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Add support for images inside tables with Trackio completions logging #4505

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Merged
qgallouedec merged 1 commit into from
Nov 11, 2025
Merged

Add support for images inside tables with Trackio completions logging #4505

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49 changes: 22 additions & 27 deletions trl/trainer/grpo_trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1939,6 +1939,12 @@ def log(self, logs: dict[str, float], start_time: float | None = None) -> None:
self.num_completions_to_print,
)

logging_backends = []
if self.args.report_to and "wandb" in self.args.report_to and wandb.run is not None:
logging_backends.append(wandb)
if self.args.report_to and "trackio" in self.args.report_to:
logging_backends.append(trackio)

table = {
"step": [str(self.state.global_step)] * len(self._logs["prompt"]),
"prompt": self._logs["prompt"],
Expand All @@ -1950,34 +1956,23 @@ def log(self, logs: dict[str, float], start_time: float | None = None) -> None:
df_base = pd.DataFrame(table)
images_raw = self._logs["images"] or []

for logging_backend in self.args.report_to:
if logging_backend == "wandb":
if images_raw:
images = []
for image_list in self._logs["images"]:
images.append([wandb.Image(image) for image in image_list])
df = pd.concat([df_base, pd.Series(images, name="image")], axis=1, copy=False)
else:
df = df_base

if self.wandb_log_unique_prompts:
df = df.drop_duplicates(subset=["prompt"])

wandb.log({"completions": wandb.Table(dataframe=df)})

if logging_backend == "trackio":
if images_raw:
# TODO: Implement once supported upstream https://github.com/gradio-app/trackio/issues/334
logger.info("Skipping image logging for Trackio")
df = df_base
# images = []
# for image_list in self._logs["images"]:
# images.append([trackio.Image(image) for image in image_list])
# df = pd.concat([df_base, pd.Series(images, name="image")], axis=1, copy=False)
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else:
df = df_base
for logging_backend in logging_backends:
if images_raw:
images = []
for image_list in self._logs["images"]:
images.append([logging_backend.Image(image) for image in image_list])
df = pd.concat(
[df_base, pd.Series(images, name="image")],
axis=1,
copy=False,
)
else:
df = df_base

if self.wandb_log_unique_prompts:
df = df.drop_duplicates(subset=["prompt"])

trackio.log({"completions": trackio.Table(dataframe=df)})
logging_backend.log({"completions": logging_backend.Table(dataframe=df)})

# Ensure the model card is saved along with the checkpoint
def _save_checkpoint(self, model, trial):
Expand Down
49 changes: 22 additions & 27 deletions trl/trainer/rloo_trainer.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1534,6 +1534,12 @@ def log(self, logs: dict[str, float], start_time: float | None = None) -> None:
self.num_completions_to_print,
)

logging_backends = []
if self.args.report_to and "wandb" in self.args.report_to and wandb.run is not None:
logging_backends.append(wandb)
if self.args.report_to and "trackio" in self.args.report_to:
logging_backends.append(trackio)

table = {
"step": [str(self.state.global_step)] * len(self._logs["prompt"]),
"prompt": self._logs["prompt"],
Expand All @@ -1545,34 +1551,23 @@ def log(self, logs: dict[str, float], start_time: float | None = None) -> None:
df_base = pd.DataFrame(table)
images_raw = self._logs["images"] or []

for logging_backend in self.args.report_to:
if logging_backend == "wandb":
if images_raw:
images = []
for image_list in self._logs["images"]:
images.append([wandb.Image(image) for image in image_list])
df = pd.concat([df_base, pd.Series(images, name="image")], axis=1, copy=False)
else:
df = df_base

if self.wandb_log_unique_prompts:
df = df.drop_duplicates(subset=["prompt"])

wandb.log({"completions": wandb.Table(dataframe=df)})

if logging_backend == "trackio":
if images_raw:
# TODO: Implement once supported upstream https://github.com/gradio-app/trackio/issues/334
logger.info("Skipping image logging for Trackio")
df = df_base
# images = []
# for image_list in self._logs["images"]:
# images.append([trackio.Image(image) for image in image_list])
# df = pd.concat([df_base, pd.Series(images, name="image")], axis=1, copy=False)
else:
df = df_base
for logging_backend in logging_backends:
if images_raw:
images = []
for image_list in self._logs["images"]:
images.append([logging_backend.Image(image) for image in image_list])
df = pd.concat(
[df_base, pd.Series(images, name="image")],
axis=1,
copy=False,
)
else:
df = df_base

if self.wandb_log_unique_prompts:
df = df.drop_duplicates(subset=["prompt"])

trackio.log({"completions": trackio.Table(dataframe=df)})
logging_backend.log({"completions": logging_backend.Table(dataframe=df)})

# Ensure the model card is saved along with the checkpoint
def _save_checkpoint(self, model, trial):
Expand Down
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