Comparison ops
Unreleased native NuTorch shell reference. Generated by
scripts/gen-ops-reference.ts; every op also documents itself with
torch <op> --help. Tensor operands are native values, not strings.
eq
elementwise equality (returns a Bool tensor)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch eq <t1> <t2>allclose
true if all elements are close (returns a bool)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch allclose <t1> <t2> [--rtol <Float>] [--atol <Float>]sort
sort along —dim (default last); returns values and indices
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch sort <t1> [--dim <Int>] [--descending]gt
elementwise a > b (Bool, broadcasting)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch gt <t1> <t2>lt
elementwise a < b (Bool, broadcasting)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch lt <t1> <t2>ge
elementwise a >= b (Bool, broadcasting)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch ge <t1> <t2>le
elementwise a <= b (Bool, broadcasting)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch le <t1> <t2>ne
elementwise a != b (Bool, broadcasting)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch ne <t1> <t2>logical_and
elementwise logical AND (Bool, broadcasting)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch logical_and <t1> <t2>logical_or
elementwise logical OR (Bool, broadcasting)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch logical_or <t1> <t2>logical_xor
elementwise logical XOR (Bool, broadcasting)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch logical_xor <t1> <t2>isclose
elementwise closeness (Bool; —rtol/—atol)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch isclose <t1> <t2> [--rtol <Float>] [--atol <Float>]isnan
elementwise NaN test (Bool)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch isnan <t1>isinf
elementwise infinity test (Bool)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch isinf <t1>isfinite
elementwise finiteness test (Bool)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch isfinite <t1>isposinf
elementwise +inf test (Bool)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch isposinf <t1>isneginf
elementwise -inf test (Bool)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch isneginf <t1>logical_not
elementwise logical NOT (Bool)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch logical_not <t1>equal
whole-tensor equality (returns a bool)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch equal <t1> <t2>topk
top-k values+indices (—smallest = PyTorch largest=False, a NuTorch-ism)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch topk <t1> <k> [--dim <Int>] [--smallest]argsort
indices that would sort along —dim (default last)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch argsort <t1> [--dim <Int>] [--descending]searchsorted
insertion indices: searchsorted(sorted_seq, values)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch searchsorted <t1> <t2>bucketize
bucket indices: bucketize(values, boundaries)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch bucketize <t1> <t2>msort
sort along the first dimension (values only)
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch msort <t1>unique
sorted unique values
Signature (placeholders describe arguments; this is not a runnable example):
use torch
torch unique <t1>