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-rw-r--r--common/common.cpp10
-rw-r--r--examples/llava/clip.cpp47
-rw-r--r--examples/perplexity/perplexity.cpp4
-rw-r--r--ggml.c9
-rw-r--r--ggml.h1
-rw-r--r--llama.cpp24
6 files changed, 42 insertions, 53 deletions
diff --git a/common/common.cpp b/common/common.cpp
index 0a709617..6b07f119 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -216,12 +216,10 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
}
// store the external file name in params
params.prompt_file = argv[i];
- file.seekg(0, std::ios::end);
- size_t size = file.tellg();
- file.seekg(0, std::ios::beg);
- params.prompt.resize(size);
- file.read((char *)params.prompt.data(), size);
- fprintf(stderr, "Read %zu bytes from binary file %s\n", size, argv[i]);
+ std::ostringstream ss;
+ ss << file.rdbuf();
+ params.prompt = ss.str();
+ fprintf(stderr, "Read %zu bytes from binary file %s\n", params.prompt.size(), argv[i]);
} else if (arg == "-f" || arg == "--file") {
if (++i >= argc) {
invalid_param = true;
diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
index 6161fd85..4a0338a3 100644
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -2,18 +2,6 @@
// so there might be still unnecessary artifacts hanging around
// I'll gradually clean and extend it
-#include <cassert>
-#include <cmath>
-#include <cstdlib>
-#include <cstring>
-#include <fstream>
-#include <iostream>
-#include <map>
-#include <regex>
-#include <stdexcept>
-#include <vector>
-#include <sstream>
-
#include "clip.h"
#include "ggml.h"
#include "ggml-alloc.h"
@@ -30,6 +18,19 @@
#define STB_IMAGE_IMPLEMENTATION
#include "stb_image.h"
+#include <cassert>
+#include <cmath>
+#include <cstdlib>
+#include <cstring>
+#include <fstream>
+#include <iostream>
+#include <map>
+#include <regex>
+#include <stdexcept>
+#include <vector>
+#include <sstream>
+#include <cinttypes>
+
static std::string format(const char * fmt, ...) {
va_list ap;
va_list ap2;
@@ -217,9 +218,9 @@ static std::string gguf_kv_to_str(const struct gguf_context * ctx_gguf, int i) {
static void print_tensor_info(const ggml_tensor* tensor, const char* prefix = "") {
size_t tensor_size = ggml_nbytes(tensor);
- printf("%s: n_dims = %d, name = %s, tensor_size=%zu, shape:[%d, %d, %d, %d], type: %d\n",
+ printf("%s: n_dims = %d, name = %s, tensor_size=%zu, shape:[%" PRId64 ", %" PRId64 ", %" PRId64 ", %" PRId64 "], type = %s\n",
prefix, ggml_n_dims(tensor), tensor->name, tensor_size,
- tensor->ne[0], tensor->ne[1], tensor->ne[2], tensor->ne[3], tensor->type);
+ tensor->ne[0], tensor->ne[1], tensor->ne[2], tensor->ne[3], ggml_type_name(tensor->type));
}
static projector_type clip_projector_type_from_string(const std::string & name) {
@@ -592,7 +593,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32
mlp_3 = ggml_cont(ctx0, ggml_permute(ctx0, mlp_3, 1, 0, 2, 3));
mlp_3 = ggml_reshape_4d(ctx0, mlp_3, n_patch, n_patch, mlp_3->ne[1], mlp_3->ne[2]);
// stride = 1, padding = 1, bias is nullptr
- block_1 = ggml_conv_depthwise_2d(ctx0, model.mm_model_block_1_block_0_0_w, mlp_3, nullptr, 1, 1, 1, 1, 1, 1);
+ block_1 = ggml_conv_depthwise_2d(ctx0, model.mm_model_block_1_block_0_0_w, mlp_3, 1, 1, 1, 1, 1, 1);
// layer norm
// // block_1 shape = [1, 2048, 24, 24], ne = [24, 24, 2048, 1]
@@ -640,7 +641,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32
// block_2
{
// stride = 2
- block_1 = ggml_conv_depthwise_2d(ctx0, model.mm_model_block_2_block_0_0_w, block_1, nullptr, 2, 2, 1, 1, 1, 1);
+ block_1 = ggml_conv_depthwise_2d(ctx0, model.mm_model_block_2_block_0_0_w, block_1, 2, 2, 1, 1, 1, 1);
// block_1 shape = [1, 2048, 12, 12], ne = [12, 12, 2048, 1]
// layer norm
@@ -741,18 +742,10 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
{
std::map<enum ggml_type, uint32_t> n_type;
- uint32_t n_type_max = 0;
- enum ggml_type type_max = GGML_TYPE_F32;
-
for (int i = 0; i < n_tensors; i++) {
enum ggml_type type = gguf_get_tensor_type(ctx, i);
n_type[type]++;
-
- if (n_type_max < n_type[type]) {
- n_type_max = n_type[type];
- type_max = type;
- }
}
printf("%s: Dumping metadata keys/values. Note: KV overrides do not apply in this output.\n", __func__);
@@ -795,14 +788,12 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
size_t tensor_size = ggml_nbytes(cur);
buffer_size += tensor_size;
if (verbosity >= 3) {
- printf("%s: tensor[%d]: n_dims = %d, name = %s, tensor_size=%zu, offset=%zu, shape:[%d, %d, %d, %d], type: %d\n", __func__, i,
- ggml_n_dims(cur), cur->name, tensor_size, offset, cur->ne[0], cur->ne[1], cur->ne[2], cur->ne[3], type);
+ printf("%s: tensor[%d]: n_dims = %d, name = %s, tensor_size=%zu, offset=%zu, shape:[%" PRIu64 ", %" PRIu64 ", %" PRIu64 ", %" PRIu64 "], type = %s\n",
+ __func__, i, ggml_n_dims(cur), cur->name, tensor_size, offset, cur->ne[0], cur->ne[1], cur->ne[2], cur->ne[3], ggml_type_name(type));
}
}
}
-
-
buffer_size += n_tensors * 128 /* CLIP PADDING */;
clip_ctx * new_clip = new clip_ctx;
diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp
index 1b7f85f4..de6d3eb4 100644
--- a/examples/perplexity/perplexity.cpp
+++ b/examples/perplexity/perplexity.cpp
@@ -1202,11 +1202,11 @@ static void winogrande_score(llama_context * ctx, const gpt_params & params) {
printf("Final Winogrande score(%d tasks): %.4lf +/- %.4lf\n", n_done, 100*p, sigma);
}
-static bool deserialize_string(std::istream& in, std::string& str) {
+static bool deserialize_string(std::istream & in, std::string & str) {
uint32_t size;
if (!in.read((char *)&size, sizeof(size)).fail()) {
str.resize(size);
- if (!in.read((char *)str.data(), size).fail()) return true;
+ if (!in.read((char *)&str[0], size).fail()) return true;
}
return false;
}
diff --git a/ggml.c b/ggml.c
index f85045c9..ca98fde8 100644
--- a/ggml.c
+++ b/ggml.c
@@ -5368,14 +5368,12 @@ struct ggml_tensor * ggml_conv_depthwise_2d(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b,
- struct ggml_tensor * c,
int s0,
int s1,
int p0,
int p1,
int d0,
int d1) {
-
struct ggml_tensor * new_a = ggml_reshape_4d(ctx, a, a->ne[0], a->ne[1], 1, a->ne[2] * a->ne[3]);
struct ggml_tensor * im2col = ggml_im2col(ctx, new_a,
ggml_reshape_4d(ctx, b, b->ne[0], b->ne[1], 1, b->ne[2] * b->ne[3]),
@@ -9991,7 +9989,7 @@ static void ggml_compute_forward_mul_mat(
return;
}
- const int64_t tgemm0 = ggml_perf_time_us();
+ //const int64_t tgemm0 = ggml_perf_time_us();
for (int64_t i13 = 0; i13 < ne13; i13++) {
for (int64_t i12 = 0; i12 < ne12; i12++) {
const int64_t i03 = i13/r3;
@@ -16934,7 +16932,10 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa
if (ggml_compute_forward_mul_mat_use_blas(node)) {
if (node->src[0]->type != GGML_TYPE_F32) {
// here we need memory for fully dequantized matrix from src0
- cur = ggml_type_size(GGML_TYPE_F32)*ggml_nelements(node->src[0]);
+ // take into account that src0 can be broadcasted into src1[2,3]
+ cur = ggml_type_size(GGML_TYPE_F32)
+ * node->src[0]->ne[0]*node->src[0]->ne[1]
+ * node->src[1]->ne[2]*node->src[1]->ne[3];
}
} else
#endif
diff --git a/ggml.h b/ggml.h
index dca7bd9c..1c497627 100644
--- a/ggml.h
+++ b/ggml.h
@@ -1499,7 +1499,6 @@ extern "C" {
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b,
- struct ggml_tensor * c,
int s0,
int s1,
int p0,
diff --git a/llama.cpp b/llama.cpp
index f6f1ec0f..582e8226 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -2300,18 +2300,18 @@ struct llama_model_loader {
}
switch (type_max) {
- case GGML_TYPE_F32: ftype = LLAMA_FTYPE_ALL_F32; break;
- case GGML_TYPE_F16: ftype = LLAMA_FTYPE_MOSTLY_F16; break;
- case GGML_TYPE_Q4_0: ftype = LLAMA_FTYPE_MOSTLY_Q4_0; break;
- case GGML_TYPE_Q4_1: ftype = LLAMA_FTYPE_MOSTLY_Q4_1; break;
- case GGML_TYPE_Q5_0: ftype = LLAMA_FTYPE_MOSTLY_Q5_0; break;
- case GGML_TYPE_Q5_1: ftype = LLAMA_FTYPE_MOSTLY_Q5_1; break;
- case GGML_TYPE_Q8_0: ftype = LLAMA_FTYPE_MOSTLY_Q8_0; break;
- case GGML_TYPE_Q2_K: ftype = LLAMA_FTYPE_MOSTLY_Q2_K; break;
- case GGML_TYPE_Q3_K: ftype = LLAMA_FTYPE_MOSTLY_Q3_K_M; break;
- case GGML_TYPE_Q4_K: ftype = LLAMA_FTYPE_MOSTLY_Q4_K_M; break;
- case GGML_TYPE_Q5_K: ftype = LLAMA_FTYPE_MOSTLY_Q5_K_M; break;
- case GGML_TYPE_Q6_K: ftype = LLAMA_FTYPE_MOSTLY_Q6_K; break;
+ case GGML_TYPE_F32: ftype = LLAMA_FTYPE_ALL_F32; break;
+ case GGML_TYPE_F16: ftype = LLAMA_FTYPE_MOSTLY_F16; break;
+ case GGML_TYPE_Q4_0: ftype = LLAMA_FTYPE_MOSTLY_Q4_0; break;
+ case GGML_TYPE_Q4_1: ftype = LLAMA_FTYPE_MOSTLY_Q4_1; break;
+ case GGML_TYPE_Q5_0: ftype = LLAMA_FTYPE_MOSTLY_Q5_0; break;
+ case GGML_TYPE_Q5_1: ftype = LLAMA_FTYPE_MOSTLY_Q5_1; break;
+ case GGML_TYPE_Q8_0: ftype = LLAMA_FTYPE_MOSTLY_Q8_0; break;
+ case GGML_TYPE_Q2_K: ftype = LLAMA_FTYPE_MOSTLY_Q2_K; break;
+ case GGML_TYPE_Q3_K: ftype = LLAMA_FTYPE_MOSTLY_Q3_K_M; break;
+ case GGML_TYPE_Q4_K: ftype = LLAMA_FTYPE_MOSTLY_Q4_K_M; break;
+ case GGML_TYPE_Q5_K: ftype = LLAMA_FTYPE_MOSTLY_Q5_K_M; break;
+ case GGML_TYPE_Q6_K: ftype = LLAMA_FTYPE_MOSTLY_Q6_K; break;
case GGML_TYPE_IQ2_XXS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_XXS; break;
case GGML_TYPE_IQ2_XS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_XS; break;
default:
generated by cgit v1.2.3 (git 2.25.1) at 2025-08-16 01:34:29 +0000