pass platform through to pre-minimization

OpenFreeEnergy · Apr 22, 2023 · b73dfc6 · b73dfc6
1 parent 9abe3c9
commit b73dfc6
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Showing 2 changed files with 16 additions and 6 deletions.
diff --git a/openfe/protocols/openmm_rfe/_rfe_utils/multistate.py b/openfe/protocols/openmm_rfe/_rfe_utils/multistate.py
@@ -36,7 +36,8 @@ def __init__(self, *args, hybrid_factory=None, **kwargs):
 
     def setup(self, reporter, lambda_protocol,
               temperature=298.15 * unit.kelvin, n_replicas=None,
-              endstates=True, minimization_steps=100):
+              endstates=True, minimization_steps=100,
+              minimization_platform="CPU"):
         """
         Setup MultistateSampler based on the input lambda protocol and number
         of replicas.
@@ -58,7 +59,9 @@ class creation of LambdaProtocol.
             Whether or not to generate unsampled endstates (i.e. dispersion
             correction).
         minimization_steps : int
-            Number of steps to minimize states.
+            Number of steps to pre-minimize states.
+        minimization_platform : str
+            Platform to do the initial pre-minimization with.
 
         Attributes
         ----------
@@ -114,8 +117,10 @@ class creation of LambdaProtocol.
 
             # now generating a sampler_state for each thermodyanmic state,
             # with relaxed positions
+            # Note: remove once  choderalab/openmmtools#672 is completed
             minimize(compound_thermostate_copy, sampler_state,
-                     max_iterations=minimization_steps)
+                     max_iterations=minimization_steps,
+                     platform_name=minimization_platform)
             sampler_state_list.append(copy.deepcopy(sampler_state))
 
         del compound_thermostate, sampler_state
@@ -257,8 +262,10 @@ def create_endstates(first_thermostate, last_thermostate):
     return unsampled_endstates
 
 
-def minimize(thermodynamic_state: states.ThermodynamicState, sampler_state: states.SamplerState,
-             max_iterations: int=100) -> states.SamplerState:
+def minimize(thermodynamic_state: states.ThermodynamicState,
+             sampler_state: states.SamplerState,
+             max_iterations: int=100,
+             platform_name: str="CPU") -> states.SamplerState:
     """
     Adapted from perses.dispersed.feptasks.minimize
 
@@ -273,6 +280,8 @@ def minimize(thermodynamic_state: states.ThermodynamicState, sampler_state: stat
         The starting state at which to minimize the system.
     max_iterations : int, optional, default 100
         The maximum number of minimization steps. Default is 100.
+    platform_name : str
+        The OpenMM platform name to carry out the minimization with.
 
     Returns
     -------
@@ -281,7 +290,7 @@ def minimize(thermodynamic_state: states.ThermodynamicState, sampler_state: stat
     """
     # we won't take any steps, so use a simple integrator
     integrator = openmm.VerletIntegrator(1.0)
-    platform = openmm.Platform.getPlatformByName('CPU')
+    platform = openmm.Platform.getPlatformByName(platform_name)
     dummy_cache = cache.DummyContextCache(platform=platform)
     context, integrator = dummy_cache.get_context(
         thermodynamic_state, integrator

diff --git a/openfe/protocols/openmm_rfe/equil_rfe_methods.py b/openfe/protocols/openmm_rfe/equil_rfe_methods.py
@@ -628,6 +628,7 @@ def run(self, *, dry=False, verbose=True,
             lambda_protocol=lambdas,
             temperature=to_openmm(protocol_settings.thermo_settings.temperature),
             endstates=alchem_settings.unsampled_endstates,
+            minimization_platform=platform.getName(),
         )
 
         try: