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e0552b0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 | import mlflow
from typing import Protocol, Callable, Union
from contextlib import contextmanager
import torch
from torch import Tensor
def to_float(x):
if torch.is_tensor(x):
return float(x.detach().item())
return float(x)
type AddType = float | Tensor
class LogCall(Protocol):
def __call__(self, value: Union[AddType, Callable[[], AddType]]) -> None: ...
def __enter__(self) -> "LogCall": ...
def __exit__(self, exc_type, exc_val, exc_tb) -> None: ...
def __getattr__(self, name: str) -> "LogCall": ...
class Debug:
logs: dict[str, list[AddType | Callable[[], AddType]]] = {}
_current_prefix = ""
_is_pre = False
def __init__(
self,
experiment: str,
run: str,
):
mlflow.set_tracking_uri("http://127.0.0.1:5000")
mlflow.set_experiment(experiment)
if mlflow.active_run() is not None:
mlflow.end_run()
mlflow.start_run(run_name=run)
@contextmanager
def _scope(self, name: str, is_pre: bool = False):
old_prefix = self._current_prefix
old_is_pre = self._is_pre
new_path = f"{self._current_prefix}.{name}" if self._current_prefix else name
self._current_prefix = new_path
self._is_pre = is_pre
try:
yield self
finally:
self._current_prefix = old_prefix
self._is_pre = old_is_pre
def __getattr__(self, name: str) -> LogCall:
if name == "pre":
return self._PreProxy(self)
return self._DynamicLogger(self, name)
class _PreProxy:
def __init__(self, outer, path=""):
self.outer = outer
self.path = path
def __getattr__(self, name):
new_path = f"{self.path}.{name}" if self.path else name
return Debug._PreProxy(self.outer, new_path)
def __call__(self, value: Union[float, Callable[[], float]]):
self.outer.preAdd(self.path, value)
def __enter__(self):
self._cm = self.outer._scope(self.path, is_pre=True)
return self._cm.__enter__()
def __exit__(self, exc_type, exc_val, exc_tb):
return self._cm.__exit__(exc_type, exc_val, exc_tb)
class _DynamicLogger:
def __init__(self, parent, name):
self.parent = parent
self.name = name
self._cm = None
def __getattr__(self, name: str) -> "Debug._DynamicLogger":
new_name = f"{self.name}.{name}"
return Debug._DynamicLogger(self.parent, new_name)
def __call__(self, value: Union[float, Callable[[], float]]):
prefix = self.parent._current_prefix
full_key = f"{prefix}.{self.name}" if prefix else self.name
if self.parent._is_pre or callable(value):
self.parent.preAdd(full_key, value)
else:
self.parent.add(full_key, value)
def __enter__(self):
self._cm = self.parent._scope(self.name, is_pre=self.parent._is_pre)
return self._cm.__enter__()
def __exit__(self, exc_type, exc_val, exc_tb):
if self._cm:
return self._cm.__exit__(exc_type, exc_val, exc_tb)
def add(
self,
key: str,
value: AddType,
):
if key not in self.logs:
self.logs[key] = []
self.logs[key].append(to_float(value))
def preAdd(
self,
key: str,
fn: Callable[[], AddType],
):
if key not in self.logs:
self.logs[key] = []
self.logs[key].append(fn)
def process(self):
for key in self.logs:
self.logs[key] = [
to_float(item() if callable(item) else item) for item in self.logs[key]
]
def commit(self, step: int):
self.process()
metrics: dict[str, float] = {}
for key, values in self.logs.items():
if not values:
continue
total_sum = sum(values)
metrics[key.replace(".", "/")] = total_sum / len(values)
if step > 0 and step % 10 == 0:
mlflow.log_metrics(metrics, step)
self.logs = {}
def log_params(self, params: dict):
mlflow.log_params(params)
def end(self):
mlflow.end_run()
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