Add deprecated emit_metric() helper to cog interface (#2068)

This helps with the transition between the main cog branch and the
experimental `async` branch. Models built for the `async` branch
can be run on either without code changes.

python/cog/__init__.py

@@ -4,7 +4,7 @@
 
 from .base_predictor import BasePredictor
 from .mimetypes_ext import install_mime_extensions
-from .server.scope import current_scope
+from .server.scope import current_scope, emit_metric
 from .types import (
     ConcatenateIterator,
     ExperimentalFeatureWarning,
@@ -24,10 +24,11 @@
 
 __all__ = [
     "__version__",
+    "current_scope",
+    "emit_metric",
     "BaseModel",
     "BasePredictor",
     "ConcatenateIterator",
-    "current_scope",
     "ExperimentalFeatureWarning",
     "File",
     "Input",

python/cog/server/scope.py

@@ -37,3 +37,21 @@ def scope(sc: Scope) -> Generator[None, None, None]:
         yield
     finally:
         _current_scope.reset(s)
+
+
+def emit_metric(name: str, value: Union[float, int]) -> None:
+    """
+    DEPRECATED: This function will be removed in a future version of cog.
+
+    Records a metric event from the model. Intended to be called from
+    within the `predict` function.
+
+    This allows older models using an experimental `cog.emit_metric` function
+    to run using newer releases without requiring code changes.
+    """
+    warnings.warn(
+        "emit_metric is deprecated and will be removed in a future version. Use `current_scope().record_metric()` instead",
+        category=DeprecationWarning,
+        stacklevel=1,
+    )
+    current_scope().record_metric(name, value)

python/tests/server/fixtures/emit_metric.py

@@ -0,0 +1,13 @@
+from cog import emit_metric
+
+
+class Predictor:
+    def setup(self):
+        print("did setup")
+
+    def predict(self, *, name: str) -> str:
+        print(f"hello, {name}")
+
+        emit_metric("foo", 123)
+
+        return f"hello, {name}"

python/tests/server/fixtures/emit_metric_async.py

@@ -0,0 +1,13 @@
+from cog import emit_metric
+
+
+class Predictor:
+    def setup(self):
+        print("did setup")
+
+    async def predict(self, *, name: str) -> str:
+        print(f"hello, {name}")
+
+        emit_metric("foo", 123)
+
+        return f"hello, {name}"

python/tests/server/test_worker.py

@@ -82,6 +82,20 @@
             "foo": 123,
         },
     ),
+    (
+        WorkerConfig("emit_metric"),
+        {"name": ST_NAMES},
+        {
+            "foo": 123,
+        },
+    ),
+    (
+        WorkerConfig("emit_metric_async", is_async=True),
+        {"name": ST_NAMES},
+        {
+            "foo": 123,
+        },
+    ),
 ]
 
 OUTPUT_FIXTURES = [