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Numpy support for tensors.
The spec for the npy format can be found in npy-format. The functions from this module can be used to read tensors from npy/npz files or write tensors to these files. A npy file contains a single tensor (unnamed) whereas a npz file can contain multiple named tensors. npz files are also compressed.
These two formats are easy to use in Python using the numpy library.
import numpy as np
x = np.arange(10)
# Write a npy file.
np.save("test.npy", x)
# Read a value from the npy file.
x = np.load("test.npy")
# Write multiple values to a npz file.
values = { "x": x, "x_plus_one": x + 1 }
np.savez("test.npz", **values)
# Load multiple values from a npz file.
values = np.loadz("test.npz")
Structsยง
- Lazy tensor loader.