[pre-commit.ci] auto fixes from pre-commit.com hooks

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examples/gmrf.py

@@ -155,6 +155,7 @@
 #
 # The following training loop requires a GPU with at least 11 GB of memory.
 
+
 # %%
 @jax.jit
 def loss(noisy_image, target_image, log_potentials):

examples/ising_model.py

@@ -65,6 +65,7 @@
 # %% [markdown]
 # ### Gradients and batching
 
+
 # %%
 def loss(log_potentials_updates, evidence_updates):
     bp_arrays = bp.init(

examples/rcn.py

@@ -225,6 +225,7 @@ def fetch_mnist_dataset(test_size: int, seed: int = 5) -> tuple[np.ndarray, np.n
 # %% [markdown]
 # ### 4.2.1 Pre-compute the valid configs for different perturb radius.
 
+
 # %%
 def valid_configs(r: int, hps: int, vps: int) -> np.ndarray:
     """Returns the valid configurations for a factor given the perturb radius.
@@ -294,6 +295,7 @@ def valid_configs(r: int, hps: int, vps: int) -> np.ndarray:
 # %% [markdown]
 # ## 5.1 Helper functions to initialize the evidence for a given image
 
+
 # %%
 def get_bu_msg(img: np.ndarray) -> np.ndarray:
     """Computes the bottom-up messages given a test image.
@@ -365,6 +367,7 @@ def get_bu_msg(img: np.ndarray) -> np.ndarray:
 # %% [markdown]
 # ## 5.2 Run MAP inference on all test images
 
+
 # %%
 def get_evidence(bu_msg: np.ndarray, frc: np.ndarray) -> np.ndarray:
     """Returns the evidence (shape (n_frcs, M)).

pgmax/factor/enum.py

@@ -256,7 +256,6 @@ def pass_enum_fac_to_var_messages(
     num_val_configs: int,
     temperature: float,
 ) -> jnp.ndarray:
-
     """Passes messages from EnumFactors to Variables.
 
     The update is performed in two steps. First, a "summary" array is generated that has an entry for every valid

pgmax/factor/logical.py

@@ -312,7 +312,6 @@ def pass_logical_fac_to_var_messages(
     temperature: float,
     log_potentials: Optional[jnp.ndarray] = None,
 ) -> jnp.ndarray:
-
     """Passes messages from LogicalFactors to Variables.
 
     Args: