deeplearning/modulus/modulus-sym-v130/_modules/modulus/sym/hydra/config.html

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Source code for modulus.sym.hydra.config

# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved. # # 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 # # http://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. """ Modulus main config """ from platform import architecture import torch import logging from dataclasses import dataclass, field from hydra.core.config_store import ConfigStore from hydra.conf import RunDir, HydraConf from omegaconf import MISSING, SI from typing import List, Any from modulus.sym.constants import JIT_PYTORCH_VERSION from packaging import version from .loss import LossConf from .optimizer import OptimizerConf from .pde import PDEConf from .scheduler import SchedulerConf from .training import TrainingConf, StopCriterionConf from .profiler import ProfilerConf from .hydra import default_hydra logger = logging.getLogger(__name__) 
[docs]@dataclass class ModulusConfig: # General parameters network_dir: str = ”.” initialization_network_dir: str = "" save_filetypes: str = “vtk” summary_histograms: bool = False jit: bool = version.parse(torch.__version__) >= version.parse(JIT_PYTORCH_VERSION) jit_use_nvfuser: bool = True jit_arch_mode: str = “only_activation” jit_autograd_nodes: bool = False cuda_graphs: bool = True cuda_graph_warmup: int = 20 find_unused_parameters: bool = False broadcast_buffers: bool = False device: str = "" debug: bool = False run_mode: str = “train” arch: Any = MISSING models: Any = MISSING # List of models training: TrainingConf = MISSING stop_criterion: StopCriterionConf = MISSING loss: LossConf = MISSING optimizer: OptimizerConf = MISSING scheduler: SchedulerConf = MISSING batch_size: Any = MISSING profiler: ProfilerConf = MISSING hydra: Any = field(default_factory=lambda: default_hydra) # User custom parameters that are not used internally in modulus custom: Any = MISSING

default_defaults = [ {“training”: “default_training”}, {“graph”: “default”}, {“stop_criterion”: “default_stop_criterion”}, {“profiler”: “nvtx”}, {“override hydra/job_logging”: “info_logging”}, {“override hydra/launcher”: “basic”}, {“override hydra/help”: “modulus_help”}, {“override hydra/callbacks”: “default_callback”}, ]

[docs]@dataclass class DefaultModulusConfig(ModulusConfig): # Core defaults # Can over-ride default with “override” hydra command defaults: List[Any] = field(default_factory=lambda: default_defaults)

# Modulus config for debugging debug_defaults = [ {“training”: “default_training”}, {“graph”: “default”}, {“stop_criterion”: “default_stop_criterion”}, {“profiler”: “nvtx”}, {“override hydra/job_logging”: “debug_logging”}, {“override hydra/help”: “modulus_help”}, {“override hydra/callbacks”: “default_callback”}, ]

[docs]@dataclass class DebugModulusConfig(ModulusConfig): # Core defaults # Can over-ride default with “override” hydra command defaults: List[Any] = field(default_factory=lambda: debug_defaults) debug: bool = True

# Modulus config with experimental features (use caution) experimental_defaults = [ {“training”: “default_training”}, {“graph”: “default”}, {“stop_criterion”: “default_stop_criterion”}, {“profiler”: “nvtx”}, {“override hydra/job_logging”: “info_logging”}, {“override hydra/launcher”: “basic”}, {“override hydra/help”: “modulus_help”}, {“override hydra/callbacks”: “default_callback”}, ]

[docs]@dataclass class ExperimentalModulusConfig(ModulusConfig): # Core defaults # Can over-ride default with “override” hydra command defaults: List[Any] = field(default_factory=lambda: experimental_defaults) pde: PDEConf = MISSING
[docs]def register_modulus_configs() -> None: if not torch.__version__ == JIT_PYTORCH_VERSION: logger.warn( f“TorchScript default is being turned off due to PyTorch version mismatch.” ) cs = ConfigStore.instance() cs.store( name=“modulus_default”, node=DefaultModulusConfig, ) cs.store( name=“modulus_debug”, node=DebugModulusConfig, ) cs.store( name=“modulus_experimental”, node=ExperimentalModulusConfig, )
© Copyright 2023, NVIDIA Modulus Team. Last updated on Jan 25, 2024.