK_K; | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int j = 0; j < 8; j++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| uint8_t sc, m; | |
| const float d = GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d); | |
| const float min = | |
| GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.dmin); | |
| get_scale_min_k4(j, src[x + i * nblocks].scales, &sc, &m); | |
| const float d1 = d * sc; | |
| const float m1 = min * m; | |
| dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d = GGML_FP32_TO_FP16(d1); | |
| dst_tmp[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m = GGML_FP32_TO_FP16(-m1); | |
| // src -> [b0, b32] [b1, b33] ... [b31, b63] | |
| // dst -> [b0, b16] [b1, b17] ... [b15, b31] [b32, b48] [b33, b49] ... [b47, b63] | |
| const uint8_t * q = src[x + i * nblocks].qs + (j / 2) * QK4_1; | |
| if (j % 2 == 0) { | |
| for (int ii = 0; ii < 16; ii++) { | |
| dst_tmp[i].qs[ii] = (q[ii] & 0x0F) | ((q[ii + 16] & 0x0F) << 4); | |
| } | |
| } else { | |
| for (int ii = 0; ii < 16; ii++) { | |
| dst_tmp[i].qs[ii] = ((q[ii] & 0xF0) >> 4) | (q[ii + 16] & 0xF0); | |
| } | |
| } | |
| } | |
| *dst++ = make_block_q4_1x32(dst_tmp, interleave_block); | |
| } | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static int repack_q6_k_to_q8_0_32_bl_ref(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q6_K); | |
| GGML_ASSERT(interleave_block == 32); | |
| GGML_ASSERT(QK_K / QK4_1 == 8); | |
| constexpr int nrows_interleaved = 32; | |
| block_q8_0x32 * dst = (block_q8_0x32 *) t->data; | |
| const block_q6_K * src = (const block_q6_K *) data; | |
| block_q8_0 dst_tmp[32]; | |
| int8_t aux8[QK4_1]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK_K; | |
| if (t->ne[0] % QK_K != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| int64_t nrow_real = std::min((int64_t) nrow - b, (int64_t) nrows_interleaved); | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int bi = 0; bi < 8; bi++) { | |
| int i = 0; | |
| for (; i < nrow_real; i++) { | |
| const uint8_t * q4 = src[x + i * nblocks].ql; | |
| const uint8_t * qh = src[x + i * nblocks].qh; | |
| const int8_t * scales = src[x + i * nblocks].scales; | |
| float d = GGML_FP16_TO_FP32(src[x + i * nblocks].d); | |
| q4 += 64 * (bi / 4); | |
| qh += 32 * (bi / 4); | |
| int8_t * GGML_RESTRICT a = aux8; | |
| int8_t bi_idx = bi % 4; | |
| if (bi_idx == 0) { | |
| for (int l = 0; l < 32; ++l) { | |
| a[l] = (int8_t) ((q4[l] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32; | |
| } | |
| } else if (bi_idx == 1) { | |
| for (int l = 0; l < 32; ++l) { | |
| a[l] = (int8_t) ((q4[l + 32] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32; | |
| } | |
| } else if (bi_idx == 2) { | |
| for (int l = 0; l < 32; ++l) { | |
| a[l] = (int8_t) ((q4[l + 0] >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32; | |
| } | |
| } else if (bi_idx == 3) { | |
| for (int l = 0; l < 32; ++l) { | |
| a[l] = (int8_t) ((q4[l + 32] >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32; | |
| } | |
| } | |
| a = aux8; | |
| float a_max_abs = 0.0f; | |
| float scale_0 = scales[bi * 2 + 0] * d; | |
| float scale_1 = scales[bi * 2 + 1] * d; | |
| for (int l = 0; l < 16; ++l) { | |
| a_max_abs = std::max(a_max_abs, std::abs(a[l] * scale_0)); | |
| } | |
| for (int l = 16; l < 32; ++l) { | |
| a_max_abs = std::max(a_max_abs, std::abs(a[l] * scale_1)); | |
| } | |
| float reflect_scale = a_max_abs / ((1 << 7) - 1); | |
| float reflect_scale_0 = scale_0 / reflect_scale; | |
| float reflect_scale_1 = scale_1 / reflect_scale; | |
| for (int l = 0; l < 16; ++l) { | |
| float a_temp = std::clamp(std::nearbyintf(a[l] * reflect_scale_0), -128.0f, 127.0f); | |
| a[l] = (int8_t) (a_temp); | |
| } | |
| for (int l = 16; l < 32; ++l) { | |
| float a_temp = std::clamp(std::nearbyintf(a[l] * reflect_scale_1), -128.0f, 127.0f); | |
| a[l] = (int8_t) (a_temp); | |
| } | |
| dst_tmp[i].d = GGML_FP32_TO_FP16(reflect_scale); | |
| memcpy(dst_tmp[i].qs, a, 32 * sizeof(int8_t)); | |
| } | |
| for (; i < nrows_interleaved; i++) { | |
| memset(&dst_tmp[i], 0, sizeof(block_q8_0)); | |
| } | |
| *dst++ = make_block_q8_0x32(dst_tmp, interleave_block); | |
| } | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| // RVV optimized version of repack_q6_k_to_q8_0_32_bl | |
| // Vectorizes the Q6_K dequant -> requant pipeline using RVV intrinsics. | |
| // For each sub-block (bi), dequant 32 Q6_K values to int6 -> apply two sub-block scales -> | |
| // find max abs -> compute reflect_scale -> requant to int8 -> gather d with stride load. | |
| static int repack_q6_k_to_q8_0_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q6_K); | |
| GGML_ASSERT(interleave_block == 32); | |
| GGML_ASSERT(QK_K / QK4_1 == 8); | |
| constexpr int nrows_interleaved = 32; | |
| block_q8_0x32 * dst = (block_q8_0x32 *) t->data; | |
| const block_q6_K * src = (const block_q6_K *) data; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK_K; | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) { | |
| return -1; | |
| } | |
| const ptrdiff_t row_stride = (ptrdiff_t) nblocks * sizeof(block_q6_K); | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int bi = 0; bi < 8; bi++) { | |
| // --- 1) Gather 32 d values with stride load --- | |
| // We need to compute reflect_scale per row first, so gather d later. | |
| // Process each row: dequant Q6_K sub-block -> requant to Q8_0 | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| const block_q6_K * src_blk = &src[x + i * nblocks]; | |
| const uint8_t * q4 = src_blk->ql + 64 * (bi / 4); | |
| const uint8_t * qh = src_blk->qh + 32 * (bi / 4); | |
| const int8_t * scales = src_blk->scales; | |
| float d = GGML_FP16_TO_FP32(src_blk->d); | |
| int8_t bi_idx = bi % 4; | |
| // --- Dequant 32 Q6_K values to int6 (range [-32, 31]) using RVV --- | |
| // vl = 32 for e8m2 (VLEN=256) or loop for smaller VLEN | |
| const size_t vl16 = __riscv_vsetvl_e8m1(16); | |
| vint8m1_t va_lo, va_hi; // 16 elements each | |
| if (bi_idx == 0) { | |
| // a[l] = (q4[l] & 0xF) | (((qh[l] >> 0) & 3) << 4) - 32 | |
| vuint8m1_t vq4_lo = __riscv_vle8_v_u8m1(q4, vl16); | |
| vuint8m1_t vq4_hi = __riscv_vle8_v_u8m1(q4 + 16, vl16); | |
| vuint8m1_t vqh_lo = __riscv_vle8_v_u8m1(qh, vl16); | |
| vuint8m1_t vqh_hi = __riscv_vle8_v_u8m1(qh + 16, vl16); | |
| vuint8m1_t vlo4_lo = __riscv_vand_vx_u8m1(vq4_lo, 0x0F, vl16); | |
| vuint8m1_t vlo4_hi = __riscv_vand_vx_u8m1(vq4_hi, 0x0F, vl16); | |
| vuint8m1_t vh_lo = __riscv_vsll_vx_u8m1(__riscv_vand_vx_u8m1(vqh_lo, 0x03, vl16), 4, vl16); | |
| vuint8m1_t vh_hi = __riscv_vsll_vx_u8m1(__riscv_vand_vx_u8m1(vqh_hi, 0x03, vl16), 4, vl16); | |
| vuint8m1_t vcomb_lo = __riscv_vor_vv_u8m1(vlo4_lo, vh_lo, vl16); | |
| vuint8m1_t vcomb_hi = __riscv_vor_vv_u8m1(vlo4_hi, vh_hi, vl16); | |
| va_lo = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_lo), 32, vl16); | |
| va_hi = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_hi), 32, vl16); | |
| } else if (bi_idx == 1) { | |
| // a[l] = (q4[l+32] & 0xF) | (((qh[l] >> 2) & 3) << 4) - 32 | |
| vuint8m1_t vq4_lo = __riscv_vle8_v_u8m1(q4 + 32, vl16); | |
| vuint8m1_t vq4_hi = __riscv_vle8_v_u8m1(q4 + 48, vl16); | |
| vuint8m1_t vqh_lo = __riscv_vle8_v_u8m1(qh, vl16); | |
| vuint8m1_t vqh_hi = __riscv_vle8_v_u8m1(qh + 16, vl16); | |
| vuint8m1_t vlo4_lo = __riscv_vand_vx_u8m1(vq4_lo, 0x0F, vl16); | |
| vuint8m1_t vlo4_hi = __riscv_vand_vx_u8m1(vq4_hi, 0x0F, vl16); | |
| vuint8m1_t vh_lo = __riscv_vsll_vx_u8m1( | |
| __riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_lo, 2, vl16), 0x03, vl16), 4, vl16); | |
| vuint8m1_t vh_hi = __riscv_vsll_vx_u8m1( | |
| __riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_hi, 2, vl16), 0x03, vl16), 4, vl16); | |
| vuint8m1_t vcomb_lo = __riscv_vor_vv_u8m1(vlo4_lo, vh_lo, vl16); | |
| vuint8m1_t vcomb_hi = __riscv_vor_vv_u8m1(vlo4_hi, vh_hi, vl16); | |
| va_lo = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_lo), 32, vl16); | |
| va_hi = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_hi), 32, vl16); | |
| } else if (bi_idx == 2) { | |
| // a[l] = (q4[l] >> 4) | (((qh[l] >> 4) & 3) << 4) - 32 | |
| vuint8m1_t vq4_lo = __riscv_vle8_v_u8m1(q4, vl16); | |
| vuint8m1_t vq4_hi = __riscv_vle8_v_u8m1(q4 + 16, vl16); | |
| vuint8m1_t vqh_lo = __riscv_vle8_v_u8m1(qh, vl16); | |
| vuint8m1_t vqh_hi = __riscv_vle8_v_u8m1(qh + 16, vl16); | |
| vuint8m1_t vhi4_lo = __riscv_vsrl_vx_u8m1(vq4_lo, 4, vl16); | |
| vuint8m1_t vhi4_hi = __riscv_vsrl_vx_u8m1(vq4_hi, 4, vl16); | |
| vuint8m1_t vh_lo = __riscv_vsll_vx_u8m1( | |
| __riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_lo, 4, vl16), 0x03, vl16), 4, vl16); | |
| vuint8m1_t vh_hi = __riscv_vsll_vx_u8m1( | |
| __riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_hi, 4, vl16), 0x03, vl16), 4, vl16); | |
| vuint8m1_t vcomb_lo = __riscv_vor_vv_u8m1(vhi4_lo, vh_lo, vl16); | |
| vuint8m1_t vcomb_hi = __riscv_vor_vv_u8m1(vhi4_hi, vh_hi, vl16); | |
| va_lo = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_lo), 32, vl16); | |
| va_hi = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_hi), 32, vl16); | |
| } else { // bi_idx == 3 | |
| // a[l] = (q4[l+32] >> 4) | (((qh[l] >> 6) & 3) << 4) - 32 | |
| vuint8m1_t vq4_lo = __riscv_vle8_v_u8m1(q4 + 32, vl16); | |
| vuint8m1_t vq4_hi = __riscv_vle8_v_u8m1(q4 + 48, vl16); | |
| vuint8m1_t vqh_lo = __riscv_vle8_v_u8m1(qh, vl16); | |
| vuint8m1_t vqh_hi = __riscv_vle8_v_u8m1(qh + 16, vl16); | |
| vuint8m1_t vhi4_lo = __riscv_vsrl_vx_u8m1(vq4_lo, 4, vl16); | |
| vuint8m1_t vhi4_hi = __riscv_vsrl_vx_u8m1(vq4_hi, 4, vl16); | |
| vuint8m1_t vh_lo = __riscv_vsll_vx_u8m1( | |
| __riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_lo, 6, vl16), 0x03, vl16), 4, vl16); | |
| vuint8m1_t vh_hi = __riscv_vsll_vx_u8m1( | |
| __riscv_vand_vx_u8m1(__riscv_vsrl_vx_u8m1(vqh_hi, 6, vl16), 0x03, vl16), 4, vl16); | |
| vuint8m1_t vcomb_lo = __riscv_vor_vv_u8m1(vhi4_lo, vh_lo, vl16); | |
| vuint8m1_t vcomb_hi = __riscv_vor_vv_u8m1(vhi4_hi, vh_hi, vl16); | |
| va_lo = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_lo), 32, vl16); | |
| va_hi = __riscv_vsub_vx_i8m1(__riscv_vreinterpret_v_u8m1_i8m1(vcomb_hi), 32, vl16); | |
| } | |
| // --- Widen to i16 for scaled abs computation --- | |
| float scale_0 = scales[bi * 2 + 0] * d; | |
| float scale_1 = scales[bi * 2 + 1] * d; | |
| // Widen i8 -> i16 -> f32 for abs*scale computation | |
| vint16m2_t va_lo_w = __riscv_vsext_vf2_i16m2(va_lo, vl16); | |
| vint16m2_t va_hi_w = __riscv_vsext_vf2_i16m2(va_hi, vl16); | |
| // Compute |a[l] * scale_0| for lo half, |a[l] * scale_1| for hi half | |
| vfloat32m4_t vf_lo = __riscv_vfcvt_f_x_v_f32m4(__riscv_vsext_vf2_i32m4(va_lo_w, vl16), vl16); | |
| vfloat32m4_t vf_hi = __riscv_vfcvt_f_x_v_f32m4(__riscv_vsext_vf2_i32m4(va_hi_w, vl16), vl16); | |
| vfloat32m4_t vabs_lo = __riscv_vfabs_v_f32m4(__riscv_vfmul_vf_f32m4(vf_lo, scale_0, vl16), vl16); | |
| vfloat32m4_t vabs_hi = __riscv_vfabs_v_f32m4(__riscv_vfmul_vf_f32m4(vf_hi, scale_1, vl16), vl16); | |
| // Find max abs across both halves | |
| vfloat32m4_t vabs_max = __riscv_vfmax_vv_f32m4(vabs_lo, vabs_hi, vl16); | |
| // Reduce to scalar max | |
| vfloat32m1_t vzero = __riscv_vfmv_v_f_f32m1(0.0f, 1); | |
| vfloat32m1_t vmax_red = __riscv_vfredmax_vs_f32m4_f32m1(vabs_max, vzero, vl16); | |
| float a_max_abs = __riscv_vfmv_f_s_f32m1_f32(vmax_red); | |
| float reflect_scale = a_max_abs / 127.0f; | |
| float reflect_scale_0 = scale_0 / reflect_scale; | |
| float reflect_scale_1 = scale_1 / reflect_scale; | |
| // --- Requant: a[l] = clamp(nearbyint(a[l] * reflect_scale_x), -128, 127) --- | |
| vfloat32m4_t vscaled_lo = __riscv_vfmul_vf_f32m4(vf_lo, reflect_scale_0, vl16); | |
| vfloat32m4_t vscaled_hi = __riscv_vfmul_vf_f32m4(vf_hi, reflect_scale_1, vl16); | |
| // fcvt.x rounds to nearest (using current rounding mode) | |
| vint32m4_t vi_lo = __riscv_vfcvt_x_f_v_i32m4(vscaled_lo, vl16); | |
| vint32m4_t vi_hi = __riscv_vfcvt_x_f_v_i32m4(vscaled_hi, vl16); | |
| // Clamp to [-128, 127] | |
| vi_lo = __riscv_vmax_vx_i32m4(vi_lo, -128, vl16); | |
| vi_lo = __riscv_vmin_vx_i32m4(vi_lo, 127, vl16); | |
| vi_hi = __riscv_vmax_vx_i32m4(vi_hi, -128, vl16); | |
| vi_hi = __riscv_vmin_vx_i32m4(vi_hi, 127, vl16); | |
| // Narrow i32 -> i16 -> i8 | |
| vint16m2_t vi16_lo = __riscv_vncvt_x_x_w_i16m2(vi_lo, vl16); | |
| vint16m2_t vi16_hi = __riscv_vncvt_x_x_w_i16m2(vi_hi, vl16); | |
| vint8m1_t vi8_lo = __riscv_vncvt_x_x_w_i8m1(vi16_lo, vl16); | |
| vint8m1_t vi8_hi = __riscv_vncvt_x_x_w_i8m1(vi16_hi, vl16); | |
| // Store d and qs directly into dst block | |
| dst->d[i] = GGML_FP32_TO_FP16(reflect_scale); | |
| int8_t * dq = (int8_t *) dst->qs + i * QK8_0; | |
| __riscv_vse8_v_i8m1(dq, vi8_lo, vl16); | |
| __riscv_vse8_v_i8m1(dq + 16, vi8_hi, vl16); | |
| } | |
| dst++; | |
| } | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static int repack_q8_0_to_q8_0_32_bl_ref(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q8_0); | |
| GGML_ASSERT(interleave_block == 32); // unused | |
| constexpr int nrows_interleaved = 32; | |
| block_q8_0x32 * dst = (block_q8_0x32 *) t->data; | |
| const block_q8_0 * src = (const block_q8_0 *) data; | |
| block_q8_0 dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK8_0; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q8_0)); | |
| if (t->ne[0] % QK8_0 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| int64_t nrows_real = std::min((int64_t) nrow - b, (int64_t) nrows_interleaved); | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| int i = 0; | |
| for (; i < nrows_real; i++) { | |
| dst_tmp[i] = src[x + i * nblocks]; | |
| } | |
| for (; i < nrows_interleaved; i++) { | |
| memset(&dst_tmp[i], 0, sizeof(block_q8_0)); | |
| } | |
| *dst++ = make_block_q8_0x32(dst_tmp, interleave_block); | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| // RVV optimized version of repack_q8_0_to_q8_0_32_bl | |
| // Eliminates the intermediate dst_tmp buffer and vectorizes scale gather + qs copy. | |
| static int repack_q8_0_to_q8_0_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q8_0); | |
| GGML_ASSERT(interleave_block == 32); | |
| constexpr int nrows_interleaved = 32; | |
| block_q8_0x32 * dst = (block_q8_0x32 *) t->data; | |
| const block_q8_0 * src = (const block_q8_0 *) data; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK8_0; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q8_0)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK8_0 != 0) { | |
| return -1; | |
| } | |
| const ptrdiff_t row_stride = (ptrdiff_t) nblocks * sizeof(block_q8_0); | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| const block_q8_0 * col_src = src + x; | |
| // --- 1) Gather 32 scale values (ggml_half d) with stride load --- | |
| { | |
| const uint8_t * d_base = (const uint8_t *) &col_src->d; | |
| ggml_half * d_dst = dst->d; | |
| size_t remaining = 32; | |
| size_t offset = 0; | |
| while (remaining > 0) { | |
| size_t vl = __riscv_vsetvl_e16m1(remaining); | |
| vuint16m1_t vd = | |
| __riscv_vlse16_v_u16m1((const uint16_t *) (d_base + offset * row_stride), row_stride, vl); | |
| __riscv_vse16_v_u16m1((uint16_t *) (d_dst + offset), vd, vl); | |
| offset += vl; | |
| remaining -= vl; | |
| } | |
| } | |
| // --- 2) Copy qs for each of the 32 rows (32 bytes per row) --- | |
| { | |
| for (int i = 0; i < 32; i++) { | |
| const int8_t * sq = col_src[i * nblocks].qs; | |
| int8_t * dq = (int8_t *) dst->qs + i * QK8_0; | |
| size_t len = QK8_0; | |
| size_t idx = 0; | |
| while (len > 0) { | |
| size_t vl = __riscv_vsetvl_e8m2(len); | |
| vint8m2_t vs = __riscv_vle8_v_i8m2(sq + idx, vl); | |
| __riscv_vse8_v_i8m2(dq + idx, vs, vl); | |
| idx += vl; | |
| len -= vl; | |
| } | |
| } | |
| } | |
| dst++; | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| GGML_UNUSED(data_size); | |
| } | |
| static void convert_mxfp4_to_5bit(const block_mxfp4 & src, spacemit_kernels::nrow_block_mxfp4<1> & dst) { | |
| dst.e[0] = src.e; | |
| // Decode all 32 mxfp4 values to signed integers via kvalues_mxfp4 | |
| int8_t vals[32]; | |
| for (int j = 0; j < QK_MXFP4 / 2; j++) { | |
| vals[j] = kvalues_mxfp4[src.qs[j] & 0xF]; | |
| vals[j + QK_MXFP4 / 2] = kvalues_mxfp4[src.qs[j] >> 4]; | |
| } | |
| // vals [b0, b1, b2, b3, ..., b30, b31] | |
| // Pack abs into qs with reorder: [b0,b1]..[b14,b15]..[b30,b31] | |
| for (int j = 0; j < QK_MXFP4 / 2; j++) { | |
| uint8_t lo0 = static_cast<uint8_t>(std::abs(vals[j * 2])); | |
| uint8_t lo1 = static_cast<uint8_t>(std::abs(vals[j * 2 + 1])); | |
| dst.qs[j] = (lo0 & 0x0F) | ((lo1 & 0x0F) << 4); | |
| } | |
| // Pack sign bits into qh[4] (32 bits total, 1 bit per weight) | |
| // reorder: [0,1,2,...,15,16,17,...,31] after the qs reorder above | |
| uint32_t sign_bits = 0; | |
| for (int j = 0; j < 32; j++) { | |
| if (vals[j] < 0) { | |
| sign_bits |= (1u << j); | |
| } | |
| } | |
| memcpy(dst.qh, &sign_bits, 4); | |
| } | |
| static spacemit_kernels::nrow_block_mxfp4<32> make_block_mxfp4x32(spacemit_kernels::nrow_block_mxfp4<1> * in, | |
| unsigned int blck_size_interleave) { | |
| spacemit_kernels::nrow_block_mxfp4<32> out; | |
| GGML_ASSERT(QK_MXFP4 / blck_size_interleave == 1); | |
| GGML_UNUSED(blck_size_interleave); | |
| for (int i = 0; i < 32; i++) { | |
| out.e[i] = in[i].e[0]; | |
| } | |
| // qs: copy per-row 16 bytes | |
| for (int i = 0; i < 32; i++) { | |
| memcpy(out.qs + i * 16, in[i].qs, 16); | |
| } | |
| // qh: copy per-row 4 bytes | |
| for (int i = 0; i < 32; i++) { | |
| memcpy(out.qh + i * 4, in[i].qh, 4); | |
| } | |
| return out; | |
| } | |
| static int repack_mxfp4_to_mxfp4_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_MXFP4); | |
| GGML_ASSERT(interleave_block == 32); | |
| constexpr int nrows_interleaved = 32; | |
| spacemit_kernels::nrow_block_mxfp4<32> * dst = (spacemit_kernels::nrow_block_mxfp4<32> *) t->data; | |
| const block_mxfp4 * src = (const block_mxfp4 *) data; | |
| spacemit_kernels::nrow_block_mxfp4<1> dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK_MXFP4; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_mxfp4)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_MXFP4 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| convert_mxfp4_to_5bit(src[x + i * nblocks], dst_tmp[i]); | |
| } | |
| *dst++ = make_block_mxfp4x32(dst_tmp, interleave_block); | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| } | |
| static spacemit_kernels::nrow_block_q5_1<32> make_block_q5_1x32(spacemit_kernels::nrow_block_q5_1<1> * in, | |
| unsigned int blck_size_interleave) { | |
| spacemit_kernels::nrow_block_q5_1<32> out; | |
| GGML_ASSERT(QK5_1 / blck_size_interleave == 1); | |
| GGML_UNUSED(blck_size_interleave); | |
| for (int i = 0; i < 32; i++) { | |
| out.scales16[i] = in[i].scales16[0]; | |
| out.zp[i] = in[i].zp[0]; | |
| } | |
| // qs: low 4 bits, reorder from [b0,b16],[b1,b17]... to [b0,b1]...[b14,b15] and [b16,b17]...[b30,b31] | |
| for (int i = 0; i < 32; i++) { | |
| // low half [0..15] | |
| for (int j = 0; j < QK5_1 / 4; j++) { | |
| out.qs[i * QK5_1 / 2 + j] = (in[i].qs[j * 2] & 0x0F) | ((in[i].qs[j * 2 + 1] & 0x0F) << 4); | |
| } | |
| // high half [16..31] | |
| for (int j = 0; j < QK5_1 / 4; j++) { | |
| out.qs[i * QK5_1 / 2 + QK5_1 / 4 + j] = ((in[i].qs[j * 2] & 0xF0) >> 4) | (in[i].qs[j * 2 + 1] & 0xF0); | |
| } | |
| } | |
| // qh: 5th bit, copy directly | |
| for (int i = 0; i < 32; i++) { | |
| for (int j = 0; j < 4; j++) { | |
| out.qh[i * 4 + j] = in[i].qh[j]; | |
| } | |
| } | |
| return out; | |
| } | |
| static spacemit_kernels::nrow_block_q5_0<32> make_block_q5_0x32(spacemit_kernels::nrow_block_q5_0<1> * in, | |
| unsigned int blck_size_interleave) { | |
| spacemit_kernels::nrow_block_q5_0<32> out; | |
| GGML_ASSERT(QK5_0 / blck_size_interleave == 1); | |
| GGML_UNUSED(blck_size_interleave); | |
| for (int i = 0; i < 32; i++) { | |
| out.scales16[i] = in[i].scales16[0]; | |
| } | |
| // qs: low 4 bits, reorder from [b0,b16],[b1,b17]... to [b0,b1]...[b14,b15] and [b16,b17]...[b30,b31] | |
| for (int i = 0; i < 32; i++) { | |
| // low half [0..15] | |
| for (int j = 0; j < QK5_0 / 4; j++) { | |
| out.qs[i * QK5_0 / 2 + j] = (in[i].qs[j * 2] & 0x0F) | ((in[i].qs[j * 2 + 1] & 0x0F) << 4); | |
| } | |
| // high half [16..31] | |
| for (int j = 0; j < QK5_0 / 4; j++) { | |
| out.qs[i * QK5_0 / 2 + QK5_0 / 4 + j] = ((in[i].qs[j * 2] & 0xF0) >> 4) | (in[i].qs[j * 2 + 1] & 0xF0); | |
| } | |
| } | |
| // qh: 5th bit, copy directly | |
| for (int i = 0; i < 32; i++) { | |
| for (int j = 0; j < 4; j++) { | |
| out.qh[i * 4 + j] = in[i].qh[j]; | |
| } | |
| } | |
| return out; | |
| } | |
| static int repack_q5_0_to_q5_0_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q5_0); | |
| GGML_ASSERT(interleave_block == 32); // unused | |
| constexpr int nrows_interleaved = 32; | |
| spacemit_kernels::nrow_block_q5_0<32> * dst = (spacemit_kernels::nrow_block_q5_0<32> *) t->data; | |
| const block_q5_0 * src = (const block_q5_0 *) data; | |
| spacemit_kernels::nrow_block_q5_0<1> dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK5_0; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q5_0)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK5_0 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| const block_q5_0 & s = src[x + i * nblocks]; | |
| dst_tmp[i].scales16[0] = s.d; | |
| memcpy(dst_tmp[i].qs, s.qs, sizeof(dst_tmp[i].qs)); | |
| memcpy(dst_tmp[i].qh, s.qh, sizeof(dst_tmp[i].qh)); | |
| } | |
| *dst++ = make_block_q5_0x32(dst_tmp, interleave_block); | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| } | |
| static int repack_q5_1_to_q5_1_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q5_1); | |
| GGML_ASSERT(interleave_block == 32); // unused | |
| constexpr int nrows_interleaved = 32; | |
| spacemit_kernels::nrow_block_q5_1<32> * dst = (spacemit_kernels::nrow_block_q5_1<32> *) t->data; | |
| const block_q5_1 * src = (const block_q5_1 *) data; | |
| spacemit_kernels::nrow_block_q5_1<1> dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK5_1; | |
| GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q5_1)); | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK5_1 != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| const block_q5_1 & s = src[x + i * nblocks]; | |
| float d = GGML_FP16_TO_FP32(s.GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d); | |
| float m = GGML_FP16_TO_FP32(s.GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.m); | |
| if (d == 0.0f) { | |
| dst_tmp[i].scales16[0] = GGML_FP32_TO_FP16(std::fabs(m)); | |
| dst_tmp[i].zp[0] = m < 0.0f ? 1 : 0; | |
| memset(dst_tmp[i].qh, 0, sizeof(dst_tmp[i].qh)); | |
| memset(dst_tmp[i].qs, m > 0.0f ? 0x11 : 0x00, sizeof(dst_tmp[i].qs)); | |
| continue; | |
| } | |
| float mid = std::nearbyintf(-m / d); | |
| mid = std::min(31.0f, std::max(0.0f, mid)); | |
| dst_tmp[i].scales16[0] = GGML_FP32_TO_FP16(d); | |
| dst_tmp[i].zp[0] = static_cast<uint8_t>(mid); | |
| // qs: copy low 4 bits directly (same nibble packing) | |
| memcpy(dst_tmp[i].qs, s.qs, QK5_1 / 2); | |
| // qh: copy 5th bit directly | |
| memcpy(dst_tmp[i].qh, s.qh, 4); | |
| } | |
| *dst++ = make_block_q5_1x32(dst_tmp, interleave_block); | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| } | |
| static int repack_q5_k_to_q5_1_32_bl(ggml_tensor * t, | |
| int interleave_block, | |
| const void * GGML_RESTRICT data, | |
| size_t data_size) { | |
| GGML_ASSERT(t->type == GGML_TYPE_Q5_K); | |
| GGML_ASSERT(interleave_block == 32); | |
| GGML_ASSERT(QK_K / QK5_1 == 8); | |
| constexpr int nrows_interleaved = 32; | |
| spacemit_kernels::nrow_block_q5_1<32> * dst = (spacemit_kernels::nrow_block_q5_1<32> *) t->data; | |
| const block_q5_K * src = (const block_q5_K *) data; | |
| spacemit_kernels::nrow_block_q5_1<1> dst_tmp[32]; | |
| int nrow = ggml_nrows(t); | |
| int nblocks = t->ne[0] / QK_K; | |
| if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % QK_K != 0) { | |
| return -1; | |
| } | |
| for (int b = 0; b < nrow; b += nrows_interleaved) { | |
| for (int64_t x = 0; x < nblocks; x++) { | |
| for (int j = 0; j < 8; j++) { | |
| for (int i = 0; i < nrows_interleaved; i++) { | |
| uint8_t sc, m; | |
| const float d = GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d); | |
| const float min = | |
| GGML_FP16_TO_FP32(src[x + i * nblocks].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.dmin); | |
| get_scale_min_k4(j, src[x + i * nblocks].scales, &sc, &m); | |
| float d1 = d * sc; | |
| float m1 = min * m; | |
| float mid = std::nearbyintf(m1 / d1); | |
| mid = std::min(31.0f, std::max(0.0f, mid)); | |
| dst_tmp[i].scales16[0] = GGML_FP32_TO_FP16(d1); | |
| dst_tmp[i].zp[0] = static_cast<uint8_t>(mid); | |
| // src -> [b0, b32] [b1, b33] ... [b31, b63] | |
| // dst -> [b0, b16] [b1, b17] ... [b15, b31] [b32, b48] [b33, b49] ... [b47, b63] | |
| const uint8_t * q = src[x + i * nblocks].qs + (j / 2) * QK5_1; | |
| if (j % 2 == 0) { | |
| for (int ii = 0; ii < 16; ii++) { | |
| dst_tmp[i].qs[ii] = (q[ii] & 0x0F) | ((q[ii + 16] & 0x0F) << 4); | |
| } | |
| } else { | |
| for (int ii = 0; ii < 16; ii++) { | |
| dst_tmp[i].qs[ii] = ((q[ii] & 0xF0) >> 4) | (q[ii + 16] & 0xF0); | |
| } | |
| } | |
| // Extract the 5th bit (qh) for this sub-block | |
| // block_q5_K.qh[32]: for sub-block j, the 5th bit is at bit position j in qh[l] | |
| // qs was reordered: dst_qs maps to src weights [0,16,1,17,...,15,31] | |
| // So qh must follow the same reorder to stay aligned with qs | |
| // dst qh[4] = 32 bits for 32 weights in the reordered layout: | |
| // byte 0: weights 0..7 (from src_qh[0..7]) | |
| // byte 1: weights 8..15 (from src_qh[8..15]) | |
| // byte 2: weights 16..23 (from src_qh[16..23]) | |
| // byte 3: weights 24..31 (from src_qh[24..31]) | |
| const uint8_t * src_qh = src[x + i * nblocks].qh; | |
| for (int bi = 0; bi < 4; bi++) { | |
| uint8_t qh_byte = 0; | |
| for (int k = 0; k < 8; k++) { | |
| int src_idx = bi * 8 + k; | |
| qh_byte |= ((src_qh[src_idx] >> j) & 1) << k; | |
| } | |
| dst_tmp[i].qh[bi] = qh_byte; | |
| } | |
| } | |
| *dst++ = make_block_q5_1x32(dst_tmp, interleave_block); | |
| } | |
| } | |
| src += nrows_interleaved * nblocks; | |
| } | |
| return 0; | |
| } | |
| namespace ggml::cpu::riscv64_spacemit { | |
| template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS> int repack(ggml_tensor *, const void *, size_t); | |
| template <> int repack<block_q4_0, 32, 16>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q4_0_to_q4_0_16_bl(t, 16, data, data_size); | |
| } | |
| template <> int repack<block_q4_1, 32, 16>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q4_1_to_q4_1_16_bl(t, 16, data, data_size); | |
| } | |
| template <> int repack<block_q4_K, 32, 16>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q4_k_to_q4_1_16_bl(t, 16, data, data_size); | |
| } | |
| template <> int repack<block_q2_K, 256, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q2_k_to_q2_k_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q3_K, 256, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q3_k_to_q3_k_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q4_0, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q4_0_to_q4_0_32_bl_ref(t, 32, data, data_size); | |
| return repack_q4_0_to_q4_0_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q4_0, 256, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q4_0_to_q4_0_256_32_bl_ref(t, 32, data, data_size); | |
| //return repack_q4_0_to_q4_0_256_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q4_1, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q4_1_to_q4_1_32_bl_ref(t, 32, data, data_size); | |
| return repack_q4_1_to_q4_1_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q4_1, 256, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q4_0_to_q4_1_256_32_bl_ref(t, 32, data, data_size); | |
| return repack_q4_1_to_q4_1_256_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q4_K, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q4_k_to_q4_1_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q6_K, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q6_k_to_q8_0_32_bl_ref(t, 32, data, data_size); | |
| return repack_q6_k_to_q8_0_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q8_0, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q8_0_to_q8_0_32_bl_ref(t, 32, data, data_size); | |
| return repack_q8_0_to_q8_0_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_mxfp4, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_mxfp4_to_mxfp4_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q5_0, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q5_0_to_q5_0_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q5_1, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q5_1_to_q5_1_32_bl(t, 32, data, data_size); | |
| } | |
| template <> int repack<block_q5_K, 32, 32>(ggml_tensor * t, const void * data, size_t data_size) { | |
| return repack_q5_k_to_q5_1_32_bl(t, 32, data, data_size); | |
| } | |
| } // namespace ggml::cpu::riscv64_spacemit | |