Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

added memory used to load models

Browse Source
This commit is contained in:
Lincoln Stein 2023-08-15 21:56:19 -04:00
parent ec10aca91e
commit f9958de6be
2 changed files with 26 additions and 17 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

21
invokeai/app/services/invocation_stats.py
View File

@ -256,22 +256,27 @@ class InvocationStatsService(InvocationStatsServiceBase):
logger.info(f"Graph stats: {graph_id}") logger.info(f"Graph stats: {graph_id}")
logger.info("Node Calls Seconds VRAM Used") logger.info("Node Calls Seconds VRAM Used")
for node_type, stats in self._stats[graph_id].nodes.items(): for node_type, stats in self._stats[graph_id].nodes.items():
logger.info(f"{node_type:<20} {stats.calls:>5} {stats.time_used:7.3f}s {stats.max_vram:4.2f}G") logger.info(f"{node_type:<20} {stats.calls:>5} {stats.time_used:7.3f}s {stats.max_vram:4.3f}G")
total_time += stats.time_used total_time += stats.time_used
logger.info(f"TOTAL GRAPH EXECUTION TIME: {total_time:7.3f}s")
logger.info("RAM used: " + "%4.2fG" % stats.ram_used + f" (delta={stats.ram_changed:4.2f}G)")
if torch.cuda.is_available():
logger.info("VRAM used (all processes): " + "%4.2fG" % (torch.cuda.memory_allocated() / GIG))
cache_stats = self._cache_stats[graph_id] cache_stats = self._cache_stats[graph_id]
hwm = cache_stats.high_watermark / GIG
tot = cache_stats.cache_size / GIG
loaded = sum([v for v in cache_stats.loaded_model_sizes.values()]) / GIG
logger.info(f"TOTAL GRAPH EXECUTION TIME: {total_time:7.3f}s")
logger.info(
"RAM used by InvokeAI process: " + "%4.2fG" % stats.ram_used + f" (delta={stats.ram_changed:4.2f}G)"
)
logger.info(f"RAM used to load models: {loaded:4.2f}G")
if torch.cuda.is_available():
logger.info("VRAM in use: " + "%4.3fG" % (torch.cuda.memory_allocated() / GIG))
logger.info("RAM cache statistics:") logger.info("RAM cache statistics:")
logger.info(f" Model cache hits: {cache_stats.hits}") logger.info(f" Model cache hits: {cache_stats.hits}")
logger.info(f" Model cache misses: {cache_stats.misses}") logger.info(f" Model cache misses: {cache_stats.misses}")
logger.info(f" Models cached: {cache_stats.in_cache}") logger.info(f" Models cached: {cache_stats.in_cache}")
logger.info(f" Models cleared from cache: {cache_stats.cleared}") logger.info(f" Models cleared from cache: {cache_stats.cleared}")
hwm = cache_stats.high_watermark / GIG logger.info(f" Cache high water mark: {hwm:4.2f}/{tot:4.2f}G")
tot = cache_stats.cache_size / GIG
logger.info(f" Cache RAM usage: {hwm:4.2f}/{tot:4.2f}G")
completed.add(graph_id) completed.add(graph_id)

22
invokeai/backend/model_management/model_cache.py
View File

@ -21,7 +21,7 @@ import os
import sys import sys
import hashlib import hashlib
from contextlib import suppress from contextlib import suppress
from dataclasses import dataclass from dataclasses import dataclass, field
from pathlib import Path from pathlib import Path
from typing import Dict, Union, types, Optional, Type, Any from typing import Dict, Union, types, Optional, Type, Any
@ -43,12 +43,14 @@ GIG = 1073741824
@dataclass @dataclass
class CacheStats(object): class CacheStats(object):
hits: int = 0 hits: int = 0 # cache hits
misses: int = 0 misses: int = 0 # cache misses
high_watermark: int = 0 high_watermark: int = 0 # amount of cache used
in_cache: int = 0 in_cache: int = 0 # number of models in cache
cleared: int = 0 cleared: int = 0 # number of models cleared to make space
cache_size: int = 0 cache_size: int = 0 # total size of cache
# {submodel_key => size}
loaded_model_sizes: Dict[str, int] = field(default_factory=dict)
class ModelLocker(object): class ModelLocker(object):
@ -194,7 +196,6 @@ class ModelCache(object):
model_type=model_type, model_type=model_type,
submodel_type=submodel, submodel_type=submodel,
) )
# TODO: lock for no copies on simultaneous calls? # TODO: lock for no copies on simultaneous calls?
cache_entry = self._cached_models.get(key, None) cache_entry = self._cached_models.get(key, None)
if cache_entry is None: if cache_entry is None:
@ -219,11 +220,14 @@ class ModelCache(object):
else: else:
if self.stats: if self.stats:
self.stats.hits += 1 self.stats.hits += 1
self.stats.cache_size = self.max_cache_size * GIG
if self.stats: if self.stats:
self.stats.cache_size = self.max_cache_size * GIG
self.stats.high_watermark = max(self.stats.high_watermark, self._cache_size()) self.stats.high_watermark = max(self.stats.high_watermark, self._cache_size())
self.stats.in_cache = len(self._cached_models) self.stats.in_cache = len(self._cached_models)
self.stats.loaded_model_sizes[key] = max(
self.stats.loaded_model_sizes.get("key", 0), model_info.get_size(submodel)
)
with suppress(Exception): with suppress(Exception):
self._cache_stack.remove(key) self._cache_stack.remove(key)