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Rename GIG -> GB. And move it to where it's being used.

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This commit is contained in:
Ryan Dick 2024-01-11 12:10:31 -05:00 committed by Kent Keirsey
parent c8929b35f0
commit e2387546fe
2 changed files with 11 additions and 11 deletions
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3
invokeai/app/services/invocation_stats/invocation_stats_common.py
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@ -1,9 +1,6 @@
from collections import defaultdict
from dataclasses import dataclass
# size of GIG in bytes
GIG = 1073741824
@dataclass
class NodeExecutionStats:

19
invokeai/app/services/invocation_stats/invocation_stats_default.py
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@ -10,7 +10,10 @@ from invokeai.app.services.invoker import Invoker
from invokeai.backend.model_management.model_cache import CacheStats
from .invocation_stats_base import InvocationStatsServiceBase
from .invocation_stats_common import GIG, GraphExecutionStats, NodeExecutionStats
from .invocation_stats_common import GraphExecutionStats, NodeExecutionStats
# Size of 1GB in bytes.
GB = 2**30
class InvocationStatsService(InvocationStatsServiceBase):
@ -50,9 +53,9 @@ class InvocationStatsService(InvocationStatsServiceBase):
invocation_type=invocation.type,
start_time=start_time,
end_time=time.time(),
start_ram_gb=start_ram / GIG,
end_ram_gb=psutil.Process().memory_info().rss / GIG,
peak_vram_gb=torch.cuda.max_memory_allocated() / GIG if torch.cuda.is_available() else 0.0,
start_ram_gb=start_ram / GB,
end_ram_gb=psutil.Process().memory_info().rss / GB,
peak_vram_gb=torch.cuda.max_memory_allocated() / GB if torch.cuda.is_available() else 0.0,
)
self._stats[graph_execution_state_id].add_node_execution_stats(node_stats)
@ -83,12 +86,12 @@ class InvocationStatsService(InvocationStatsServiceBase):
log = graph_stats.get_pretty_log(graph_id)
cache_stats = self._cache_stats[graph_id]
hwm = cache_stats.high_watermark / GIG
tot = cache_stats.cache_size / GIG
loaded = sum(list(cache_stats.loaded_model_sizes.values())) / GIG
hwm = cache_stats.high_watermark / GB
tot = cache_stats.cache_size / GB
loaded = sum(list(cache_stats.loaded_model_sizes.values())) / GB
log += f"RAM used to load models: {loaded:4.2f}G\n"
if torch.cuda.is_available():
log += f"VRAM in use: {(torch.cuda.memory_allocated() / GIG):4.3f}G\n"
log += f"VRAM in use: {(torch.cuda.memory_allocated() / GB):4.3f}G\n"
log += "RAM cache statistics:\n"
log += f" Model cache hits: {cache_stats.hits}\n"
log += f" Model cache misses: {cache_stats.misses}\n"