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mlflow_logger_v1 - Adding option to log last model #13

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mlflow_logger_v1 - Adding option to log last model #13

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668e69a
Changed mlflow logger to upload model_last artifact too
adin786 Nov 5, 2022
03e103a
Stripped out unnecessary logging statements
adin786 Nov 5, 2022
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36 changes: 32 additions & 4 deletions spacy_loggers/mlflow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,13 @@
from spacy.training.loggers import console_logger


class ModelDir:
def __init__(self) -> None:
self.path = None

def update(self, path: str) -> None:
self.path = path

Comment on lines +14 to +20
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@rmitsch rmitsch Dec 7, 2022

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I think we can ditch ModelDir - let's use a simple string for the latest model path (latest_model_dir or similar).

# entry point: spacy.MLflowLogger.v1
def mlflow_logger_v1(
run_id: Optional[str] = None,
Expand All @@ -19,6 +26,7 @@ def mlflow_logger_v1(
nested: bool = False,
tags: Optional[Dict[str, Any]] = None,
remove_config_values: List[str] = [],
log_latest_dir: bool = True,
):
try:
import mlflow
Expand All @@ -33,7 +41,7 @@ def mlflow_logger_v1(
)

console = console_logger(progress_bar=False)

def setup_logger(
nlp: "Language", stdout: IO = sys.stdout, stderr: IO = sys.stderr
) -> Tuple[Callable[[Dict[str, Any]], None], Callable[[], None]]:
Expand All @@ -58,6 +66,15 @@ def setup_logger(
mlflow.log_params({k.replace("@", ""): v for k, v in batch})

console_log_step, console_finalize = console(nlp, stdout, stderr)

if log_latest_dir:
latest_model = ModelDir()

def log_model(path, name):
mlflow.log_artifacts(
path,
name
)
Comment on lines +73 to +77
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@rmitsch rmitsch Dec 7, 2022

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Similar: since this is just a wrapper without added functionality, let's use mlflow.log_artifacts() directly.


def log_step(info: Optional[Dict[str, Any]]):
console_log_step(info)
Expand All @@ -66,23 +83,34 @@ def log_step(info: Optional[Dict[str, Any]]):
other_scores = info["other_scores"]
losses = info["losses"]
output_path = info.get("output_path", None)
if log_latest_dir:
latest_model.update(output_path)

if score is not None:
mlflow.log_metric("score", score)
mlflow.log_metric("score", score, info["step"])
if losses:
mlflow.log_metrics({f"loss_{k}": v for k, v in losses.items()})
mlflow.log_metrics({f"loss_{k}": v for k, v in losses.items()}, info["step"])
if isinstance(other_scores, dict):
mlflow.log_metrics(
{
k: v
for k, v in util.dict_to_dot(other_scores).items()
if isinstance(v, float) or isinstance(v, int)
}
},
info["step"]
)
if output_path and score == max(info["checkpoints"])[0]:
nlp = load(output_path)
mlflow.spacy.log_model(nlp, "best")
log_model(output_path, 'model_best')
Comment on lines 104 to +105
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@rmitsch rmitsch Dec 7, 2022

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It irks me that now we have three artifacts - best, model_best and model_last. Ideally I'd like to have best and last, both the complete set of associated data (like best has, see screenshot). Just for the sake of consistency. If that doesn't work out due to the issues you described, I guess this is fine. I'll look into this.
image

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@rmitsch rmitsch Dec 7, 2022

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Note: I ended up using mlflow.log_artifact() rather than mlflow.spacy.log_model() because when I use the latter method outside of the log_step() function it looks like spacy just aborts the process abruptly, without letting the mlflow.spacy function do its thing.

Hm, I ran this with

        def finalize() -> None:
            if log_latest_dir:
                mlflow.spacy.log_model(nlp, "model_last")

now and this seemed to work (see image). What's your outcome?
image



def finalize() -> None:

if log_latest_dir:
log_model(latest_model.path, 'model_last')

print('End run')
Comment on lines +109 to +113
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@rmitsch rmitsch Dec 7, 2022

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Suggested change
if log_latest_dir:
log_model(latest_model.path, 'model_last')
print('End run')
if log_latest_dir:
log_model(latest_model.path, 'model_last')

console_finalize()
mlflow.end_run()

Expand Down