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[WIP] Batched converter #5231

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[WIP] Batched converter #5231

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281c636
Batch version of convert4qmc
anbenali Mar 30, 2023
2db8c2b
Merge branch 'QMCPACK:develop' into Batched_Converter
anbenali Nov 14, 2024
08aa898
Fix PyscfToqmcpack to handle gpu4pyscf
anbenali Nov 15, 2024
142faed
Making batched version of the code the default version
anbenali Nov 15, 2024
5cd6953
fix
anbenali Nov 15, 2024
bc50d38
fixing conflicts
anbenali Nov 15, 2024
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60 changes: 47 additions & 13 deletions src/QMCTools/PyscfToQmcpack.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,24 @@ def savetoqmcpack(cell,mf,title="Default",kpts=[],kmesh=[],sp_twist=[],weight=1.
from pyscf.pbc import tools
from numpy import empty
import numpy


# Try to import cupy, but set a flag if it's unavailable
try:
import cupy as cp
CUPY_AVAILABLE = True
except ImportError:
CUPY_AVAILABLE = False


def ensure_numpy(arr):
"""
Ensures that the input array is a NumPy array.
If CuPy is available and the array is a CuPy array, it converts it to a NumPy array.
Otherwise, it returns the array unchanged.
"""
if CUPY_AVAILABLE and isinstance(arr, cp.ndarray):
return arr.get() # Convert CuPy array to NumPy
return arr # Return the array as is (if it's already a NumPy array or CuPy is not available)

PBC=False
Gamma=False
Expand All @@ -43,12 +60,12 @@ def savetoqmcpack(cell,mf,title="Default",kpts=[],kmesh=[],sp_twist=[],weight=1.

SizeMode=len(ComputeMode)
for i in range(SizeMode):
if ComputeMode[i] in ("UHF","KUHF","UKS","SymAdaptedUHF","SymAdaptedUKS"):
Restricted=False
if ComputeMode[i] in ("UHF","KUHF","UKS","DFUKS","SymAdaptedUHF","SymAdaptedUKS"):
Restricted=False
if ComputeMode[i]=="pbc":
PBC=True
if Restricted==False:
sys.exit("Unrestricted calculations with PBC not supported (yet) - contact Developers")
PBC=True
if Restricted==False:
sys.exit("Unrestricted calculations with PBC not supported (yet) - contact Developers")

if PBC and len(kpts) == 0:
Gamma=True
Expand Down Expand Up @@ -500,26 +517,43 @@ def order_mo_coef(ll):

GroupParameter.create_dataset("SpinRestricted",(1,),dtype="b1",data=Restricted)
GroupDet=H5_qmcpack.create_group("Super_Twist")

# Now ensure that all elements in mo_coeff are NumPy arrays


if not PBC:
if Restricted==True:
NbAO, NbMO =mo_coeff.shape
if loc_cell.cart==True:
mo_coeff = [ensure_numpy(coeff) for coeff in mo_coeff]
eigenset=GroupDet.create_dataset("eigenset_0",(NbMO,NbAO),dtype="f8",data=order_mo_coef(mo_coeff))
else:
mo_coeff = [ensure_numpy(coeff) for coeff in mo_coeff]
eigenset=GroupDet.create_dataset("eigenset_0",(NbMO,NbAO),dtype="f8",data=list(zip(*mo_coeff)))

mf.mo_energy = ensure_numpy(mf.mo_energy)
eigenvalue=GroupDet.create_dataset("eigenval_0",(1,NbMO),dtype="f8",data=mf.mo_energy)
else:

NbAO, NbMO =mo_coeff[0].shape
mo_coeff0 = [ensure_numpy(coeff) for coeff in mo_coeff[0]]
mo_coeff1 = [ensure_numpy(coeff) for coeff in mo_coeff[1]]

if loc_cell.cart==True:
eigenset_up=GroupDet.create_dataset("eigenset_0",(NbMO,NbAO),dtype="f8",data=order_mo_coef(mo_coeff[0]))
eigenset_dn=GroupDet.create_dataset("eigenset_1",(NbMO,NbAO),dtype="f8",data=order_mo_coef(mo_coeff[1]))
eigenset_up=GroupDet.create_dataset("eigenset_0",(NbMO,NbAO),dtype="f8",data=order_mo_coef(mo_coeff0))
eigenset_dn=GroupDet.create_dataset("eigenset_1",(NbMO,NbAO),dtype="f8",data=order_mo_coef(mo_coeff1))
#eigenset_up=GroupDet.create_dataset("eigenset_0",(NbMO,NbAO),dtype="f8",data=order_mo_coef(mo_coeff[0]))
#eigenset_dn=GroupDet.create_dataset("eigenset_1",(NbMO,NbAO),dtype="f8",data=order_mo_coef(mo_coeff[1]))
else:
eigenset_up=GroupDet.create_dataset("eigenset_0",(NbMO,NbAO),dtype="f8",data=list(zip(*mo_coeff[0])))
eigenset_dn=GroupDet.create_dataset("eigenset_1",(NbMO,NbAO),dtype="f8",data=list(zip(*mo_coeff[1])))

eigenvalue_up=GroupDet.create_dataset("eigenval_0",(1,NbMO),dtype="f8",data=mf.mo_energy[0])
eigenvalue_dn=GroupDet.create_dataset("eigenval_1",(1,NbMO),dtype="f8",data=mf.mo_energy[1])
eigenset_up=GroupDet.create_dataset("eigenset_0",(NbMO,NbAO),dtype="f8",data=list(zip(*mo_coeff0)))
eigenset_dn=GroupDet.create_dataset("eigenset_1",(NbMO,NbAO),dtype="f8",data=list(zip(*mo_coeff1)))
#eigenset_up=GroupDet.create_dataset("eigenset_0",(NbMO,NbAO),dtype="f8",data=list(zip(*mo_coeff[0])))
#eigenset_dn=GroupDet.create_dataset("eigenset_1",(NbMO,NbAO),dtype="f8",data=list(zip(*mo_coeff[1])))

mo_energy0 = ensure_numpy(mf.mo_energy[0])
mo_energy1 = ensure_numpy(mf.mo_energy[1])
eigenvalue_up=GroupDet.create_dataset("eigenval_0",(1,NbMO),dtype="f8",data=mo_energy0)
eigenvalue_dn=GroupDet.create_dataset("eigenval_1",(1,NbMO),dtype="f8",data=mo_energy1)

else:
#Cell Parameters
Expand Down
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