Fix indent in docstring.

Author: Markus Semmler

src/pydvl/value/semivalues.py

@@ -371,7 +371,8 @@ def compute_beta_shapley_semivalues(
         sampler_t: The sampler type to use. See :mod:`pydvl.value.sampler` for a list.
         n_jobs: Number of parallel jobs to use.
         seed: Either an instance of a numpy random number generator or a seed for it.
-        config: Object configuring parallel computation, with cluster address, number of cpus, etc.
+        config: Object configuring parallel computation, with cluster address, number of
+            cpus, etc.
         progress: Whether to display a progress bar.
 
     Returns:

src/pydvl/value/shapley/common.py

@@ -89,8 +89,7 @@ def compute_shapley_values(
             criteria using boolean operators. Some methods ignore this argument,
             others require specific subtypes.
         n_jobs: Number of parallel jobs (available only to some methods)
-        seed: Either an instance of a numpy random number generator or a seed
-            for it.
+        seed: Either an instance of a numpy random number generator or a seed for it.
         mode: Choose which shapley algorithm to use. See
             [ShapleyMode][pydvl.value.shapley.ShapleyMode] for a list of allowed value.
 

src/pydvl/value/shapley/gt.py

@@ -140,8 +140,7 @@ def _group_testing_shapley(
         n_samples: total number of samples (subsets) to use.
         progress: Whether to display progress bars for each job.
         job_id: id to use for reporting progress (e.g. to place progres bars)
-        seed: Either an instance of a numpy random number generator or a seed
-            for it.
+        seed: Either an instance of a numpy random number generator or a seed for it.
     Returns:
 
     """
@@ -202,8 +201,7 @@ def group_testing_shapley(
         config: Object configuring parallel computation, with cluster
             address, number of cpus, etc.
         progress: Whether to display progress bars for each job.
-        seed: Either an instance of a numpy random number generator or a seed
-            for it.
+        seed: Either an instance of a numpy random number generator or a seed for it.
         options: Additional options to pass to
             [cvxpy.Problem.solve()](https://www.cvxpy.org/tutorial/advanced/index.html#solve-method-options).
             E.g. to change the solver (which defaults to `cvxpy.SCS`) pass

src/pydvl/value/shapley/montecarlo.py

@@ -323,7 +323,7 @@ def combinatorial_montecarlo_shapley(
             number of cpus, etc.
         progress: Whether to display progress bars for each job.
         seed: Either an instance of a numpy random number generator or a seed for it.
-        f
+
     Returns:
         Object with the data values.
     """