# Copyright 2024 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Modules that predict refinement or updates of time-advanced states.""" import dataclasses from typing import Any, Callable, Optional from dinosaur import coordinate_systems from dinosaur import time_integration from dinosaur import typing import gin import haiku as hk import jax from model.legacy import equations from model.legacy import features from model.legacy import filters from model.legacy import integrators from model.legacy import mappings Pytree = typing.Pytree PyTreeState = typing.PyTreeState Forcing = typing.Forcing CorrectorFn = typing.CorrectorFn CorrectorModule = typing.CorrectorModule EquationModule = equations.EquationModule FeaturesModule = features.FeaturesModule MappingModule = mappings.MappingModule StepModule = typing.StepModule StepFilterModule = Callable[..., typing.PyTreeStepFilterFn] TimeIntegrator = integrators.TimeIntegrator TransformModule = typing.TransformModule @gin.register class PredictorEulerCorrector(hk.Module): """Corrector that takes Euler step ontop of a predictor step.""" def __init__( self, coords: coordinate_systems.CoordinateSystem, dt: float, physics_specs: Any, aux_features: typing.AuxFeatures, predictor_module: StepModule, filter_module: StepFilterModule = filters.NoFilter, name: Optional[str] = None, ): super().__init__(name=name) self.dt = dt self.step_fn = predictor_module(coords, dt, physics_specs, aux_features) self.filter_fn = filter_module(coords, dt, physics_specs, aux_features) def __call__( self, state: typing.PyTreeState, tendencies: typing.PyTreeState, forcing: Optional[Forcing] = None, ) -> typing.PyTreeState: state = self.step_fn(state, forcing) euler_add_fn = lambda x, y: x + self.dt * y if y is not None else x result = jax.tree_util.tree_map(euler_add_fn, state, tendencies) return self.filter_fn(state, result) @gin.register class DycoreWithPhysicsCorrector(hk.Module): """Corrector that runs dycore with physics tendencies added to explicit terms. This corrector treats predicted physics tendencies constant at each time interval and includes them to all substeps of the dycore step. To achieve this the dycore in this module is specified by the governing equation, rather than an `EquationStep`. """ def __init__( self, coords: coordinate_systems.CoordinateSystem, dt: float, physics_specs: Any, aux_features: typing.AuxFeatures, dycore_equation_module: EquationModule = gin.REQUIRED, # pyrefly: ignore[bad-function-definition] dycore_substeps: int = gin.REQUIRED, # pyrefly: ignore[bad-function-definition] time_integrator: TimeIntegrator = integrators.imex_rk_sil3, filter_module: StepFilterModule = filters.NoFilter, checkpoint_explicit_terms: bool = True, name: Optional[str] = None, ): super().__init__(name=name) dycore_equation = dycore_equation_module( coords, dt, physics_specs, aux_features) if checkpoint_explicit_terms: dycore_equation = time_integration.ImplicitExplicitODE.from_functions( hk.remat(dycore_equation.explicit_terms), dycore_equation.implicit_terms, dycore_equation.implicit_inverse) # pyrefly: ignore[bad-argument-type] self.coords = coords self.dycore_equation = dycore_equation self.dycore_substeps = dycore_substeps self.inner_dt = dt / dycore_substeps self.dt = dt self.time_integrator = time_integrator self.filter_fn = filter_module(coords, dt, physics_specs, aux_features) def __call__( self, state: typing.PyTreeState, tendencies: typing.PyTreeState, forcing: Optional[Forcing] = None, ) -> typing.PyTreeState: state, tendencies = self.coords.with_dycore_sharding((state, tendencies)) physics_parametrization_eq = time_integration.ExplicitODE.from_functions( lambda state: tendencies) all_equations = (self.dycore_equation, physics_parametrization_eq) equation = time_integration.compose_equations(all_equations) step_fn = self.time_integrator(equation, self.inner_dt) # TODO(dkochkov) make step_with_filters work with single filter. step_fn = time_integration.step_with_filters(step_fn, [self.filter_fn]) step_fn = time_integration.repeated(step_fn, self.dycore_substeps, hk.scan) state = time_integration.maybe_fix_sim_time_roundoff( step_fn(state), self.dt ) state = self.coords.with_dycore_sharding(state) return state @gin.register class CustomCoordsCorrector(hk.Module): """Corrector module that uses gin-configured coordinates instead of coords. This class currently supports model states in spectral representation. It could be easily extended to nodal-state models by converting to modal space prior to spectral interpolation and back after the timestep if performed. """ def __init__( self, coords: coordinate_systems.CoordinateSystem, dt: float, physics_specs: Any, aux_features: typing.AuxFeatures, corrector_module: CorrectorModule = gin.REQUIRED, # pyrefly: ignore[bad-function-definition] custom_coords: coordinate_systems.CoordinateSystem = gin.REQUIRED, # pyrefly: ignore[bad-function-definition] name: Optional[str] = None, ): super().__init__(name=name) custom_coords = dataclasses.replace( custom_coords, spmd_mesh=coords.spmd_mesh ) self.corrector_fn = corrector_module( custom_coords, dt, physics_specs, aux_features) self.to_custom_coords_fn = coordinate_systems.get_spectral_interpolate_fn( coords, custom_coords) self.from_custom_coords_fn = coordinate_systems.get_spectral_interpolate_fn( custom_coords, coords) def __call__( self, state: typing.PyTreeState, tendencies: typing.PyTreeState, forcing: Optional[Forcing] = None, ) -> typing.PyTreeState: state = self.to_custom_coords_fn(state) tendencies = self.to_custom_coords_fn(tendencies) # TODO(dkochkov) Consider adding forcing interpolated to custom coords. custom_out = self.corrector_fn(state, tendencies, None) return self.from_custom_coords_fn(custom_out)