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https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
fix misplaced ram_used and ram_changed attributes
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parent
2ca8611723
commit
c39f8b478b
@ -147,9 +147,17 @@ class InvocationStatsService(InvocationStatsServiceBase):
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# {graph_id => NodeLog}
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self._stats: Dict[str, NodeLog] = {}
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self._cache_stats: Dict[str, CacheStats] = {}
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self.ram_used: float = 0.0
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self.ram_changed: float = 0.0
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class StatsContext:
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"""Context manager for collecting statistics."""
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invocation: BaseInvocation = None
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collector: "InvocationStatsServiceBase" = None
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graph_id: str = None
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start_time: int = 0
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ram_used: int = 0
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model_manager: ModelManagerService = None
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def __init__(
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self,
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@ -177,13 +185,15 @@ class InvocationStatsService(InvocationStatsServiceBase):
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def __exit__(self, *args):
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"""Called on exit from the context."""
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ram_used = psutil.Process().memory_info().rss
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self.collector.update_mem_stats(
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ram_used=ram_used / GIG,
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ram_changed=(ram_used - self.ram_used) / GIG,
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)
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self.collector.update_invocation_stats(
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graph_id=self.graph_id,
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invocation_type=self.invocation.type,
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time_used=time.time() - self.start_time,
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vram_used=torch.cuda.max_memory_allocated() / GIG if torch.cuda.is_available() else 0.0,
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ram_used=ram_used / GIG,
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ram_changed=(ram_used - self.ram_used) / GIG,
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)
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def collect_stats(
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@ -213,14 +223,26 @@ class InvocationStatsService(InvocationStatsServiceBase):
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except KeyError:
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logger.warning(f"Attempted to clear statistics for unknown graph {graph_execution_id}")
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def update_mem_stats(
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self,
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ram_used: float,
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ram_changed: float,
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):
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"""
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Update the collector with RAM memory usage info.
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:param ram_used: How much RAM is currently in use.
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:param ram_changed: How much RAM changed since last generation.
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"""
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self.ram_used = ram_used
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self.ram_changed = ram_changed
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def update_invocation_stats(
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self,
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graph_id: str,
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invocation_type: str,
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time_used: float,
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vram_used: float,
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ram_used: float,
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ram_changed: float,
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):
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"""
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Add timing information on execution of a node. Usually
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@ -238,8 +260,6 @@ class InvocationStatsService(InvocationStatsServiceBase):
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stats.calls += 1
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stats.time_used += time_used
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stats.max_vram = max(stats.max_vram, vram_used)
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stats.ram_used = ram_used
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stats.ram_changed = ram_changed
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def log_stats(self):
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"""
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@ -266,7 +286,7 @@ class InvocationStatsService(InvocationStatsServiceBase):
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loaded = sum([v for v in cache_stats.loaded_model_sizes.values()]) / GIG
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logger.info(f"TOTAL GRAPH EXECUTION TIME: {total_time:7.3f}s")
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logger.info("RAM used by InvokeAI process: " + "%4.2fG" % stats.ram_used + f" ({stats.ram_changed:+5.3f}G)")
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logger.info("RAM used by InvokeAI process: " + "%4.2fG" % self.ram_used + f" ({self.ram_changed:+5.3f}G)")
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logger.info(f"RAM used to load models: {loaded:4.2f}G")
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if torch.cuda.is_available():
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logger.info("VRAM in use: " + "%4.3fG" % (torch.cuda.memory_allocated() / GIG))
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