#include <string>
#include <vector>
+#define GGUF_MAX_STRING_LENGTH (1024*1024*1024)
+#define GGUF_MAX_ARRAY_ELEMENTS (1024*1024*1024)
+
+#ifdef _WIN32
+# define gguf_ftell _ftelli64
+# define gguf_fseek _fseeki64
+#else
+# define gguf_ftell ftello
+# define gguf_fseek fseeko
+#endif
+
template <typename T>
struct type_to_gguf_type;
};
struct gguf_reader {
- FILE * file;
+ gguf_reader(FILE * file) : file(file) {
+ // read the remaining bytes once and update on each read
+ nbytes_remain = file_remain(file);
+ }
- gguf_reader(FILE * file) : file(file) {}
+ // helper for remaining bytes in a file
+ static uint64_t file_remain(FILE * file) {
+ const int64_t cur = gguf_ftell(file);
+ if (cur < 0) {
+ return 0;
+ }
+ if (gguf_fseek(file, 0, SEEK_END) != 0) {
+ gguf_fseek(file, cur, SEEK_SET);
+
+ return 0;
+ }
+ const int64_t end = gguf_ftell(file);
+ if (end < 0) {
+ gguf_fseek(file, cur, SEEK_SET);
+
+ return 0;
+ }
+ gguf_fseek(file, cur, SEEK_SET);
+ return static_cast<uint64_t>(end - cur);
+ }
template <typename T>
bool read(T & dst) const {
- return fread(&dst, 1, sizeof(dst), file) == sizeof(dst);
+ const size_t size = sizeof(dst);
+ if (nbytes_remain < size) {
+ return false;
+ }
+ const size_t nread = fread(&dst, 1, size, file);
+ nbytes_remain -= nread;
+ return nread == size;
}
template <typename T>
bool read(std::vector<T> & dst, const size_t n) const {
+ if (n > GGUF_MAX_ARRAY_ELEMENTS) {
+ return false;
+ }
+ if constexpr (std::is_same<T, std::string>::value) {
+ // strings are prefixed with their length, so we need to account for that
+ if (n > SIZE_MAX / sizeof(uint64_t)) {
+ return false;
+ }
+ if (nbytes_remain < n * sizeof(uint64_t)) {
+ return false;
+ }
+ } else {
+ if (n > SIZE_MAX / sizeof(T)) {
+ return false;
+ }
+ if (nbytes_remain < n * sizeof(T)) {
+ return false;
+ }
+ }
dst.resize(n);
for (size_t i = 0; i < dst.size(); ++i) {
if constexpr (std::is_same<T, bool>::value) {
}
bool read(std::string & dst) const {
- uint64_t size = -1;
+ uint64_t size = 0;
if (!read(size)) {
return false;
}
- dst.resize(size);
- return fread(dst.data(), 1, dst.length(), file) == dst.length();
+ if (size > GGUF_MAX_STRING_LENGTH) {
+ GGML_LOG_ERROR("%s: string length %" PRIu64 " exceeds maximum %" PRIu64 "\n", __func__, size, (uint64_t) GGUF_MAX_STRING_LENGTH);
+ return false;
+ }
+ if (size > nbytes_remain) {
+ GGML_LOG_ERROR("%s: string length %" PRIu64 " exceeds remaining file size %" PRIu64 " bytes\n", __func__, size, nbytes_remain);
+ return false;
+ }
+ dst.resize(static_cast<size_t>(size));
+ const size_t nread = fread(dst.data(), 1, size, file);
+ nbytes_remain -= nread;
+ return nread == size;
}
bool read(void * dst, const size_t size) const {
- return fread(dst, 1, size, file) == size;
+ if (size > nbytes_remain) {
+ return false;
+ }
+ const size_t nread = fread(dst, 1, size, file);
+ nbytes_remain -= nread;
+ return nread == size;
}
+
+private:
+ FILE * file;
+
+ mutable uint64_t nbytes_remain;
};
struct gguf_context * gguf_init_empty(void) {
// tensor shape
{
- uint32_t n_dims = -1;
+ uint32_t n_dims = 0;
ok = ok && gr.read(n_dims);
if (n_dims > GGML_MAX_DIMS) {
GGML_LOG_ERROR("%s: tensor '%s' has invalid number of dimensions: %" PRIu32 " > %" PRIu32 "\n",
// check that tensor type is within defined range
if (info.t.type < 0 || info.t.type >= GGML_TYPE_COUNT) {
- GGML_LOG_ERROR("%s: tensor '%s' has invalid ggml type %d (%s)\n",
- __func__, info.t.name, info.t.type, ggml_type_name(info.t.type));
+ GGML_LOG_ERROR("%s: tensor '%s' has invalid ggml type %d. should be in [0, %d)\n",
+ __func__, info.t.name, info.t.type, GGML_TYPE_COUNT);
ok = false;
break;
}
break;
}
+ // check that the size of the tensor in bytes is representable
+ if (ok && uint64_t(ggml_nelements(&info.t)/ggml_blck_size(info.t.type)) > SIZE_MAX/ggml_type_size(info.t.type)) {
+ GGML_LOG_ERROR("%s: tensor '%s' with shape (%" PRIi64 ", %" PRIi64 ", %" PRIi64 ", %" PRIi64 ") has a size in bytes > %zu\n",
+ __func__, info.t.name, info.t.ne[0], info.t.ne[1], info.t.ne[2], info.t.ne[3], SIZE_MAX);
+ ok = false;
+ break;
+ }
+
// calculate byte offsets given the tensor shape and type
info.t.nb[0] = type_size;
info.t.nb[1] = info.t.nb[0]*(info.t.ne[0]/blck_size);
GGML_ASSERT(int64_t(ctx->info.size()) == n_tensors);
// we require the data section to be aligned, so take into account any padding
- if (fseek(file, GGML_PAD(ftell(file), ctx->alignment), SEEK_SET) != 0) {
+ if (gguf_fseek(file, GGML_PAD(gguf_ftell(file), ctx->alignment), SEEK_SET) != 0) {
GGML_LOG_ERROR("%s: failed to seek to beginning of data section\n", __func__);
gguf_free(ctx);
return nullptr;
}
// store the current file offset - this is where the data section starts
- ctx->offset = ftell(file);
+ ctx->offset = gguf_ftell(file);
// compute the total size of the data section, taking into account the alignment
{
// the ggml_tensor structs to the appropriate locations in the binary blob
// compute the exact size needed for the new ggml_context
- const size_t mem_size =
- params.no_alloc ?
- (n_tensors )*ggml_tensor_overhead() :
- (n_tensors + 1)*ggml_tensor_overhead() + ctx->size;
+ size_t mem_size = 0;
+ if (params.no_alloc) {
+ if (n_tensors != 0 && SIZE_MAX / n_tensors < ggml_tensor_overhead()) {
+ GGML_LOG_ERROR("%s: memory size overflow while allocating ggml context\n", __func__);
+ gguf_free(ctx);
+ return nullptr;
+ }
+
+ const size_t overhead = n_tensors * ggml_tensor_overhead();
+
+ mem_size = overhead;
+ } else {
+ if ((n_tensors + 1) != 0 && SIZE_MAX / (n_tensors + 1) < ggml_tensor_overhead()) {
+ GGML_LOG_ERROR("%s: memory size overflow while allocating ggml context\n", __func__);
+ gguf_free(ctx);
+ return nullptr;
+ }
+
+ const size_t overhead = (n_tensors + 1) * ggml_tensor_overhead();
+
+ if (SIZE_MAX - overhead < ctx->size) {
+ GGML_LOG_ERROR("%s: memory size overflow while allocating ggml context\n", __func__);
+ gguf_free(ctx);
+ return nullptr;
+ }
+
+ mem_size = overhead + ctx->size;
+ }
struct ggml_init_params pdata = {
/*mem_size =*/ mem_size,
FILE * file = ggml_fopen(fname, "rb");
if (!file) {
- GGML_LOG_ERROR("%s: failed to open GGUF file '%s'\n", __func__, fname);
+ GGML_LOG_ERROR("%s: failed to open GGUF file '%s' (%s)\n", __func__, fname, strerror(errno));
return nullptr;
}
ctx->info[tensor_id].t.data = (void *)(uintptr_t)data; // double cast suppresses warning about casting away const
}
-struct gguf_writer {
- std::vector<int8_t> & buf;
+struct gguf_writer_base {
+ size_t written_bytes {0u};
+
+ ~gguf_writer_base(void) = default;
- gguf_writer(std::vector<int8_t> & buf) : buf(buf) {}
+ // we bet on devirtualization
+ virtual void write(int8_t val) = 0;
+ virtual void write(const std::vector<int8_t> & val) = 0;
+ virtual void write_tensor_data(const struct gguf_tensor_info & info, size_t offset_data, size_t alignment) = 0;
template <typename T>
- void write(const T & val) const {
+ void write(const T & val) {
for (size_t i = 0; i < sizeof(val); ++i) {
- buf.push_back(reinterpret_cast<const int8_t *>(&val)[i]);
+ write(reinterpret_cast<const int8_t *>(&val)[i]);
}
}
- void write(const std::vector<int8_t> & val) const {
- buf.insert(buf.end(), val.begin(), val.end());
- }
-
- void write(const bool & val) const {
+ void write(const bool & val) {
const int8_t val8 = val ? 1 : 0;
write(val8);
}
- void write(const std::string & val) const {
+ void write(const std::string & val) {
{
const uint64_t n = val.length();
write(n);
}
for (size_t i = 0; i < val.length(); ++i) {
- buf.push_back(reinterpret_cast<const int8_t *>(val.data())[i]);
+ write((val.data())[i]);
}
}
- void write(const char * val) const {
+ void write(const char * val) {
write(std::string(val));
}
- void write(const enum ggml_type & val) const {
+ void write(const enum ggml_type & val) {
write(int32_t(val));
}
- void write(const enum gguf_type & val) const {
+ void write(const enum gguf_type & val) {
write(int32_t(val));
}
- void write(const struct gguf_kv & kv) const {
+ void write(const struct gguf_kv & kv) {
const uint64_t ne = kv.get_ne();
write(kv.get_key());
}
}
- void write_tensor_meta(const struct gguf_tensor_info & info) const {
+ void write_tensor_meta(const struct gguf_tensor_info & info) {
write(info.t.name);
const uint32_t n_dims = ggml_n_dims(&info.t);
write(info.offset);
}
- void pad(const size_t alignment) const {
- while (buf.size() % alignment != 0) {
+ void pad(const size_t alignment) {
+ while (written_bytes % alignment != 0) {
const int8_t zero = 0;
write(zero);
}
}
+};
+
+// vector buffer based writer
+struct gguf_writer_buf final : public gguf_writer_base {
+ std::vector<int8_t> & buf;
+
+ gguf_writer_buf(std::vector<int8_t> & buf) : buf(buf) {}
- void write_tensor_data(const struct gguf_tensor_info & info, const size_t offset_data, const size_t alignment) const {
+ using gguf_writer_base::write;
+
+ void write(const int8_t val) override {
+ buf.push_back(val);
+ written_bytes++;
+ }
+
+ void write(const std::vector<int8_t> & val) override {
+ buf.insert(buf.end(), val.begin(), val.end());
+ written_bytes += val.size();
+ }
+
+ void write_tensor_data(const struct gguf_tensor_info & info, const size_t offset_data, const size_t alignment) override {
GGML_ASSERT(buf.size() - offset_data == info.offset);
GGML_ASSERT(ggml_is_contiguous(&info.t));
GGML_ASSERT(info.t.data);
memcpy(buf.data() + offset, info.t.data, nbytes);
}
+ written_bytes += nbytes;
pad(alignment);
}
};
-void gguf_write_to_buf(const struct gguf_context * ctx, std::vector<int8_t> & buf, bool only_meta) {
- const struct gguf_writer gw(buf);
+// file based writer
+struct gguf_writer_file final : public gguf_writer_base {
+ FILE * file;
+
+ gguf_writer_file(FILE* file) : file(file) {}
+
+ using gguf_writer_base::write;
+
+ void write(const int8_t val) override {
+ const auto real_val = static_cast<uint8_t>(val);
+ const auto ret = fputc(real_val, file);
+ written_bytes++;
+ if (ret != real_val) {
+ throw std::runtime_error("unexpected fputc result '" + std::to_string(ret) + "' instead of '" + std::to_string((int)real_val) + "'");
+ }
+ }
+
+ void write(const std::vector<int8_t> & val) override {
+ const auto ret = fwrite(val.data(), 1, val.size(), file);
+ written_bytes += val.size();
+ if (ret != val.size()) {
+ throw std::runtime_error("unexpected fwrite number of bytes written, '" + std::to_string(ret) + "' instead of '" + std::to_string(val.size()) + "'");
+ }
+ }
+
+ void write_tensor_data(const struct gguf_tensor_info & info, const size_t offset_data, const size_t alignment) override {
+ GGML_ASSERT(written_bytes - offset_data == info.offset);
+
+ GGML_ASSERT(ggml_is_contiguous(&info.t));
+ const size_t nbytes = ggml_nbytes(&info.t);
+
+ std::vector<int8_t> buf(nbytes);
+ if (info.t.buffer) {
+ ggml_backend_tensor_get(&info.t, buf.data(), 0, nbytes);
+ } else {
+ GGML_ASSERT(info.t.data);
+ memcpy(buf.data(), info.t.data, nbytes);
+ }
+ write(buf);
+ pad(alignment);
+ }
+};
+
+template <typename writer_t>
+static void gguf_write_out(const struct gguf_context * ctx, writer_t & gw, bool only_meta) {
const int64_t n_kv = gguf_get_n_kv(ctx);
const int64_t n_tensors = gguf_get_n_tensors(ctx);
return;
}
- const size_t offset_data = gw.buf.size();
+ const size_t offset_data = gw.written_bytes;
// write tensor data
for (int64_t i = 0; i < n_tensors; ++i) {
}
}
+void gguf_write_to_buf(const struct gguf_context * ctx, std::vector<int8_t> & buf, bool only_meta) {
+ gguf_writer_buf gw(buf);
+ gguf_write_out(ctx, gw, only_meta);
+}
+
bool gguf_write_to_file(const struct gguf_context * ctx, const char * fname, bool only_meta) {
FILE * file = ggml_fopen(fname, "wb");
return false;
}
- std::vector<int8_t> buf;
- gguf_write_to_buf(ctx, buf, only_meta);
- const bool ok = fwrite(buf.data(), 1, buf.size(), file) == buf.size();
+ try {
+ gguf_writer_file gw(file);
+ gguf_write_out(ctx, gw, only_meta);
+ } catch (const std::runtime_error& ex) {
+ GGML_LOG_ERROR("%s: failed to write GGUF data into '%s': %s\n", __func__, fname, ex.what());
+ fclose(file);
+ return false;
+ }
+
fclose(file);
- return ok;
+ return true;
}
size_t gguf_get_meta_size(const struct gguf_context * ctx) {
overview / pkg / ggml / sources / whisper.cpp / commitdiff