mirror of
https://github.com/ggerganov/whisper.cpp.git
synced 2024-11-07 08:34:37 +01:00
ggml : sync with ggml repo (warning fixes + asserts)
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6108d3cc58
commit
05c3ea3bc8
24
ggml.c
24
ggml.c
@ -8245,8 +8245,6 @@ static void ggml_compute_forward_mul_mat_f16_f32(
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ggml_fp16_t * d_X = ggml_cuda_pool_malloc(sizeof(float) * x_ne, &x_size);
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ggml_fp16_t * d_Y = ggml_cuda_pool_malloc(sizeof(float) * y_ne, &y_size);
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float * d_D = ggml_cuda_pool_malloc(sizeof(float) * d_ne, &d_size);
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#else
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float * const wdata = params->wdata;
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#endif
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for (int64_t i03 = 0; i03 < ne03; i03++) {
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for (int64_t i02 = 0; i02 < ne02; i02++) {
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@ -8263,8 +8261,11 @@ static void ggml_compute_forward_mul_mat_f16_f32(
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wdata[id++] = GGML_FP32_TO_FP16(*(float *) ((char *) src1->data + i03*nb13 + i02*nb12 + i01*nb11 + i00*nb10));
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}
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}
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assert(id*sizeof(ggml_fp16_t) <= params->wsize);
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}
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#else
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float * const wdata = params->wdata;
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{
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size_t id = 0;
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for (int64_t i01 = 0; i01 < ne01; ++i01) {
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@ -8272,6 +8273,8 @@ static void ggml_compute_forward_mul_mat_f16_f32(
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wdata[id++] = GGML_FP16_TO_FP32(*(ggml_fp16_t *) ((char *) src0->data + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00));
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}
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}
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assert(id*sizeof(float) <= params->wsize);
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}
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#endif
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@ -8537,7 +8540,10 @@ static void ggml_compute_forward_mul_mat_q_f32(
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dequantize_row_q((char *) src0->data + i03*nb03 + i02*nb02 + i01*nb01, wdata + id, ne00);
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id += ne00;
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}
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assert(id*sizeof(float) <= params->wsize);
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}
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const float * x = wdata;
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#endif
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@ -9118,7 +9124,7 @@ static void ggml_compute_forward_alibi_f32(
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//const int nb3 = src0->nb[3];
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assert(nb0 == sizeof(float));
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assert(ne1+n_past == ne0);
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assert(ne1 + n_past == ne0); (void) n_past;
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// add alibi to src0 (KQ_scaled)
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const int n_heads_log2_floor = 1 << (int) floor(log2(n_head));
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@ -9179,7 +9185,7 @@ static void ggml_compute_forward_alibi_f16(
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//const int nb3 = src0->nb[3];
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assert(nb0 == sizeof(ggml_fp16_t));
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assert(ne1+n_past == ne0);
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assert(ne1 + n_past == ne0); (void) n_past;
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// add alibi to src0 (KQ_scaled)
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const int n_heads_log2_floor = 1 << (int) floor(log2(n_head));
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@ -11571,12 +11577,12 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
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if (ggml_compute_forward_mul_mat_use_blas(node->src0, node->src1, node)) {
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node->n_tasks = 1; // TODO: this actually is doing nothing
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// the threads are still spinning
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#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
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#if defined(GGML_USE_CUBLAS)
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// with cuBLAS, we need memory for the full 3D / 4D data of src1
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cur = GGML_TYPE_SIZE[GGML_TYPE_F16]*ggml_nelements(node->src1);
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#else
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// here we need memory just for single 2D matrix from src0
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cur = GGML_TYPE_SIZE[GGML_TYPE_F32]*(node->src0->ne[0]*node->src0->ne[1]);
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#else
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// with GPU, we need memory for the full 3D / 4D data
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cur = GGML_TYPE_SIZE[GGML_TYPE_F32]*MAX(ggml_nelements(node->src1), ggml_nelements(node->src0));
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#endif
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} else {
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cur = GGML_TYPE_SIZE[GGML_TYPE_F16]*ggml_nelements(node->src1);
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@ -11586,7 +11592,7 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
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#endif
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} else if (node->src0->type == GGML_TYPE_F32 && node->src1->type == GGML_TYPE_F32) {
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cur = 0;
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#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
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#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
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if (ggml_compute_forward_mul_mat_use_blas(node->src0, node->src1, node)) {
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node->n_tasks = 1;
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}
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4
ggml.h
4
ggml.h
@ -701,8 +701,8 @@ extern "C" {
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struct ggml_tensor * c1);
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// Mapping operations
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GGML_API typedef void (*ggml_unary_op_f32_t)(const int, float *, const float *);
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GGML_API typedef void (*ggml_binary_op_f32_t)(const int, float *, const float *, const float *);
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typedef void (*ggml_unary_op_f32_t)(const int, float *, const float *);
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typedef void (*ggml_binary_op_f32_t)(const int, float *, const float *, const float *);
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GGML_API struct ggml_tensor * ggml_map_unary_f32(
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struct ggml_context * ctx,
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