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Makefile
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###################
# General setting #
###################
# Global settings
CUDA = cu111 # CUDA version 11.1
PYTHON ?= poetry run python3
RUN = poetry run
PIP = pip3
RM = rm -rf
# User settings
DEVICE_ID = 0
#################
# Model setting #
#################
# # Setting for FluxGNN
CD_FLUXGNN_INPUT_YAML ?= inputs/convection_diffusion/fluxgnn/fluxgnn.yml
CD_FLUXGNN_PRETRAINED_MODEL ?= data/pretrained/convection_diffusion/fluxgnn
MIXTURE_FLUXGNN_STEP ?= 4 # 2, 4
MIXTURE_FLUXGNN_NODE ?= 8 # 8, 16, 32, 64
MIXTURE_FLUXGNN_REP ?= 4 # 2, 4, 8
MIXTURE_FLUXGNN_PRETRAINED_MODEL ?= data/pretrained/mixture/fluxgnn_step4_n8_rep4
# # Setting for FVM
CD_FV_INPUT_YAML ?= inputs/convection_diffusion/fv/fv.yml
MIXTURE_FVM_UREP ?= 32 # 4, 8, 16, 32, 64, 128
MIXTURE_FVM_AREP ?= 4 # 4, 8, 16, 32, 64, 128
# # Setting for PENN
PENN_N_NODE ?= 32 # 4 8 16 32 64 128
PENN_REP ?= 4 # 4 8 16
MIXTURE_PENN_PRETRAINED_MODEL ?= data/pretrained/mixture/penn_n32_rep4
# # Setting for MP-PDE
MPPDE_TW ?= 4 # 2 4 8
MPPDE_HIDDEN_FEATURES ?= 128 # 32 64 128
MPPDE_NEIGHBORS ?= 4 # 4 8 16
MIXTURE_MPPDE_PRETRAINED_MODEL ?= data/pretrained/mixture/mppde_f128_n4_tw4
################
# Installation #
################
install: libs
-$(PYTHON) -m pip uninstall -y MP-Neural-PDE-Solvers
make -C MP-Neural-PDE-Solvers install
libs: poetry
-$(PYTHON) -m pip uninstall -y pysiml
$(PYTHON) -m pip install lib/siml/dist/pysiml-*.whl
$(PYTHON) -m pip install pytest
poetry:
cd lib/siml && poetry build --format=wheel && cd ../..
poetry config virtualenvs.create true
poetry config virtualenvs.in-project true
-$(PYTHON) -m pip uninstall -y torch torch-scatter torch-sparse torch-geometric
-$(PYTHON) -m pip uninstall -y fluxgnn
poetry install
poetry run python3 -m pip install torch==1.9.1+cu111 --extra-index-url https://download.pytorch.org/whl/cu111
################################
# Convection-diffusion dataset #
################################
cd_fluxgnn_train:
$(PYTHON) experiments/run.py train \
$(CD_FLUXGNN_INPUT_YAML)
cd_fluxgnn_eval:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py eval \
$(CD_FLUXGNN_PRETRAINED_MODEL) -g -1
cd_fvm_eval:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py fv \
$(CD_FV_INPUT_YAML) -g -1
###################
# Mixture dataset #
###################
## Ours
mixture_fluxgnn_train:
$(PYTHON) experiments/run.py train \
inputs/mixture/fluxgnn/fluxgnn_step$(MIXTURE_FLUXGNN_STEP)_n$(MIXTURE_FLUXGNN_NODE)_rep$(MIXTURE_FLUXGNN_REP).yml
mixture_fluxgnn_eval: \
mixture_fluxgnn_eval_ref \
mixture_fluxgnn_eval_rotation \
mixture_fluxgnn_eval_scaling \
mixture_fluxgnn_eval_taller
mixture_fluxgnn_eval_ref:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py eval \
$(MIXTURE_FLUXGNN_PRETRAINED_MODEL) -g -1
mixture_fluxgnn_eval_rotation:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py eval \
$(MIXTURE_FLUXGNN_PRETRAINED_MODEL) -g -1 \
-d data/mixture/transformed/raw/test/rotation/h* \
-n rotation
mixture_fluxgnn_eval_scaling:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py eval \
$(MIXTURE_FLUXGNN_PRETRAINED_MODEL) -g -1 \
-d data/mixture/transformed/raw/test/scaling/h* \
-n scaling
mixture_fluxgnn_eval_taller:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py eval \
$(MIXTURE_FLUXGNN_PRETRAINED_MODEL) -g -1 \
-d data/mixture/taller/raw/h* \
-n taller
## FVM
mixture_fvm_eval: \
mixture_fvm_eval_ref \
mixture_fvm_eval_rotation \
mixture_fvm_eval_scaling \
mixture_fvm_eval_taller
mixture_fvm_eval_ref:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py fv \
inputs/mixture/fv/fv_urep$(MIXTURE_FVM_UREP)_arep$(MIXTURE_FVM_AREP).yml \
-g -1
mixture_fvm_eval_rotation:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py fv \
inputs/mixture/fv/fv_urep$(MIXTURE_FVM_UREP)_arep$(MIXTURE_FVM_AREP).yml \
-g -1 \
-d data/mixture/transformed/raw/test/rotation/h* \
-n rotation
mixture_fvm_eval_scaling:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py fv \
inputs/mixture/fv/fv_urep$(MIXTURE_FVM_UREP)_arep$(MIXTURE_FVM_AREP).yml \
-g -1 \
-d data/mixture/transformed/raw/test/scaling/h* \
-n scaling
mixture_fvm_eval_taller:
OMP_NUM_THREADS=1 $(PYTHON) experiments/run.py fv \
inputs/mixture/fv/fv_urep$(MIXTURE_FVM_UREP)_arep$(MIXTURE_FVM_AREP).yml \
-g -1 \
-d data/mixture/taller/raw/h* \
-n taller
## PENN (Horie+ NeurIPS 2022)
mixture_penn_train:
$(PYTHON) penn/train.py \
inputs/mixture/penn/penn_n$(strip $(PENN_N_NODE))_rep$(strip $(PENN_REP)).yml \
-g $(DEVICE_ID) -c true \
-o results/mixture/penn/models/penn_n$(strip $(PENN_N_NODE))_rep$(strip $(PENN_REP))
mixture_penn_eval: \
mixture_penn_eval_ref \
mixture_penn_eval_rotation \
mixture_penn_eval_scaling \
mixture_penn_eval_taller
mixture_penn_eval_ref:
OMP_NUM_THREADS=1 $(PYTHON) penn/eval.py \
$(MIXTURE_PENN_PRETRAINED_MODEL) \
data/mixture/preprocessed/test \
-b results/mixture/penn/predictions \
-p data/mixture/preprocessed/preprocessors.pkl \
-w data/mixture/interim \
-a mixture \
-e 32
mixture_penn_eval_rotation:
OMP_NUM_THREADS=1 $(PYTHON) penn/eval.py \
$(MIXTURE_PENN_PRETRAINED_MODEL) \
data/mixture/transformed/preprocessed/test/rotation \
-b results/mixture/penn/predictions \
-p data/mixture/preprocessed/preprocessors.pkl \
-w data/mixture/transformed/interim \
-a mixture \
-e 32
mixture_penn_eval_scaling:
OMP_NUM_THREADS=1 $(PYTHON) penn/eval.py \
$(MIXTURE_PENN_PRETRAINED_MODEL) \
data/mixture/transformed/preprocessed/test/scaling \
-b results/mixture/penn/predictions \
-p data/mixture/preprocessed/preprocessors.pkl \
-w data/mixture/transformed/interim \
-a mixture \
-e 32
mixture_penn_eval_taller:
OMP_NUM_THREADS=1 $(PYTHON) penn/eval.py \
$(MIXTURE_PENN_PRETRAINED_MODEL) \
data/mixture/taller/preprocessed \
-b results/mixture/penn/predictions \
-p data/mixture/preprocessed/preprocessors.pkl \
-w data/mixture/taller/interim \
-a mixture \
-e 32
## MP-PDE (Brandstetter+ ICLR 2022)
mixture_mppde_train:
make -C MP-Neural-PDE-Solvers train_tw$(strip $(MPPDE_TW)) \
NEIGHBORS=$(strip $(MPPDE_NEIGHBORS)) \
HIDDEN_FEATURES=$(strip $(MPPDE_HIDDEN_FEATURES))
mixture_mppde_eval: \
mixture_mppde_eval_ref \
mixture_mppde_eval_rotation \
mixture_mppde_eval_scaling \
mixture_mppde_eval_taller
mixture_mppde_eval_ref:
OMP_NUM_THREADS=1 make -C MP-Neural-PDE-Solvers eval_tw$(strip $(MPPDE_TW)) \
SAVE_DIRECTORY=../results/mixture/mppde/$(notdir $(MIXTURE_MPPDE_PRETRAINED_MODEL)) \
MODEL_PATH=../$(MIXTURE_MPPDE_PRETRAINED_MODEL)/model.pt \
NEIGHBORS=$(strip $(MPPDE_NEIGHBORS)) \
HIDDEN_FEATURES=$(strip $(MPPDE_HIDDEN_FEATURES))
$(PYTHON) experiments/generate_vtu.py \
results/mixture/mppde/$(notdir $(MIXTURE_MPPDE_PRETRAINED_MODEL)) \
data/mixture/interim \
-p data/mixture/preprocessed/preprocessors.pkl \
-f true
mixture_mppde_eval_rotation:
OMP_NUM_THREADS=1 make -C MP-Neural-PDE-Solvers eval_tw$(MPPDE_TW) \
SAVE_DIRECTORY=../results/mixture/mppde/rotation/$(notdir $(MIXTURE_MPPDE_PRETRAINED_MODEL)) \
MODEL_PATH=../$(MIXTURE_MPPDE_PRETRAINED_MODEL)/model.pt \
NEIGHBORS=$(strip $(MPPDE_NEIGHBORS)) \
HIDDEN_FEATURES=$(MPPDE_HIDDEN_FEATURES) \
DATA_TYPE=rotation
$(PYTHON) experiments/generate_vtu.py \
results/mixture/mppde/rotation/$(notdir $(MIXTURE_MPPDE_PRETRAINED_MODEL)) \
data/mixture/transformed/interim/test \
-p data/mixture/preprocessed/preprocessors.pkl \
-f true
mixture_mppde_eval_scaling:
OMP_NUM_THREADS=1 make -C MP-Neural-PDE-Solvers eval_tw$(MPPDE_TW) \
SAVE_DIRECTORY=../results/mixture/mppde/scaling/$(notdir $(MIXTURE_MPPDE_PRETRAINED_MODEL)) \
MODEL_PATH=../$(MIXTURE_MPPDE_PRETRAINED_MODEL)/model.pt \
NEIGHBORS=$(strip $(MPPDE_NEIGHBORS)) \
HIDDEN_FEATURES=$(MPPDE_HIDDEN_FEATURES) \
DATA_TYPE=scaling
$(PYTHON) experiments/generate_vtu.py \
results/mixture/mppde/scaling/$(notdir $(MIXTURE_MPPDE_PRETRAINED_MODEL)) \
data/mixture/transformed/interim/test \
-p data/mixture/preprocessed/preprocessors.pkl \
-f true
mixture_mppde_eval_taller:
OMP_NUM_THREADS=1 make -C MP-Neural-PDE-Solvers eval_tw$(MPPDE_TW) \
SAVE_DIRECTORY=../results/mixture/mppde/taller/$(notdir $(MIXTURE_MPPDE_PRETRAINED_MODEL)) \
MODEL_PATH=../$(MIXTURE_MPPDE_PRETRAINED_MODEL)/model.pt \
NEIGHBORS=$(strip $(MPPDE_NEIGHBORS)) \
HIDDEN_FEATURES=$(MPPDE_HIDDEN_FEATURES) \
DATA_TYPE=taller
$(PYTHON) experiments/generate_vtu.py \
results/mixture/mppde/taller/$(notdir $(MIXTURE_MPPDE_PRETRAINED_MODEL)) \
data/mixture/taller/interim \
-p data/mixture/preprocessed/preprocessors.pkl \
-f true
########
# Test #
########
test_cd_fluxgnn_train:
$(PYTHON) experiments/run.py train \
tests/cd/fluxgnn.yml -g -1
test_mixture_fluxgnn_train:
$(PYTHON) experiments/run.py train \
tests/mixture/fluxgnn.yml -g -1
########
# Misc #
########
clean:
find . -type f -name "*.py[co]" -delete
find . -type d -name "__pycache__" -delete
## Delete all data
delete_all_data: clean
$(RM) data/convection_diffusion/data/*
$(RM) data/mixture/data/*