f2890a4494
* fix(ext_server): Port llama.cpp sampling refactors to ext_server
This was a fairly large changeset. I closely followed the changes here:
df270ef745
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(server.cpp): Refactor server.cpp logging for llama.cpp overhaul
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Bump llama.cpp to the latest master with `granite` support
This does not yet have granite MoE support, but that can come in a
follow up PR
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(patches): Update all patches (except solar-pro) to work with bumped llama.cpp
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(solar): Update solar patch for llama.cpp bump
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama.cpp): Bump llama.cpp for granitemoe support
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama.cpp): Bump llama.cpp for granitemoe support
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(solar): Update the solar-pro patch for latest llama.cpp bump
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama.cpp): Bump to the latest master of llama.cpp
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(patches): Update all patches for latest bump
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama): Always run sync.sh from the right directory
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama/patches): Update llama patches
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(llama)!: Rough sync with llama.cpp submodule
There are a number of changes that will need to be propagated to llama.go
before any of this works!
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama/patches): Add a patch and update for missing ggml-impl.h include
This include is where the ggml_cgraph struct is defined. It is included in
many of the .c files to define the forward declartion in ggml.h. It seems
that with the subset of code included here, the import was somehow lost (or
out-of-order) when building, so adding this include to llama.cpp fixes the
missing definition.
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama/sync): Add missing ggml-cpu-impl.h copy-over in sync.sh
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Add missing log.cpp
This was added as part of the logging overhaul done in llama.cpp
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Overhaul use of sampling module for llama.cpp changes
The changes here reflect the changes made in the big llama.cpp sampling PR
https://github.com/ggerganov/llama.cpp/pull/9294
The sampling functionality is now broken into the base interface
(llama_sampler) and the generation implementation (gpt_sampler). The
changes here reflect that. Since the sampling.h/sampling.cpp code uses c++
STL headers, the sampling_ext.[h|cpp] wrapper is maintained to allow go to
access a pure-C interface.
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Fix the impl of SampleTokenGreedy for new sampling
I don't think this method is currently used, so it could probably just be
removed so that all sampling goes through the GPT interface, but in the
interest of doing no harm, this should keep the method working as expected.
Branch: IBMGraniteArchitectureSupport
* fix(llama): Remove unused SampleTokenGreedy
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(sync): Remove bash-specific change to sync.sh
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* chore(gofumpt): Format on llama.go to pass linting
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llm): Fix missing <thread> include in ext_server
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Remove TODO about grammar_first
This feature was not used/needed previously so should be fine without
plumbing it through now.
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Better naming for sampling wrapper and args
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Fix patch 05 to use new wrapper api and re-sync
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* runner: Flush pending responses before returning
If there are any pending reponses (such as from potential stop
tokens) then we should send them back before ending the sequence.
Otherwise, we can be missing tokens at the end of a response.
Fixes #6707
* fix(llama/sampling): Use gpt_sampler with a forward declaration
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llama): Remove unnecessary patch for gguf impl header
This was caused by an earlier mistake in the embeddings patch that was
dereferencing the pointer instead of using the wrapper API.
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix(llm): Remove use of deprecated --log-disable flag
Branch: IBMGraniteArchitectureSupport
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
---------
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
1068 lines
39 KiB
C
Vendored
1068 lines
39 KiB
C
Vendored
/**
|
|
* llama.cpp - commit 3f1ae2e32cde00c39b96be6d01c2997c29bae555 - do not edit this file
|
|
*
|
|
* MIT License
|
|
*
|
|
* Copyright (c) 2023-2024 The ggml authors
|
|
*
|
|
* Permission is hereby granted, free of charge, to any person obtaining a copy
|
|
* of this software and associated documentation files (the "Software"), to deal
|
|
* in the Software without restriction, including without limitation the rights
|
|
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
|
* copies of the Software, and to permit persons to whom the Software is
|
|
* furnished to do so, subject to the following conditions:
|
|
*
|
|
* The above copyright notice and this permission notice shall be included in all
|
|
* copies or substantial portions of the Software.
|
|
*
|
|
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
|
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
|
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
|
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
|
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
|
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
|
* SOFTWARE.
|
|
*/
|
|
|
|
#include "ggml-alloc.h"
|
|
#include "ggml-backend-impl.h"
|
|
#include "ggml.h"
|
|
#include "ggml-impl.h"
|
|
#include <assert.h>
|
|
#include <limits.h>
|
|
#include <stdarg.h>
|
|
#include <stdio.h>
|
|
#include <stdlib.h>
|
|
#include <string.h>
|
|
|
|
#define MAX(a, b) ((a) > (b) ? (a) : (b))
|
|
#define MAX_FREE_BLOCKS 256
|
|
|
|
//#define GGML_ALLOCATOR_DEBUG
|
|
|
|
//#define AT_PRINTF(...) fprintf(stderr, __VA_ARGS__)
|
|
#define AT_PRINTF(...)
|
|
|
|
|
|
static bool ggml_is_view(const struct ggml_tensor * t) {
|
|
return t->view_src != NULL;
|
|
}
|
|
|
|
static bool ggml_are_same_layout(const struct ggml_tensor * a, const struct ggml_tensor * b) {
|
|
if (a->type != b->type) {
|
|
return false;
|
|
}
|
|
for (int i = 0; i < GGML_MAX_DIMS; i++) {
|
|
if (a->ne[i] != b->ne[i]) {
|
|
return false;
|
|
}
|
|
if (a->nb[i] != b->nb[i]) {
|
|
return false;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
static bool ggml_op_can_inplace(enum ggml_op op) {
|
|
switch (op) {
|
|
case GGML_OP_SCALE:
|
|
case GGML_OP_DIAG_MASK_ZERO:
|
|
case GGML_OP_DIAG_MASK_INF:
|
|
case GGML_OP_ADD:
|
|
case GGML_OP_ADD1:
|
|
case GGML_OP_SUB:
|
|
case GGML_OP_MUL:
|
|
case GGML_OP_DIV:
|
|
case GGML_OP_SQR:
|
|
case GGML_OP_SQRT:
|
|
case GGML_OP_LOG:
|
|
case GGML_OP_UNARY:
|
|
case GGML_OP_ROPE:
|
|
case GGML_OP_RMS_NORM:
|
|
case GGML_OP_SOFT_MAX:
|
|
return true;
|
|
|
|
default:
|
|
return false;
|
|
}
|
|
}
|
|
|
|
static size_t aligned_offset(const void * buffer, size_t offset, size_t alignment) {
|
|
assert(alignment && !(alignment & (alignment - 1))); // power of 2
|
|
size_t align = (alignment - (((uintptr_t)buffer + offset) % alignment)) % alignment;
|
|
return offset + align;
|
|
}
|
|
|
|
// tallocr
|
|
|
|
struct ggml_tallocr ggml_tallocr_new(ggml_backend_buffer_t buffer) {
|
|
void * base = ggml_backend_buffer_get_base(buffer);
|
|
size_t align = ggml_backend_buffer_get_alignment(buffer);
|
|
|
|
assert(align && !(align & (align - 1))); // power of 2
|
|
|
|
struct ggml_tallocr talloc = (struct ggml_tallocr) {
|
|
/*.buffer = */ buffer,
|
|
/*.base = */ base,
|
|
/*.alignment = */ align,
|
|
/*.offset = */ aligned_offset(base, 0, align),
|
|
};
|
|
return talloc;
|
|
}
|
|
|
|
void ggml_tallocr_alloc(struct ggml_tallocr * talloc, struct ggml_tensor * tensor) {
|
|
size_t size = ggml_backend_buffer_get_alloc_size(talloc->buffer, tensor);
|
|
size = GGML_PAD(size, talloc->alignment);
|
|
|
|
if (talloc->offset + size > ggml_backend_buffer_get_size(talloc->buffer)) {
|
|
fprintf(stderr, "%s: not enough space in the buffer to allocate %s (needed %zu, available %zu)\n",
|
|
__func__, tensor->name, size, ggml_backend_buffer_get_size(talloc->buffer) - talloc->offset);
|
|
GGML_ABORT("not enough space in the buffer");
|
|
}
|
|
|
|
void * addr = (char *)ggml_backend_buffer_get_base(talloc->buffer) + talloc->offset;
|
|
talloc->offset += size;
|
|
|
|
assert(((uintptr_t)addr % talloc->alignment) == 0);
|
|
|
|
ggml_backend_tensor_alloc(talloc->buffer, tensor, addr);
|
|
}
|
|
|
|
// dynamic tensor allocator
|
|
|
|
struct free_block {
|
|
size_t offset;
|
|
size_t size;
|
|
};
|
|
|
|
struct ggml_dyn_tallocr {
|
|
size_t alignment;
|
|
int n_free_blocks;
|
|
struct free_block free_blocks[MAX_FREE_BLOCKS];
|
|
size_t max_size;
|
|
|
|
#ifdef GGML_ALLOCATOR_DEBUG
|
|
struct {
|
|
const struct ggml_tensor * tensor;
|
|
size_t offset;
|
|
} allocated_tensors[1024];
|
|
#endif
|
|
};
|
|
|
|
#ifdef GGML_ALLOCATOR_DEBUG
|
|
static void add_allocated_tensor(struct ggml_dyn_tallocr * alloc, size_t offset, const struct ggml_tensor * tensor) {
|
|
for (int i = 0; i < 1024; i++) {
|
|
if (alloc->allocated_tensors[i].tensor == NULL) {
|
|
alloc->allocated_tensors[i].tensor = tensor;
|
|
alloc->allocated_tensors[i].offset = offset;
|
|
return;
|
|
}
|
|
}
|
|
GGML_ABORT("out of allocated_tensors");
|
|
}
|
|
static void remove_allocated_tensor(struct ggml_dyn_tallocr * alloc, size_t offset, const struct ggml_tensor * tensor) {
|
|
for (int i = 0; i < 1024; i++) {
|
|
if (alloc->allocated_tensors[i].offset == offset) {
|
|
alloc->allocated_tensors[i].tensor = NULL;
|
|
return;
|
|
}
|
|
}
|
|
GGML_ABORT("tried to free tensor %s not found\n", tensor->name);
|
|
}
|
|
#endif
|
|
|
|
static size_t ggml_dyn_tallocr_alloc(struct ggml_dyn_tallocr * alloc, size_t size, const struct ggml_tensor * tensor) {
|
|
size = aligned_offset(NULL, size, alloc->alignment);
|
|
|
|
AT_PRINTF("%s: allocating %s (%zu bytes) - ", __func__, tensor->name, size);
|
|
|
|
size_t max_avail = 0;
|
|
|
|
// find the best fitting free block besides the last block
|
|
int best_fit_block = -1;
|
|
size_t best_fit_size = SIZE_MAX;
|
|
for (int i = 0; i < alloc->n_free_blocks - 1; i++) {
|
|
struct free_block * block = &alloc->free_blocks[i];
|
|
max_avail = MAX(max_avail, block->size);
|
|
if (block->size >= size && block->size <= best_fit_size) {
|
|
best_fit_block = i;
|
|
best_fit_size = block->size;
|
|
}
|
|
}
|
|
|
|
if (best_fit_block == -1) {
|
|
// the last block is our last resort
|
|
struct free_block * block = &alloc->free_blocks[alloc->n_free_blocks - 1];
|
|
max_avail = MAX(max_avail, block->size);
|
|
if (block->size >= size) {
|
|
best_fit_block = alloc->n_free_blocks - 1;
|
|
} else {
|
|
// this should never happen
|
|
fprintf(stderr, "%s: not enough space in the buffer to allocate %zu bytes, largest block available %zu bytes\n",
|
|
__func__, size, max_avail);
|
|
GGML_ABORT("not enough space in the buffer");
|
|
}
|
|
}
|
|
|
|
struct free_block * block = &alloc->free_blocks[best_fit_block];
|
|
size_t offset = block->offset;
|
|
block->offset = offset + size;
|
|
block->size -= size;
|
|
if (block->size == 0) {
|
|
// remove block if empty
|
|
alloc->n_free_blocks--;
|
|
for (int j = best_fit_block; j < alloc->n_free_blocks; j++) {
|
|
alloc->free_blocks[j] = alloc->free_blocks[j+1];
|
|
}
|
|
}
|
|
|
|
AT_PRINTF("block %d, offset %zu\n", best_fit_block, offset);
|
|
|
|
#ifdef GGML_ALLOCATOR_DEBUG
|
|
add_allocated_tensor(alloc, offset, tensor);
|
|
size_t cur_max = offset + size;
|
|
if (cur_max > alloc->max_size) {
|
|
// sort allocated_tensors by offset
|
|
for (int i = 0; i < 1024; i++) {
|
|
for (int j = i + 1; j < 1024; j++) {
|
|
if (alloc->allocated_tensors[i].offset > alloc->allocated_tensors[j].offset) {
|
|
const struct ggml_tensor * tmp_tensor = alloc->allocated_tensors[i].tensor;
|
|
size_t tmp_offset = alloc->allocated_tensors[i].offset;
|
|
alloc->allocated_tensors[i].tensor = alloc->allocated_tensors[j].tensor;
|
|
alloc->allocated_tensors[i].offset = alloc->allocated_tensors[j].offset;
|
|
alloc->allocated_tensors[j].tensor = tmp_tensor;
|
|
alloc->allocated_tensors[j].offset = tmp_offset;
|
|
}
|
|
}
|
|
}
|
|
fprintf(stderr, "max_size = %.2f MB: tensors: ", cur_max / 1024.0 / 1024.0);
|
|
for (int i = 0; i < 1024; i++) {
|
|
if (alloc->allocated_tensors[i].tensor) {
|
|
fprintf(stderr, "%s [%zx-%zx] (%.2f MB) ", alloc->allocated_tensors[i].tensor->name,
|
|
alloc->allocated_tensors[i].offset,
|
|
alloc->allocated_tensors[i].offset + ggml_nbytes(alloc->allocated_tensors[i].tensor),
|
|
ggml_nbytes(alloc->allocated_tensors[i].tensor) / 1024.0 / 1024.0);
|
|
}
|
|
}
|
|
fprintf(stderr, "\n");
|
|
}
|
|
#endif
|
|
|
|
alloc->max_size = MAX(alloc->max_size, offset + size);
|
|
|
|
return offset;
|
|
|
|
GGML_UNUSED(tensor);
|
|
}
|
|
|
|
// this is a very naive implementation, but for our case the number of free blocks should be very small
|
|
static void ggml_dyn_tallocr_free_tensor(struct ggml_dyn_tallocr * alloc, size_t offset, size_t size, const struct ggml_tensor * tensor) {
|
|
size = aligned_offset(NULL, size, alloc->alignment);
|
|
|
|
AT_PRINTF("%s: freeing %s at %zu (%zu bytes) - n_free_blocks = %d\n", __func__, tensor->name, offset, size, alloc->n_free_blocks);
|
|
|
|
#ifdef GGML_ALLOCATOR_DEBUG
|
|
remove_allocated_tensor(alloc, offset, tensor);
|
|
#endif
|
|
|
|
// see if we can merge with an existing block
|
|
for (int i = 0; i < alloc->n_free_blocks; i++) {
|
|
struct free_block * block = &alloc->free_blocks[i];
|
|
// check if ptr is at the end of the block
|
|
if (block->offset + block->size == offset) {
|
|
block->size += size;
|
|
// check if we can merge with the next block
|
|
if (i < alloc->n_free_blocks - 1 && block->offset + block->size == alloc->free_blocks[i+1].offset) {
|
|
block->size += alloc->free_blocks[i+1].size;
|
|
alloc->n_free_blocks--;
|
|
for (int j = i+1; j < alloc->n_free_blocks; j++) {
|
|
alloc->free_blocks[j] = alloc->free_blocks[j+1];
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
// check if ptr is at the beginning of the block
|
|
if (offset + size == block->offset) {
|
|
block->offset = offset;
|
|
block->size += size;
|
|
// check if we can merge with the previous block
|
|
if (i > 0 && alloc->free_blocks[i-1].offset + alloc->free_blocks[i-1].size == block->offset) {
|
|
alloc->free_blocks[i-1].size += block->size;
|
|
alloc->n_free_blocks--;
|
|
for (int j = i; j < alloc->n_free_blocks; j++) {
|
|
alloc->free_blocks[j] = alloc->free_blocks[j+1];
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
}
|
|
// otherwise, add a new block
|
|
GGML_ASSERT(alloc->n_free_blocks < MAX_FREE_BLOCKS && "out of free blocks");
|
|
// insert the new block in the correct position to keep the array sorted by address (to make merging blocks faster)
|
|
int insert_pos = 0;
|
|
while (insert_pos < alloc->n_free_blocks && alloc->free_blocks[insert_pos].offset < offset) {
|
|
insert_pos++;
|
|
}
|
|
// shift all blocks from insert_pos onward to make room for the new block
|
|
for (int i = alloc->n_free_blocks; i > insert_pos; i--) {
|
|
alloc->free_blocks[i] = alloc->free_blocks[i-1];
|
|
}
|
|
// insert the new block
|
|
alloc->free_blocks[insert_pos].offset = offset;
|
|
alloc->free_blocks[insert_pos].size = size;
|
|
alloc->n_free_blocks++;
|
|
|
|
GGML_UNUSED(tensor);
|
|
}
|
|
|
|
static void ggml_dyn_tallocr_reset(struct ggml_dyn_tallocr * alloc) {
|
|
alloc->n_free_blocks = 1;
|
|
alloc->free_blocks[0].offset = 0;
|
|
alloc->free_blocks[0].size = SIZE_MAX/2; // restrict maximum size of a measure allocator to half size_t max to avoid overflows
|
|
alloc->max_size = 0;
|
|
|
|
#ifdef GGML_ALLOCATOR_DEBUG
|
|
for (int i = 0; i < 1024; i++) {
|
|
alloc->allocated_tensors[i].tensor = NULL;
|
|
}
|
|
#endif
|
|
}
|
|
|
|
static struct ggml_dyn_tallocr * ggml_dyn_tallocr_new(size_t alignment) {
|
|
struct ggml_dyn_tallocr * alloc = (struct ggml_dyn_tallocr *)malloc(sizeof(struct ggml_dyn_tallocr));
|
|
|
|
*alloc = (struct ggml_dyn_tallocr) {
|
|
/*.alignment = */ alignment,
|
|
/*.n_free_blocks = */ 0,
|
|
/*.free_blocks = */ {{0}},
|
|
/*.max_size = */ 0,
|
|
#ifdef GGML_ALLOCATOR_DEBUG
|
|
/*.allocated_tensors = */ {{0}},
|
|
#endif
|
|
};
|
|
|
|
ggml_dyn_tallocr_reset(alloc);
|
|
|
|
return alloc;
|
|
}
|
|
|
|
static void ggml_dyn_tallocr_free(struct ggml_dyn_tallocr * alloc) {
|
|
free(alloc);
|
|
}
|
|
|
|
static size_t ggml_dyn_tallocr_max_size(struct ggml_dyn_tallocr * alloc) {
|
|
return alloc->max_size;
|
|
}
|
|
|
|
|
|
/////////////////////////////////////
|
|
|
|
// graph allocator
|
|
|
|
struct hash_node {
|
|
int n_children;
|
|
int n_views;
|
|
int buffer_id;
|
|
size_t offset; // offset within the buffer
|
|
bool allocated;
|
|
};
|
|
|
|
struct tensor_alloc {
|
|
int buffer_id;
|
|
size_t offset;
|
|
size_t size_max; // 0 = pre-allocated, unused, or view
|
|
};
|
|
|
|
struct leaf_alloc {
|
|
int buffer_id;
|
|
struct tensor_alloc leaf;
|
|
};
|
|
|
|
struct node_alloc {
|
|
struct tensor_alloc dst;
|
|
struct tensor_alloc src[GGML_MAX_SRC];
|
|
};
|
|
|
|
struct ggml_gallocr {
|
|
ggml_backend_buffer_type_t * bufts; // [n_buffers]
|
|
ggml_backend_buffer_t * buffers; // [n_buffers]
|
|
struct ggml_dyn_tallocr ** buf_tallocs; // [n_buffers]
|
|
int n_buffers;
|
|
|
|
struct ggml_hash_set hash_set;
|
|
struct hash_node * hash_values; // [hash_set.size]
|
|
|
|
struct node_alloc * node_allocs; // [n_nodes]
|
|
int n_nodes;
|
|
|
|
struct leaf_alloc * leaf_allocs; // [n_leafs]
|
|
int n_leafs;
|
|
};
|
|
|
|
ggml_gallocr_t ggml_gallocr_new_n(ggml_backend_buffer_type_t * bufts, int n_bufs) {
|
|
ggml_gallocr_t galloc = (ggml_gallocr_t)calloc(1, sizeof(struct ggml_gallocr));
|
|
GGML_ASSERT(galloc != NULL);
|
|
|
|
galloc->bufts = calloc(n_bufs, sizeof(ggml_backend_buffer_type_t));
|
|
GGML_ASSERT(galloc->bufts != NULL);
|
|
|
|
galloc->buffers = calloc(n_bufs, sizeof(ggml_backend_buffer_t));
|
|
GGML_ASSERT(galloc->buffers != NULL);
|
|
|
|
galloc->buf_tallocs = calloc(n_bufs, sizeof(struct ggml_dyn_tallocr *));
|
|
GGML_ASSERT(galloc->buf_tallocs != NULL);
|
|
|
|
for (int i = 0; i < n_bufs; i++) {
|
|
galloc->bufts[i] = bufts[i];
|
|
galloc->buffers[i] = NULL;
|
|
|
|
// check if the same buffer type is used multiple times and reuse the same allocator
|
|
for (int j = 0; j < i; j++) {
|
|
if (bufts[i] == bufts[j]) {
|
|
galloc->buf_tallocs[i] = galloc->buf_tallocs[j];
|
|
break;
|
|
}
|
|
}
|
|
|
|
if (galloc->buf_tallocs[i] == NULL) {
|
|
size_t alignment = ggml_backend_buft_get_alignment(bufts[i]);
|
|
galloc->buf_tallocs[i] = ggml_dyn_tallocr_new(alignment);
|
|
}
|
|
}
|
|
galloc->n_buffers = n_bufs;
|
|
|
|
return galloc;
|
|
}
|
|
|
|
ggml_gallocr_t ggml_gallocr_new(ggml_backend_buffer_type_t buft) {
|
|
return ggml_gallocr_new_n(&buft, 1);
|
|
}
|
|
|
|
void ggml_gallocr_free(ggml_gallocr_t galloc) {
|
|
if (galloc == NULL) {
|
|
return;
|
|
}
|
|
|
|
for (int i = 0; i < galloc->n_buffers; i++) {
|
|
if (galloc->buffers != NULL) {
|
|
// skip if already freed
|
|
bool freed = false;
|
|
for (int j = 0; j < i; j++) {
|
|
if (galloc->buffers[j] == galloc->buffers[i]) {
|
|
freed = true;
|
|
break;
|
|
}
|
|
}
|
|
if (!freed) {
|
|
ggml_backend_buffer_free(galloc->buffers[i]);
|
|
}
|
|
}
|
|
if (galloc->buf_tallocs != NULL) {
|
|
// skip if already freed
|
|
bool freed = false;
|
|
for (int j = 0; j < i; j++) {
|
|
if (galloc->buf_tallocs[j] == galloc->buf_tallocs[i]) {
|
|
freed = true;
|
|
break;
|
|
}
|
|
}
|
|
if (!freed) {
|
|
ggml_dyn_tallocr_free(galloc->buf_tallocs[i]);
|
|
}
|
|
}
|
|
}
|
|
|
|
ggml_hash_set_free(&galloc->hash_set);
|
|
free(galloc->hash_values);
|
|
free(galloc->bufts);
|
|
free(galloc->buffers);
|
|
free(galloc->buf_tallocs);
|
|
free(galloc->node_allocs);
|
|
free(galloc->leaf_allocs);
|
|
free(galloc);
|
|
}
|
|
|
|
typedef struct ggml_gallocr * ggml_gallocr_t;
|
|
|
|
static struct hash_node * ggml_gallocr_hash_get(ggml_gallocr_t galloc, struct ggml_tensor * t) {
|
|
size_t i = ggml_hash_find_or_insert(&galloc->hash_set, t);
|
|
return &galloc->hash_values[i];
|
|
}
|
|
|
|
static bool ggml_gallocr_is_own(ggml_gallocr_t galloc, struct ggml_tensor * t) {
|
|
return ggml_gallocr_hash_get(galloc, t)->allocated;
|
|
}
|
|
|
|
static void ggml_gallocr_set_node_offset(ggml_gallocr_t galloc, struct ggml_tensor * node, int buffer_id, size_t offset) {
|
|
struct hash_node * hn = ggml_gallocr_hash_get(galloc, node);
|
|
hn->buffer_id = buffer_id;
|
|
hn->offset = offset;
|
|
hn->allocated = true;
|
|
}
|
|
|
|
static bool ggml_gallocr_is_allocated(ggml_gallocr_t galloc, struct ggml_tensor * t) {
|
|
return t->data != NULL || ggml_gallocr_hash_get(galloc, t)->allocated;
|
|
}
|
|
|
|
static void ggml_gallocr_allocate_node(ggml_gallocr_t galloc, struct ggml_tensor * node, int buffer_id) {
|
|
struct hash_node * hn = ggml_gallocr_hash_get(galloc, node);
|
|
|
|
if (!ggml_gallocr_is_allocated(galloc, node) && !ggml_is_view(node)) {
|
|
hn->allocated = true;
|
|
assert(hn->offset == 0);
|
|
|
|
// try to reuse a parent's buffer (inplace)
|
|
if (ggml_op_can_inplace(node->op)) {
|
|
for (int i = 0; i < GGML_MAX_SRC; i++) {
|
|
struct ggml_tensor * parent = node->src[i];
|
|
if (parent == NULL) {
|
|
continue;
|
|
}
|
|
|
|
// if the node's data is external, then we cannot re-use it
|
|
if (!ggml_gallocr_is_own(galloc, parent)) {
|
|
AT_PRINTF("not reusing parent %s for %s as %p is external\n", parent->name, node->name, parent->data);
|
|
continue;
|
|
}
|
|
|
|
// outputs cannot be reused
|
|
if (parent->flags & GGML_TENSOR_FLAG_OUTPUT || (parent->view_src != NULL && parent->view_src->flags & GGML_TENSOR_FLAG_OUTPUT)) {
|
|
AT_PRINTF("not reusing parent %s for %s as it is an output\n", parent->name, node->name);
|
|
continue;
|
|
}
|
|
|
|
if (!ggml_are_same_layout(node, parent)) {
|
|
AT_PRINTF("not reusing parent %s for %s as layouts are different\n", parent->name, node->name);
|
|
continue;
|
|
}
|
|
|
|
struct hash_node * p_hn = ggml_gallocr_hash_get(galloc, parent);
|
|
if (p_hn->n_children == 1 && p_hn->n_views == 0) {
|
|
if (ggml_is_view(parent)) {
|
|
struct ggml_tensor * view_src = parent->view_src;
|
|
struct hash_node * view_src_hn = ggml_gallocr_hash_get(galloc, view_src);
|
|
if (view_src_hn->n_views == 1 && view_src_hn->n_children == 0 && view_src->data == parent->data) {
|
|
AT_PRINTF("reusing view parent %s (%s) for %s\n", parent->name, view_src->name, node->name);
|
|
assert(view_src_hn->offset == p_hn->offset);
|
|
hn->buffer_id = p_hn->buffer_id;
|
|
hn->offset = p_hn->offset;
|
|
p_hn->allocated = false; // avoid freeing the parent
|
|
view_src_hn->allocated = false;
|
|
return;
|
|
}
|
|
} else {
|
|
AT_PRINTF("reusing parent %s for %s\n", parent->name, node->name);
|
|
hn->buffer_id = p_hn->buffer_id;
|
|
hn->offset = p_hn->offset;
|
|
p_hn->allocated = false; // avoid freeing the parent
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
// allocate tensor from the buffer
|
|
struct ggml_dyn_tallocr * alloc = galloc->buf_tallocs[buffer_id];
|
|
ggml_backend_buffer_type_t buft = galloc->bufts[buffer_id];
|
|
size_t size = ggml_backend_buft_get_alloc_size(buft, node);
|
|
size_t offset = ggml_dyn_tallocr_alloc(alloc, size, node);
|
|
hn->buffer_id = buffer_id;
|
|
hn->offset = offset;
|
|
return;
|
|
}
|
|
}
|
|
|
|
static void ggml_gallocr_free_node(ggml_gallocr_t galloc, struct ggml_tensor * node) {
|
|
// graph outputs are never freed
|
|
if (node->flags & GGML_TENSOR_FLAG_OUTPUT) {
|
|
AT_PRINTF("not freeing output %s\n", node->name);
|
|
return;
|
|
}
|
|
|
|
struct hash_node * hn = ggml_gallocr_hash_get(galloc, node);
|
|
size_t offset = hn->offset;
|
|
int buffer_id = hn->buffer_id;
|
|
struct ggml_dyn_tallocr * alloc = galloc->buf_tallocs[buffer_id];
|
|
ggml_backend_buffer_type_t buft = galloc->bufts[buffer_id];
|
|
size_t size = ggml_backend_buft_get_alloc_size(buft, node);
|
|
ggml_dyn_tallocr_free_tensor(alloc, offset, size, node);
|
|
hn->allocated = false;
|
|
}
|
|
|
|
static int get_node_buffer_id(const int * node_buffer_ids, int i) {
|
|
return node_buffer_ids ? node_buffer_ids[i] : 0;
|
|
}
|
|
|
|
static void ggml_gallocr_alloc_graph_impl(ggml_gallocr_t galloc, struct ggml_cgraph * graph, const int * node_buffer_ids, const int * leaf_buffer_ids) {
|
|
// clear hash tables
|
|
ggml_hash_set_reset(&galloc->hash_set);
|
|
memset(galloc->hash_values, 0, sizeof(struct hash_node) * galloc->hash_set.size);
|
|
|
|
// allocate leafs
|
|
// these may be tensors that the application is not using in the graph, but may still want to allocate for other purposes
|
|
for (int i = 0; i < graph->n_leafs; i++) {
|
|
struct ggml_tensor * leaf = graph->leafs[i];
|
|
ggml_gallocr_allocate_node(galloc, leaf, get_node_buffer_id(leaf_buffer_ids, i));
|
|
}
|
|
|
|
// count number of children and views
|
|
// allocate other graph inputs and leafs first to avoid overwriting them
|
|
for (int i = 0; i < graph->n_nodes; i++) {
|
|
struct ggml_tensor * node = graph->nodes[i];
|
|
|
|
// TODO: better way to add external dependencies
|
|
// GGML_OP_NONE does not appear normally in the graph nodes, but is used by ggml-backend to add dependencies to
|
|
// control when some tensors are allocated and freed. in this case, the dependencies are in `src`, but the node
|
|
// itself is never used and should not be considered a dependency
|
|
if (ggml_is_view(node) && node->op != GGML_OP_NONE) {
|
|
struct ggml_tensor * view_src = node->view_src;
|
|
ggml_gallocr_hash_get(galloc, view_src)->n_views += 1;
|
|
}
|
|
|
|
if (node->flags & GGML_TENSOR_FLAG_INPUT) {
|
|
ggml_gallocr_allocate_node(galloc, graph->nodes[i], get_node_buffer_id(node_buffer_ids, i));
|
|
}
|
|
|
|
for (int j = 0; j < GGML_MAX_SRC; j++) {
|
|
struct ggml_tensor * src = node->src[j];
|
|
if (src == NULL) {
|
|
continue;
|
|
}
|
|
|
|
ggml_gallocr_hash_get(galloc, src)->n_children += 1;
|
|
|
|
// allocate explicit inputs
|
|
if (src->flags & GGML_TENSOR_FLAG_INPUT) {
|
|
ggml_gallocr_allocate_node(galloc, src, get_node_buffer_id(node_buffer_ids, i));
|
|
}
|
|
}
|
|
}
|
|
|
|
// allocate tensors
|
|
for (int i = 0; i < graph->n_nodes; i++) {
|
|
struct ggml_tensor * node = graph->nodes[i];
|
|
int buffer_id = get_node_buffer_id(node_buffer_ids, i);
|
|
|
|
// allocate parents (only leafs need to be allocated at this point)
|
|
for (int j = 0; j < GGML_MAX_SRC; j++) {
|
|
struct ggml_tensor * parent = node->src[j];
|
|
if (parent == NULL) {
|
|
continue;
|
|
}
|
|
ggml_gallocr_allocate_node(galloc, parent, buffer_id);
|
|
}
|
|
|
|
// allocate node
|
|
ggml_gallocr_allocate_node(galloc, node, buffer_id);
|
|
|
|
AT_PRINTF("exec: %s (%s) <= ", ggml_op_desc(node), node->name);
|
|
for (int j = 0; j < GGML_MAX_SRC; j++) {
|
|
struct ggml_tensor * parent = node->src[j];
|
|
if (parent == NULL) {
|
|
continue;
|
|
}
|
|
AT_PRINTF("%s", parent->name);
|
|
if (j < GGML_MAX_SRC - 1 && node->src[j + 1] != NULL) {
|
|
AT_PRINTF(", ");
|
|
}
|
|
}
|
|
AT_PRINTF("\n");
|
|
|
|
// update parents
|
|
for (int j = 0; j < GGML_MAX_SRC; j++) {
|
|
struct ggml_tensor * parent = node->src[j];
|
|
if (parent == NULL) {
|
|
continue;
|
|
}
|
|
struct hash_node * p_hn = ggml_gallocr_hash_get(galloc, parent);
|
|
p_hn->n_children -= 1;
|
|
|
|
AT_PRINTF("parent %s: %d children, %d views, allocated: %d\n",
|
|
parent->name, p_hn->n_children, p_hn->n_views, p_hn->allocated);
|
|
|
|
if (p_hn->n_children == 0 && p_hn->n_views == 0) {
|
|
if (ggml_is_view(parent)) {
|
|
struct ggml_tensor * view_src = parent->view_src;
|
|
struct hash_node * view_src_hn = ggml_gallocr_hash_get(galloc, view_src);
|
|
view_src_hn->n_views -= 1;
|
|
AT_PRINTF("view_src %s: %d children, %d views\n",
|
|
view_src->name, view_src_hn->n_children, view_src_hn->n_views);
|
|
if (view_src_hn->n_views == 0 && view_src_hn->n_children == 0 && view_src_hn->allocated) {
|
|
ggml_gallocr_free_node(galloc, view_src);
|
|
}
|
|
}
|
|
else if (p_hn->allocated) {
|
|
ggml_gallocr_free_node(galloc, parent);
|
|
}
|
|
}
|
|
AT_PRINTF("\n");
|
|
}
|
|
}
|
|
}
|
|
|
|
bool ggml_gallocr_reserve_n(ggml_gallocr_t galloc, struct ggml_cgraph * graph, const int * node_buffer_ids, const int * leaf_buffer_ids) {
|
|
size_t min_hash_size = graph->n_nodes + graph->n_leafs;
|
|
// add 25% margin to avoid hash collisions
|
|
min_hash_size += min_hash_size / 4;
|
|
|
|
// initialize hash table
|
|
if (galloc->hash_set.size < min_hash_size) {
|
|
ggml_hash_set_free(&galloc->hash_set);
|
|
galloc->hash_set = ggml_hash_set_new(min_hash_size);
|
|
GGML_ASSERT(galloc->hash_set.keys != NULL);
|
|
|
|
free(galloc->hash_values);
|
|
galloc->hash_values = malloc(sizeof(struct hash_node) * galloc->hash_set.size);
|
|
GGML_ASSERT(galloc->hash_values != NULL);
|
|
}
|
|
|
|
// reset allocators
|
|
for (int i = 0; i < galloc->n_buffers; i++) {
|
|
ggml_dyn_tallocr_reset(galloc->buf_tallocs[i]);
|
|
}
|
|
|
|
// allocate in hash table
|
|
ggml_gallocr_alloc_graph_impl(galloc, graph, node_buffer_ids, leaf_buffer_ids);
|
|
|
|
// set the node_allocs from the hash table
|
|
if (galloc->n_nodes < graph->n_nodes) {
|
|
free(galloc->node_allocs);
|
|
galloc->node_allocs = calloc(graph->n_nodes, sizeof(struct node_alloc));
|
|
GGML_ASSERT(galloc->node_allocs != NULL);
|
|
}
|
|
galloc->n_nodes = graph->n_nodes;
|
|
for (int i = 0; i < graph->n_nodes; i++) {
|
|
struct ggml_tensor * node = graph->nodes[i];
|
|
struct node_alloc * node_alloc = &galloc->node_allocs[i];
|
|
if (node->view_src || node->data) {
|
|
node_alloc->dst.buffer_id = -1;
|
|
node_alloc->dst.offset = SIZE_MAX;
|
|
node_alloc->dst.size_max = 0;
|
|
} else {
|
|
struct hash_node * hn = ggml_gallocr_hash_get(galloc, node);
|
|
node_alloc->dst.buffer_id = hn->buffer_id;
|
|
node_alloc->dst.offset = hn->offset;
|
|
node_alloc->dst.size_max = ggml_backend_buft_get_alloc_size(galloc->bufts[hn->buffer_id], node);
|
|
}
|
|
for (int j = 0; j < GGML_MAX_SRC; j++) {
|
|
struct ggml_tensor * src = node->src[j];
|
|
if (!src || src->view_src || src->data) {
|
|
node_alloc->src[j].buffer_id = -1;
|
|
node_alloc->src[j].offset = SIZE_MAX;
|
|
node_alloc->src[j].size_max = 0;
|
|
} else {
|
|
struct hash_node * hn = ggml_gallocr_hash_get(galloc, src);
|
|
node_alloc->src[j].buffer_id = hn->buffer_id;
|
|
node_alloc->src[j].offset = hn->offset;
|
|
node_alloc->src[j].size_max = ggml_backend_buft_get_alloc_size(galloc->bufts[hn->buffer_id], src);
|
|
}
|
|
}
|
|
}
|
|
if (galloc->n_leafs < graph->n_leafs) {
|
|
free(galloc->leaf_allocs);
|
|
galloc->leaf_allocs = calloc(graph->n_leafs, sizeof(galloc->leaf_allocs[0]));
|
|
GGML_ASSERT(galloc->leaf_allocs != NULL);
|
|
}
|
|
galloc->n_leafs = graph->n_leafs;
|
|
for (int i = 0; i < graph->n_leafs; i++) {
|
|
struct ggml_tensor * leaf = graph->leafs[i];
|
|
struct hash_node * hn = ggml_gallocr_hash_get(galloc, leaf);
|
|
galloc->leaf_allocs[i].buffer_id = hn->buffer_id;
|
|
if (leaf->view_src || leaf->data) {
|
|
galloc->leaf_allocs[i].leaf.buffer_id = -1;
|
|
galloc->leaf_allocs[i].leaf.offset = SIZE_MAX;
|
|
galloc->leaf_allocs[i].leaf.size_max = 0;
|
|
} else {
|
|
galloc->leaf_allocs[i].leaf.buffer_id = hn->buffer_id;
|
|
galloc->leaf_allocs[i].leaf.offset = hn->offset;
|
|
galloc->leaf_allocs[i].leaf.size_max = ggml_backend_buft_get_alloc_size(galloc->bufts[hn->buffer_id], leaf);
|
|
}
|
|
}
|
|
|
|
// reallocate buffers if needed
|
|
for (int i = 0; i < galloc->n_buffers; i++) {
|
|
// if the buffer type is used multiple times, we reuse the same buffer
|
|
for (int j = 0; j < i; j++) {
|
|
if (galloc->buf_tallocs[j] == galloc->buf_tallocs[i]) {
|
|
galloc->buffers[i] = galloc->buffers[j];
|
|
break;
|
|
}
|
|
}
|
|
|
|
size_t cur_size = galloc->buffers[i] ? ggml_backend_buffer_get_size(galloc->buffers[i]) : 0;
|
|
size_t new_size = ggml_dyn_tallocr_max_size(galloc->buf_tallocs[i]);
|
|
|
|
// even if there are no tensors allocated in this buffer, we still need to allocate it to initialize views
|
|
if (new_size > cur_size || galloc->buffers[i] == NULL) {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: reallocating %s buffer from size %.02f MiB to %.02f MiB\n", __func__, ggml_backend_buft_name(galloc->bufts[i]), cur_size / 1024.0 / 1024.0, new_size / 1024.0 / 1024.0);
|
|
#endif
|
|
|
|
ggml_backend_buffer_free(galloc->buffers[i]);
|
|
galloc->buffers[i] = ggml_backend_buft_alloc_buffer(galloc->bufts[i], new_size);
|
|
if (galloc->buffers[i] == NULL) {
|
|
fprintf(stderr, "%s: failed to allocate %s buffer of size %zu\n", __func__, ggml_backend_buft_name(galloc->bufts[i]), new_size);
|
|
return false;
|
|
}
|
|
ggml_backend_buffer_set_usage(galloc->buffers[i], GGML_BACKEND_BUFFER_USAGE_COMPUTE);
|
|
}
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
bool ggml_gallocr_reserve(ggml_gallocr_t galloc, struct ggml_cgraph *graph) {
|
|
return ggml_gallocr_reserve_n(galloc, graph, NULL, NULL);
|
|
}
|
|
|
|
static void ggml_gallocr_init_tensor(ggml_gallocr_t galloc, struct ggml_tensor * tensor, struct tensor_alloc * tensor_alloc) {
|
|
int buffer_id = tensor_alloc->buffer_id;
|
|
assert(tensor->data || tensor->view_src || ggml_backend_buffer_get_alloc_size(galloc->buffers[buffer_id], tensor) <= tensor_alloc->size_max);
|
|
|
|
if (tensor->view_src != NULL) {
|
|
if (tensor->buffer == NULL) {
|
|
assert(tensor_alloc->offset == SIZE_MAX);
|
|
if (tensor->view_src->buffer == NULL) {
|
|
// this tensor was allocated without ggml-backend
|
|
return;
|
|
}
|
|
ggml_backend_view_init(tensor);
|
|
}
|
|
} else {
|
|
if (tensor->data == NULL) {
|
|
assert(tensor_alloc->offset != SIZE_MAX);
|
|
assert(ggml_backend_buffer_get_alloc_size(galloc->buffers[buffer_id], tensor) <= tensor_alloc->size_max);
|
|
void * base = ggml_backend_buffer_get_base(galloc->buffers[buffer_id]);
|
|
void * addr = (char *)base + tensor_alloc->offset;
|
|
ggml_backend_tensor_alloc(galloc->buffers[buffer_id], tensor, addr);
|
|
} else {
|
|
if (tensor->buffer == NULL) {
|
|
// this tensor was allocated without ggml-backend
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
static bool ggml_gallocr_node_needs_realloc(ggml_gallocr_t galloc, struct ggml_tensor * node, struct tensor_alloc * talloc) {
|
|
size_t node_size = (node->data || node->view_src) ? 0 : ggml_backend_buft_get_alloc_size(galloc->bufts[talloc->buffer_id], node);
|
|
return talloc->size_max >= node_size;
|
|
}
|
|
|
|
static bool ggml_gallocr_needs_realloc(ggml_gallocr_t galloc, struct ggml_cgraph * graph) {
|
|
if (galloc->n_nodes != graph->n_nodes) {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: graph has different number of nodes\n", __func__);
|
|
#endif
|
|
return true;
|
|
}
|
|
|
|
if (galloc->n_leafs != graph->n_leafs) {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: graph has different number of leafs\n", __func__);
|
|
#endif
|
|
return true;
|
|
}
|
|
|
|
for (int i = 0; i < graph->n_nodes; i++) {
|
|
struct ggml_tensor * node = graph->nodes[i];
|
|
struct node_alloc * node_alloc = &galloc->node_allocs[i];
|
|
|
|
if (!ggml_gallocr_node_needs_realloc(galloc, node, &node_alloc->dst)) {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: node %s is not valid\n", __func__, node->name);
|
|
#endif
|
|
return true;
|
|
}
|
|
|
|
for (int j = 0; j < GGML_MAX_SRC; j++) {
|
|
struct ggml_tensor * src = node->src[j];
|
|
if (src == NULL) {
|
|
continue;
|
|
}
|
|
if (!ggml_gallocr_node_needs_realloc(galloc, src, &node_alloc->src[j])) {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: src %d (%s) of node %s is not valid\n", __func__, j, src->name, node->name);
|
|
#endif
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
bool ggml_gallocr_alloc_graph(ggml_gallocr_t galloc, struct ggml_cgraph * graph) {
|
|
if (ggml_gallocr_needs_realloc(galloc, graph)) {
|
|
if (galloc->n_buffers == 1) {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: reallocating buffers automatically\n", __func__);
|
|
#endif
|
|
if (!ggml_gallocr_reserve(galloc, graph)) {
|
|
return false;
|
|
}
|
|
} else {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: cannot reallocate multi buffer graph automatically, call reserve\n", __func__);
|
|
#endif
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// reset buffers
|
|
for (int i = 0; i < galloc->n_buffers; i++) {
|
|
if (galloc->buffers[i] != NULL) {
|
|
ggml_backend_buffer_reset(galloc->buffers[i]);
|
|
}
|
|
}
|
|
|
|
// allocate the graph tensors from the previous assignments
|
|
// leafs
|
|
for (int i = 0; i < graph->n_leafs; i++) {
|
|
struct ggml_tensor * leaf = graph->leafs[i];
|
|
struct leaf_alloc * leaf_alloc = &galloc->leaf_allocs[i];
|
|
ggml_gallocr_init_tensor(galloc, leaf, &leaf_alloc->leaf);
|
|
}
|
|
// nodes
|
|
for (int i = 0; i < graph->n_nodes; i++) {
|
|
struct ggml_tensor * node = graph->nodes[i];
|
|
struct node_alloc * node_alloc = &galloc->node_allocs[i];
|
|
for (int j = 0; j < GGML_MAX_SRC; j++) {
|
|
struct ggml_tensor * src = node->src[j];
|
|
if (src == NULL) {
|
|
continue;
|
|
}
|
|
ggml_gallocr_init_tensor(galloc, src, &node_alloc->src[j]);
|
|
}
|
|
ggml_gallocr_init_tensor(galloc, node, &node_alloc->dst);
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
size_t ggml_gallocr_get_buffer_size(ggml_gallocr_t galloc, int buffer_id) {
|
|
GGML_ASSERT(buffer_id >= 0 && buffer_id < galloc->n_buffers);
|
|
|
|
if (galloc->buffers[buffer_id] == NULL) {
|
|
return 0;
|
|
}
|
|
|
|
for (int i = 0; i < buffer_id; i++) {
|
|
if (galloc->buffers[i] == galloc->buffers[buffer_id]) {
|
|
// this buffer is the same as a previous one due to the same buffer type being used multiple times
|
|
// only return the buffer size the first time it appears to avoid double counting
|
|
return 0;
|
|
}
|
|
}
|
|
|
|
return ggml_backend_buffer_get_size(galloc->buffers[buffer_id]);
|
|
}
|
|
|
|
// utils
|
|
|
|
static bool alloc_tensor_range(struct ggml_context * ctx,
|
|
struct ggml_tensor * first, struct ggml_tensor * last,
|
|
ggml_backend_buffer_type_t buft, size_t size,
|
|
ggml_backend_buffer_t ** buffers, size_t * n_buffers) {
|
|
ggml_backend_buffer_t buffer = ggml_backend_buft_alloc_buffer(buft, size);
|
|
if (buffer == NULL) {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: failed to allocate %s buffer of size %zu\n", __func__, ggml_backend_buft_name(buft), size);
|
|
#endif
|
|
for (size_t i = 0; i < *n_buffers; i++) {
|
|
ggml_backend_buffer_free((*buffers)[i]);
|
|
}
|
|
free(*buffers);
|
|
return false;
|
|
}
|
|
|
|
struct ggml_tallocr tallocr = ggml_tallocr_new(buffer);
|
|
|
|
for (struct ggml_tensor * t = first; t != last; t = ggml_get_next_tensor(ctx, t)) {
|
|
if (t->data == NULL) {
|
|
if (t->view_src == NULL) {
|
|
ggml_tallocr_alloc(&tallocr, t);
|
|
} else if (t->buffer == NULL) {
|
|
ggml_backend_view_init(t);
|
|
}
|
|
} else {
|
|
if (t->view_src != NULL && t->buffer == NULL) {
|
|
// view of a pre-allocated tensor
|
|
ggml_backend_view_init(t);
|
|
}
|
|
}
|
|
}
|
|
|
|
*buffers = realloc(*buffers, sizeof(ggml_backend_buffer_t) * (*n_buffers + 1));
|
|
(*buffers)[(*n_buffers)++] = buffer;
|
|
|
|
return true;
|
|
}
|
|
|
|
ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors_from_buft(struct ggml_context * ctx, ggml_backend_buffer_type_t buft) {
|
|
GGML_ASSERT(ggml_get_no_alloc(ctx) == true);
|
|
|
|
size_t alignment = ggml_backend_buft_get_alignment(buft);
|
|
size_t max_size = ggml_backend_buft_get_max_size(buft);
|
|
|
|
ggml_backend_buffer_t * buffers = NULL;
|
|
size_t n_buffers = 0;
|
|
|
|
size_t cur_buf_size = 0;
|
|
struct ggml_tensor * first = ggml_get_first_tensor(ctx);
|
|
for (struct ggml_tensor * t = first; t != NULL; t = ggml_get_next_tensor(ctx, t)) {
|
|
size_t this_size = 0;
|
|
if (t->data == NULL && t->view_src == NULL) {
|
|
this_size = GGML_PAD(ggml_backend_buft_get_alloc_size(buft, t), alignment);
|
|
}
|
|
|
|
if (this_size > max_size) {
|
|
fprintf(stderr, "%s: tensor %s is too large to fit in a %s buffer (tensor size: %zu, max buffer size: %zu)\n",
|
|
__func__, t->name,
|
|
ggml_backend_buft_name(buft),
|
|
this_size, max_size);
|
|
for (size_t i = 0; i < n_buffers; i++) {
|
|
ggml_backend_buffer_free(buffers[i]);
|
|
}
|
|
free(buffers);
|
|
return NULL;
|
|
}
|
|
|
|
if ((cur_buf_size + this_size) > max_size) {
|
|
// allocate tensors in the current buffer
|
|
if (!alloc_tensor_range(ctx, first, t, buft, cur_buf_size, &buffers, &n_buffers)) {
|
|
return NULL;
|
|
}
|
|
first = t;
|
|
cur_buf_size = this_size;
|
|
} else {
|
|
cur_buf_size += this_size;
|
|
}
|
|
}
|
|
|
|
// allocate remaining tensors
|
|
if (cur_buf_size > 0) {
|
|
if (!alloc_tensor_range(ctx, first, NULL, buft, cur_buf_size, &buffers, &n_buffers)) {
|
|
return NULL;
|
|
}
|
|
}
|
|
|
|
if (n_buffers == 0) {
|
|
#ifndef NDEBUG
|
|
fprintf(stderr, "%s: all tensors in the context are already allocated\n", __func__);
|
|
#endif
|
|
return NULL;
|
|
}
|
|
|
|
ggml_backend_buffer_t buffer;
|
|
if (n_buffers == 1) {
|
|
buffer = buffers[0];
|
|
} else {
|
|
buffer = ggml_backend_multi_buffer_alloc_buffer(buffers, n_buffers);
|
|
}
|
|
free(buffers);
|
|
return buffer;
|
|
}
|
|
|
|
ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors(struct ggml_context * ctx, ggml_backend_t backend) {
|
|
return ggml_backend_alloc_ctx_tensors_from_buft(ctx, ggml_backend_get_default_buffer_type(backend));
|
|
}
|