deepmd.tf.entrypoints.compress#
Compress a model, which including tabulating the embedding-net.
Functions#
| Compress model. |
Module Contents#
- deepmd.tf.entrypoints.compress.compress(*, input: str, output: str, extrapolate: int, step: float, frequency: str, checkpoint_folder: str, training_script: str, mpi_log: str, log_path: str | None, log_level: int, **kwargs) None[source]#
Compress model.
The table is composed of fifth-order polynomial coefficients and is assembled from two sub-tables. The first table takes the step parameter as the domain’s uniform step size, while the second table takes 10 * step as it’s uniform step size. The range of the first table is automatically detected by the code, while the second table ranges from the first table’s upper boundary(upper) to the extrapolate(parameter) * upper.
- Parameters:
- input
str frozen model file to compress
- output
str compressed model filename
- extrapolate
int scale of model extrapolation
- step
float uniform step size of the tabulation’s first table
- frequency
str frequency of tabulation overflow check
- checkpoint_folder
str trining checkpoint folder for freezing
- training_script
str training script of the input frozen model
- mpi_log
str mpi logging mode for training
- log_path
Optional[str] if speccified log will be written to this file
- log_level
int logging level
- **kwargs
additional arguments
- input