Closed Linux-cpp-lisp closed 2 months ago
GraphModel
model_dtype
BATCH_PTR_KEY
AtomicDataDict
AtomicInMemoryDataset.rdf()
examples/rdf.py
type_to_chemical_symbol
nequip-evaluate --output-fields-from-original-dataset
dataset_*_absmax
HDF5Dataset
include_file_as_baseline_config
nequip-deploy --using-dataset
start_of_epoch_callbacks
nequip.train.callbacks.loss_schedule.SimpleLossSchedule
nequip-deploy build --checkpoint
--override
NEQUIP_MATSCIPY_NL
seed
dataset_seed
silu
e
tanh
o
shuffle
default_dtype
float64
float32
allow_tf32: true
nequip-benchmark
--n-data
StressForceOutput
ForceOutput
edge_energy
ALL_ENERGY_KEYS
wandb>=0.13.8
load_model_state
fixed_fields
npz_fixed_field_keys
NequIP
_params
optimizer_params
optimizer_kwargs
per_species_rescale_arguments_in_dataset_units
[0.6.0] - 2024-5-10
Added
GraphModel
top-level modulemodel_dtype
BATCH_PTR_KEY
inAtomicDataDict
AtomicInMemoryDataset.rdf()
andexamples/rdf.py
type_to_chemical_symbol
nequip-evaluate --output-fields-from-original-dataset
dataset_*_absmax
statistics optionHDF5Dataset
(#227)include_file_as_baseline_config
for simple modifications of existing configsnequip-deploy --using-dataset
to support data-dependent deployment stepsstart_of_epoch_callbacks
nequip.train.callbacks.loss_schedule.SimpleLossSchedule
for changing the loss coefficients at specified epochsnequip-deploy build --checkpoint
and--override
to avoid many largely duplicated YAML filesNEQUIP_MATSCIPY_NL
environment variableChanged
seed
dataset_seed
toseed
if it is not explicitly providedsilu
(e
) andtanh
(o
)shuffle
option is unchanged)default_dtype
defaults tofloat64
(model_dtype
defaultfloat32
,allow_tf32: true
by default--- see https://arxiv.org/abs/2304.10061)nequip-benchmark
now only uses--n-data
frames to build the modelStressForceOutput
, notForceOutput
edge_energy
toALL_ENERGY_KEYS
subjecting it to global rescaleFixed
wandb>=0.13.8
load_model_state
GPU -> CPURemoved
fixed_fields
machinery (npz_fixed_field_keys
is still supported, but through a more straightforward implementation)NequIP
, they must now always be provided explicitly_params
as an allowable subconfiguration suffix (i.e. instead ofoptimizer_params
now onlyoptimizer_kwargs
is valid, not both)per_species_rescale_arguments_in_dataset_units