Low level control over safetensors files

Low level control over safetensors files

Low level control over safetensors files

Details

Allows opening a connection to a safetensors file and query the tensor names, metadata, etc. Opening a connection only reads the file metadata into memory. This allows for more fined grained control over reading.

Public fields

con

the connection object with the file

metadata

an R list containing the metadata header in the file

framework

the framework used to return the tensors

device

the device to where tensors are copied

max_offset

the largest offset boundary that was visited. Mainly used in torch to find the end of the safetensors file.

Methods

Public methods

• safetensors$new()

• safetensors$keys()

• safetensors$get_tensor()

• safetensors$clone()

---

Method new()

Opens the connection with the file

Usage

safetensors$new(path, ..., framework = "torch", device = "cpu")

Arguments

path

Path to the file to load

...

Unused

framework

Framework to load the data into. Currently only torch is supported

device

Device to copy data once loaded

---

Method keys()

Get the keys (tensor names) in the file

Usage

safetensors$keys()

---

Method get_tensor()

Get a tensor from its name

Usage

safetensors$get_tensor(name)

Arguments

name

Name of the tensor to load

---

Method clone()

The objects of this class are cloneable with this method.

Usage

safetensors$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (rlang::is_installed("torch") && torch::torch_is_installed()) {
tensors <- list(x = torch::torch_randn(10, 10))
temp <- tempfile()
safe_save_file(tensors, temp)
f <- safetensors$new(temp)
f$get_tensor("x")
}
#> torch_tensor
#> -1.0069  1.3835 -0.4267  0.9520 -1.1701 -0.1416  1.8651 -0.5533  0.8212  0.5618
#> -0.0693  0.6516 -1.3801  1.1040  0.6986  0.4746 -2.4160 -0.6960 -0.5122  0.0510
#> -0.5953 -1.7474 -0.0464 -2.9962  1.7087  0.0263 -1.6959 -0.5752  1.0939 -0.6676
#> -0.9730  0.0677  2.3533 -0.7038 -0.3961 -0.8484 -0.0824  1.8545 -0.0144  2.4188
#> -2.1679 -0.0730 -0.6888  1.4964 -0.3781 -0.5696  0.2817 -1.5948 -0.5050 -0.6034
#>  0.9729 -0.2263  1.1841 -1.1103 -0.4616  0.2582 -1.1055 -0.8074  0.1076  0.2405
#> -0.3871  0.6849  0.8837 -0.3960 -0.0671 -0.5247 -1.0028 -0.1707  0.8143 -0.5429
#>  0.7049 -0.8462 -0.3540 -0.0198 -0.9670  1.0882 -0.0433 -0.3659  1.1965  1.0966
#> -2.9764 -0.0494 -1.5416 -0.0517  0.0758 -0.3580  0.2868  0.6684  0.9559  0.1280
#>  0.7369  1.7290 -1.2192 -1.7569  0.9882  0.5809 -2.3600  0.3209 -0.6417  0.6386
#> [ CPUFloatType{10,10} ]