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Fix incorrect input routing for models #3186

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merged 3 commits into from
May 31, 2024
Merged

Fix incorrect input routing for models #3186

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25812d9
Fix incorrect input routing
shchur May 31, 2024
4022835
Fix input for MXNet models
shchur May 31, 2024
e8afdde
Fix MXNet tests
shchur May 31, 2024
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19 changes: 15 additions & 4 deletions src/gluonts/model/forecast_generator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,6 +82,15 @@ def make_distribution_forecast(distr, *args, **kwargs) -> Forecast:
raise NotImplementedError


def make_predictions(prediction_net, inputs: dict):
# MXNet predictors only support positional arguments
class_name = prediction_net.__class__.__module__
if class_name.startswith("gluonts.mx") or class_name.startswith("mxnet"):
return prediction_net(*inputs.values())
else:
return prediction_net(**inputs)


class ForecastGenerator:
"""
Classes used to bring the output of a network into a class.
Expand Down Expand Up @@ -115,7 +124,7 @@ def __call__(
) -> Iterator[Forecast]:
for batch in inference_data_loader:
inputs = select(input_names, batch, ignore_missing=True)
(outputs,), loc, scale = prediction_net(*inputs.values())
(outputs,), loc, scale = make_predictions(prediction_net, inputs)
outputs = to_numpy(outputs)
if scale is not None:
outputs = outputs * to_numpy(scale[..., None])
Expand Down Expand Up @@ -159,14 +168,16 @@ def __call__(
) -> Iterator[Forecast]:
for batch in inference_data_loader:
inputs = select(input_names, batch, ignore_missing=True)
outputs = to_numpy(prediction_net(*inputs.values()))
outputs = to_numpy(make_predictions(prediction_net, inputs))
if output_transform is not None:
outputs = output_transform(batch, outputs)
if num_samples:
num_collected_samples = outputs[0].shape[0]
collected_samples = [outputs]
while num_collected_samples < num_samples:
outputs = to_numpy(prediction_net(*inputs.values()))
outputs = to_numpy(
make_predictions(prediction_net, inputs)
)
if output_transform is not None:
outputs = output_transform(batch, outputs)
collected_samples.append(outputs)
Expand Down Expand Up @@ -209,7 +220,7 @@ def __call__(
) -> Iterator[Forecast]:
for batch in inference_data_loader:
inputs = select(input_names, batch, ignore_missing=True)
outputs = prediction_net(*inputs.values())
outputs = make_predictions(prediction_net, inputs)

if output_transform:
log_once(OUTPUT_TRANSFORM_NOT_SUPPORTED_MSG)
Expand Down
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