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Setup.py
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Setup.py
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import os
import sys
def install_dependencies(**kwargs):
pytorch_version = kwargs.get("pytorch_version", "1.12.0")
cuda_version = kwargs.get("cuda_version", "11.3")
if pytorch_version == "1.7.1":
torchvision_version = "0.8.2"
torchaudio_version = "0.7.2"
elif pytorch_version == "1.9.0":
torchvision_version = "0.10.0"
torchaudio_version = "0.9.0"
elif pytorch_version == "1.9.1":
torchvision_version = "0.10.1"
torchaudio_version = "0.9.1"
elif pytorch_version == "1.12.0":
torchvision_version = "0.13.0"
torchaudio_version = "0.12.0"
else:
raise ValueError(pytorch_version)
os.system(
"conda install pytorch==%s torchvision==%s torchaudio==%s cudatoolkit=%s -c pytorch" % (
pytorch_version,
torchvision_version,
torchaudio_version,
cuda_version,
)
)
os.system("pip install pandas")
os.system("pip install networkx")
os.system("pip install seaborn")
os.system("pip install progressbar")
os.system("pip install pyshp")
os.system("pip install python-polylabel")
os.system("pip install scikit-learn")
os.system(
"pip install torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://pytorch-geometric.com/whl/torch-%s+cu%s.html" % (
pytorch_version,
cuda_version.replace(".", ""),
)
)
os.system("pip install torch-geometric==2.0.0")
os.system("pip install torch-geometric-temporal")
os.system("pip install tensorflow")
os.system("pip install --upgrade protobuf==3.19.4")
os.system("pip install setuptools==59.5.0")
os.system("pip install geopandas")
def integrate_submodules(**kwargs):
def get_base_dir(model):
return os.sep.join(["Models", "%s_PyTorch" % (model)])
def get_base_import(model):
return get_base_dir(model).replace(os.sep, ".")
def get_bases(model):
return get_base_dir(model), get_base_import(model)
debug = kwargs.get("debug", 0)
# TCN
print("##### Integrating TCN #####")
base_dir, base_import = get_bases("TCN")
path = os.sep.join([base_dir, "TCN", "adding_problem", "model.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from TCN.tcn import", "from %s.TCN.tcn import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
# MTGNN
print("##### Integrating MTGNN #####")
base_dir, base_import = get_bases("MTGNN")
path = os.sep.join([base_dir, "net.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from layer import", "from %s.layer import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
# TGCN
print("##### Integrating TGCN #####")
base_dir, base_import = get_bases("TGCN")
path = os.sep.join([base_dir, "models", "__init__.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from models.", "from %s.models." % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
#
path = os.sep.join([base_dir, "models", "gcn.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace(
"from utils.graph_conv import calculate_laplacian_with_self_loop",
"from %s.utils.graph_conv import calculate_laplacian_with_self_loop" % (base_import)
)
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
#
path = os.sep.join([base_dir, "models", "tgcn.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace(
"from utils.graph_conv import calculate_laplacian_with_self_loop",
"from %s.utils.graph_conv import calculate_laplacian_with_self_loop" % (base_import)
)
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
# DCRNN
print("##### Integrating DCRNN #####")
base_dir, base_import = get_bases("DCRNN")
path = os.sep.join([base_dir, "model", "pytorch", "dcrnn_model.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from model.pytorch.dcrnn_cell import", "from %s.model.pytorch.dcrnn_cell import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
path = os.sep.join([base_dir, "model", "pytorch", "dcrnn_cell.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from lib import", "from %s.lib import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
# AGCRN
print("##### Integrating AGCRN #####")
base_dir, base_import = get_bases("AGCRN")
path = os.sep.join([base_dir, "model", "AGCRN.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from model.AGCRNCell import", "from %s.model.AGCRNCell import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
path = os.sep.join([base_dir, "model", "AGCRNCell.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from model.AGCN import", "from %s.model.AGCN import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
# STGCN
print("##### Integrating STGCN #####")
base_dir, base_import = get_bases("STGCN")
path = os.sep.join([base_dir, "model", "models.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from model import", "from %s.model import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
# ASTGCN/MSTGCN
print("##### Integrating ASTGCN/MSGCN #####")
base_dir, base_import = get_bases("ASTGCN")
path = os.sep.join([base_dir, "model", "ASTGCN_r.py"])
with open(path, "r", encoding="utf8") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from lib.utils import", "from %s.lib.utils import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w", encoding="utf8") as f:
f.write(_)
path = os.sep.join([base_dir, "model", "MSTGCN_r.py"])
with open(path, "r", encoding="utf8") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from lib.utils import", "from %s.lib.utils import" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w", encoding="utf8") as f:
f.write(_)
# StemGNN
print("##### Integrating StemGNN #####")
base_dir, base_import = get_bases("StemGNN")
path = os.sep.join([base_dir, "models", "base_model.py"])
with open(path, "r") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace(
"self.GLUs.append(GLU(self.time_step * 4, self.time_step * self.output_channel))",
"self.GLUs.append(GLU(self.time_step * 3, self.time_step * self.output_channel))"
)
_ = _.replace(
"ffted = torch.rfft(input, 1, onesided=False)",
"ffted = torch.view_as_real(torch.fft.rfft(input, dim=1))"
)
_ = _.replace(
"iffted = torch.irfft(time_step_as_inner, 1, onesided=False)",
"iffted = torch.fft.irfft(torch.view_as_complex(time_step_as_inner), 4, dim=1)"
)
if debug:
print(114*"#")
print(_)
input()
with open(path, "w") as f:
f.write(_)
# GeoMAN
print("##### Integrating GeoMAN #####")
base_dir, base_import = get_bases("GeoMAN")
path = os.sep.join([base_dir, "GeoMAN.py"])
with open(path, "r", encoding="utf8") as f:
_ = f.read()
if debug:
print(_)
_ = _.replace("from utils import Linear", "from %s.utils import Linear" % (base_import))
if debug:
print(114*"#")
print(_)
input()
with open(path, "w", encoding="utf8") as f:
f.write(_)
if __name__ == "__main__":
if len(sys.argv) < 2:
raise ValueError("Missing argument \"mode\" @ argv[1]. Options include [install_dependencies|integrate_submodules]")
mode = sys.argv[1]
if mode == "install_dependencies":
kwargs = {}
if len(sys.argv) > 2: kwargs["pytorch_version"] = sys.argv[2]
if len(sys.argv) > 3: kwargs["cuda_version"] = sys.argv[3]
if len(sys.argv) > 4: kwargs["debug"] = sys.argv[4]
install_dependencies(**kwargs)
elif mode == "integrate_submodules":
kwargs = {}
if len(sys.argv) > 2: kwargs["debug"] = sys.argv[2]
integrate_submodules(**kwargs)
else:
raise ValueError(mode)