Get_Rows & Dequantize implementation adapted to work for repacked weights of type q4_0

ggml/src/ggml-cpu/repack.cpp

@@ -1170,6 +1170,9 @@ template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS, ggml_type PAR
                 size = GGML_PAD(size, sizeof(int64_t));  // + padding for next bloc.
                 size += sizeof(int64_t) * (1+op->src[0]->ne[2]) * op->src[1]->ne[2];
                 return true;
+            case GGML_OP_GET_ROWS:
+                size = 0;  // GET_ROWS (standard and repacked) doesn't need a work buffer
+                return true;
             default:
                 // GGML_ABORT("fatal error");
                 break;
@@ -1185,6 +1188,9 @@ template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS, ggml_type PAR
             case GGML_OP_MUL_MAT_ID:
                 forward_mul_mat_id(params, op);
                 return true;
+            case GGML_OP_GET_ROWS:
+                forward_get_rows(params, op);
+                return true;
             default:
                 // GGML_ABORT("fatal error");
                 break;
@@ -1390,6 +1396,132 @@ template <typename BLOC_TYPE, int64_t INTER_SIZE, int64_t NB_COLS, ggml_type PAR
 #undef MMID_MATRIX_ROW
     }
 
+    void forward_get_rows(const ggml_compute_params * params,
+                          ggml_tensor * dst) {
+        const ggml_tensor * src0 = dst->src[0];
+
+        switch (src0->type) {
+            case GGML_TYPE_Q4_0: {
+                ggml_compute_forward_get_rows_q4_0x8(params, dst);
+            } break;
+            default:
+                GGML_ABORT("fatal error");
+                break;
+        }
+    }
+
+    static void ggml_compute_forward_get_rows_q4_0x8(
+        const ggml_compute_params * params,
+        ggml_tensor * dst) {
+        const ggml_tensor * src0 = dst->src[0];
+        const ggml_tensor * src1 = dst->src[1];
+
+        GGML_TENSOR_BINARY_OP_LOCALS
+
+        const int64_t nc = ne00;
+        const int64_t nr = ggml_nelements(src1);
+
+        assert(ne0 == nc);
+        assert(ne02 == ne11);
+        assert(nb00 == ggml_type_size(src0->type));
+        assert(ggml_nrows(dst) == nr);
+
+        const int ith = params->ith;
+        const int nth = params->nth;
+
+        // rows per thread
+        const int dr = (nr + nth - 1) / nth;
+
+        // row range for this thread
+        const int ir0 = dr * ith;
+        const int ir1 = MIN(ir0 + dr, nr);
+
+        constexpr int nrows_interleaved = 8;
+        const size_t sizeof_one_repacked_block = sizeof(block_q4_0x8);
+
+        const int num_repacked_blocks_per_row_width = nc / QK4_0;
+
+        const size_t stride_between_actual_row_groups = num_repacked_blocks_per_row_width * sizeof_one_repacked_block;
+
+        for (int64_t i = ir0; i < ir1; ++i) {
+            const int64_t i12 = i / (ne11 * ne10);
+            const int64_t i11 = (i - i12 * ne11 * ne10) / ne10;
+            const int64_t i10 = (i - i12 * ne11 * ne10 - i11 * ne10);
+            const int64_t i01 = *(int32_t *)((char *)src1->data + i10 * nb10 + i11 * nb11 + i12 * nb12);  // original logical row
+
+            GGML_ASSERT(i01 >= 0 && i01 < ne01);
+
+            int row_group_idx = i01 / nrows_interleaved;
+            const int row_idx_in_group = i01 % nrows_interleaved;
+
+            const char * base_ptr_for_higher_dims_in_src0 = (const char *)src0->data + i11 * nb02 + i12 * nb03;
+
+            // Pointer to the first block_q4_0x8 of the identified row_group_idx
+            const block_q4_0x8 * p_first_repacked_block_of_group_x8 = (const block_q4_0x8 *)(base_ptr_for_higher_dims_in_src0 + row_group_idx * stride_between_actual_row_groups);
+
+            dequantize_row_q4_0x8(
+                p_first_repacked_block_of_group_x8,
+                (float *)((char *)dst->data + i10 * nb1 + i11 * nb2 + i12 * nb3), nc, row_idx_in_group);
+        }
+    }
+
+    /**
+     * Dequantizes a single logical row from data repacked with quant interleaving.
+     *
+     * @param p_repacked_group_column_blocks Pointer to the start of 'block_q4_0x8' for the row group.
+     * @param y                              Output buffer for the dequantized float values.
+     * @param k                              Total number of elements (columns) in the logical row.
+     * @param row_idx_in_group               Index (0-7) of the logical row to dequantize.
+     */
+    static void dequantize_row_q4_0x8(
+        const block_q4_0x8 * GGML_RESTRICT p_repacked_group_column_blocks,
+        float * GGML_RESTRICT y,
+        int64_t k,
+        int row_idx_in_group) {
+        const int GGML_Q4_0_X8_INTERLEAVE_SIZE = 8;
+        assert(k % QK4_0 == 0);
+        assert(row_idx_in_group >= 0 && row_idx_in_group < GGML_Q4_0_X8_INTERLEAVE_SIZE);
+
+        const int nb = k / QK4_0;
+        const int bytes_for_half_elements = (QK4_0 / 2) / 2;
+
+        const int offset_to_second_half_data = bytes_for_half_elements * GGML_Q4_0_X8_INTERLEAVE_SIZE;
+        const uint64_t xor_mask = 0x8888888888888888ULL;
+        const int qk4_0_half_elements = QK4_0 / 2;
+
+        for (int i = 0; i < nb; ++i) {
+            const block_q4_0x8 * current_column_repacked_block = &p_repacked_group_column_blocks[i];
+            const float d_val = GGML_FP16_TO_FP32(current_column_repacked_block->d[row_idx_in_group]);
+            float * y_curr = y + i * QK4_0;
+
+            const int8_t * qs_first_half_repacked_ptr = &(current_column_repacked_block->qs[row_idx_in_group * bytes_for_half_elements]);
+
+            uint64_t first_half_chunk_u64;
+            memcpy(&first_half_chunk_u64, qs_first_half_repacked_ptr, sizeof(uint64_t));
+            first_half_chunk_u64 ^= xor_mask;  // Reverse the XOR
+            const uint8_t * original_qs_first_half_bytes = (const uint8_t *)&first_half_chunk_u64;
+
+            const int8_t * qs_second_half_repacked_ptr = &(current_column_repacked_block->qs[offset_to_second_half_data + (row_idx_in_group * bytes_for_half_elements)]);
+
+            uint64_t second_half_chunk_u64;
+            memcpy(&second_half_chunk_u64, qs_second_half_repacked_ptr, sizeof(uint64_t));
+            second_half_chunk_u64 ^= xor_mask;  // Reverse the XOR
+            const uint8_t * original_qs_second_half_bytes = (const uint8_t *)&second_half_chunk_u64;
+
+            // dequantizing all QK4_0's for this block.
+            for (int j = 0; j < bytes_for_half_elements; ++j) {
+                const uint8_t quant_byte_first = original_qs_first_half_bytes[j];
+                y_curr[j] = ((quant_byte_first & 0x0F) - 8) * d_val;
+                y_curr[j + qk4_0_half_elements] = ((quant_byte_first >> 4) - 8) * d_val;
+
+                const uint8_t quant_byte_second = original_qs_second_half_bytes[j];
+                const int out_idx_base_second_half = j + bytes_for_half_elements;  // Offset for the second set of low nibbles
+                y_curr[out_idx_base_second_half] = ((quant_byte_second & 0x0F) - 8) * d_val;
+                y_curr[out_idx_base_second_half + qk4_0_half_elements] = ((quant_byte_second >> 4) - 8) * d_val;
+            }
+        }
+    }
+
     int repack(struct ggml_tensor * t, const void * data, size_t data_size) override {
         GGML_LOG_DEBUG("%s: repack tensor %s with %s_%dx%d\n", __func__, t->name, ggml_type_name(t->type),
                        (int) NB_COLS, (int) INTER_SIZE);
@@ -1522,12 +1654,23 @@ class extra_buffer_type : ggml::cpu::extra_buffer_type {
             //if (op->src[1]->type == GGML_TYPE_Q8_0) {
             //    return true;
             //}
+        } else if (op->op == GGML_OP_GET_ROWS
+            && op->src[0]->buffer
+            && (ggml_n_dims(op->src[0]) == 2)
+            && op->src[0]->buffer->buft == ggml_backend_cpu_repack_buffer_type()
+            && ggml_repack_get_optimal_repack_type(op->src[0])) {
+            if (op->src[1]->buffer && !ggml_backend_buft_is_host(op->src[1]->buffer->buft)) {
+                return false;
+            }
+            if (op->src[0]->type == GGML_TYPE_Q4_0) {
+                return true;
+            }
         }
         return false;
     }
 
     ggml::cpu::tensor_traits * get_tensor_traits(const struct ggml_tensor * op) override {
-        if (op->op == GGML_OP_MUL_MAT || op->op == GGML_OP_MUL_MAT_ID) {
+        if (op->op == GGML_OP_MUL_MAT || op->op == GGML_OP_MUL_MAT_ID || op->op == GGML_OP_GET_ROWS) {
             if (op->src[0]->buffer && op->src[0]->buffer->buft == ggml_backend_cpu_repack_buffer_type()) {
                 return (ggml::cpu::tensor_traits *) op->src[0]->extra;
             }

src/whisper.cpp

@@ -1437,24 +1437,25 @@ static bool weight_buft_supported(const whisper_hparams & hparams, ggml_tensor *
         // GPU and default CPU backend support all operators
         op_supported = true;
     } else {
+        ggml_init_params params = {
+            /*.mem_size   =*/ 2 * ggml_tensor_overhead(),
+            /*.mem_buffer =*/ nullptr,
+            /*.no_alloc   =*/ true,
+        };
+
+        ggml_context_ptr ctx_ptr { ggml_init(params) };
+        if (!ctx_ptr) {
+            throw std::runtime_error("failed to create ggml context");
+        }
+        ggml_context * ctx = ctx_ptr.get();
+
+        ggml_tensor * op_tensor = nullptr;
+        
+        int64_t n_ctx = hparams.n_audio_ctx;
+
         switch (op) {
-            // The current extra_buffer_type implementations only support GGML_OP_MUL_MAT
+            // The current extra_buffer_type implementations only support GGML_OP_MUL_MAT & GGML_OP_GET_ROWS (q4_0)
             case GGML_OP_MUL_MAT: {
-                ggml_init_params params = {
-                    /*.mem_size   =*/ 2 * ggml_tensor_overhead(),
-                    /*.mem_buffer =*/ nullptr,
-                    /*.no_alloc   =*/ true,
-                };
-
-                ggml_context_ptr ctx_ptr { ggml_init(params) };
-                if (!ctx_ptr) {
-                    throw std::runtime_error("failed to create ggml context");
-                }
-                ggml_context * ctx = ctx_ptr.get();
-
-                ggml_tensor * op_tensor = nullptr;
-
-                int64_t n_ctx = hparams.n_audio_ctx;
                 ggml_tensor * b = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, w->ne[0], n_ctx, w->ne[2], w->ne[3]);
                 op_tensor = ggml_mul_mat(ctx, w, b);
 
@@ -1466,6 +1467,18 @@ static bool weight_buft_supported(const whisper_hparams & hparams, ggml_tensor *
                 w->buffer = nullptr;
                 break;
             }
+            case GGML_OP_GET_ROWS: {
+                ggml_tensor * b = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, n_ctx);
+                op_tensor = ggml_get_rows(ctx, w, b);
+
+                // create a temporary dummy buffer for the weight so that supports_op can check the buffer type
+                GGML_ASSERT(w->buffer == nullptr);
+                w->buffer = ggml_backend_buft_alloc_buffer(buft, 0);
+                op_supported = ggml_backend_dev_supports_op(dev, op_tensor);
+                ggml_backend_buffer_free(w->buffer);
+                w->buffer = nullptr;
+                break;
+            }
             default: {
                 op_supported = false;
                 break;