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refactor: remove deprecated x_shape where not needed. #1271

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Merged
merged 1 commit into from
Sep 11, 2024
Merged

refactor: remove deprecated x_shape where not needed. #1271

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1 change: 0 additions & 1 deletion sbi/inference/posteriors/ensemble_posterior.py
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Original file line number Diff line number Diff line change
Expand Up @@ -96,7 +96,6 @@ def __init__(
potential_fn=potential_fn,
theta_transform=theta_transform,
device=device,
x_shape=None,
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This is passed as None explicitly here, i.e., the x_shape argument was not added to the user-facing constructor in the first place.
Thus I think it's fine to remove it here.

)

def ensure_same_device(self, posteriors: List) -> str:
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2 changes: 0 additions & 2 deletions sbi/inference/trainers/fmpe/fmpe.py
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Expand Up @@ -23,7 +23,6 @@
npe_msg_on_invalid_x,
validate_theta_and_x,
warn_if_zscoring_changes_data,
x_shape_from_simulation,
)
from sbi.utils.sbiutils import mask_sims_from_prior

Expand Down Expand Up @@ -199,7 +198,6 @@ def train(
theta[self.train_indices].to("cpu"),
x[self.train_indices].to("cpu"),
)
self._x_shape = x_shape_from_simulation(x.to("cpu"))

del theta, x

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2 changes: 0 additions & 2 deletions sbi/inference/trainers/npse/npse.py
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Expand Up @@ -26,7 +26,6 @@
test_posterior_net_for_multi_d_x,
validate_theta_and_x,
warn_if_zscoring_changes_data,
x_shape_from_simulation,
)
from sbi.utils.sbiutils import ImproperEmpirical, mask_sims_from_prior

Expand Down Expand Up @@ -282,7 +281,6 @@ def default_calibration_kernel(x):
theta[self.train_indices].to("cpu"),
x[self.train_indices].to("cpu"),
)
self._x_shape = x_shape_from_simulation(x.to("cpu"))

test_posterior_net_for_multi_d_x(
self._neural_net,
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2 changes: 0 additions & 2 deletions sbi/inference/trainers/nre/nre_base.py
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Expand Up @@ -21,7 +21,6 @@
check_estimator_arg,
check_prior,
clamp_and_warn,
x_shape_from_simulation,
)
from sbi.utils.torchutils import repeat_rows

Expand Down Expand Up @@ -203,7 +202,6 @@ def train(
theta[self.train_indices].to("cpu"),
x[self.train_indices].to("cpu"),
)
self._x_shape = x_shape_from_simulation(x.to("cpu"))
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self._x_shape is not used internally anymore, so it's safe to remove it here.

del x, theta
self._neural_net.to(self._device)

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4 changes: 1 addition & 3 deletions tests/test_utils.py
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Expand Up @@ -219,7 +219,6 @@ def __init__(
potential_fn: Callable,
theta_transform: Optional[TorchTransform] = None,
device: Optional[str] = "cpu",
x_shape: Optional[torch.Size] = None,
):
"""
Args:
Expand All @@ -228,10 +227,9 @@ def __init__(
Allows to perform, e.g. MCMC in unconstrained space.
device: Training device, e.g., "cpu", "cuda" or "cuda:0". If None,
`potential_fn.device` is used.
x_shape: Shape of the observed data.
"""
assert isinstance(potential_fn, PosteriorPotential)
super().__init__(potential_fn, theta_transform, device, x_shape)
super().__init__(potential_fn, theta_transform, device)

def sample(
self,
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