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[FRONTEND][RANDOM] Improved backward compatibility of RNG (#438)

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The unsigned int PR definitely improved our RNG. However, it requires
different floating point arithmetics which, means the results are not
bit-wise identical to how they were before. This commit revives backward
compatibility, but we should change it back to the "right" way later.
This commit is contained in:
Philippe Tillet
2022-01-21 18:05:55 -08:00
committed by GitHub
parent 4c97d1ecd7
commit ccf9abe0ba
1 changed files with 12 additions and 2 deletions
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14
python/triton/language/random.py
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@@ -77,13 +77,23 @@ def randint4x(seed, offset, n_rounds: tl.constexpr = N_ROUNDS_DEFAULT):
# rand # rand
# ------------------- # -------------------
# @triton.jit
# def uint32_to_uniform_float(x):
# """
# Numerically stable function to convert a random uint32 into a random float uniformly sampled in [0, 1).
# """
# two_to_the_minus_32: tl.constexpr = 2.328306e-10
# return x * two_to_the_minus_32
@triton.jit @triton.jit
def uint32_to_uniform_float(x): def uint32_to_uniform_float(x):
""" """
Numerically stable function to convert a random uint32 into a random float uniformly sampled in [0, 1). Numerically stable function to convert a random uint32 into a random float uniformly sampled in [0, 1).
""" """
two_to_the_minus_32: tl.constexpr = 2.328306e-10 x = x.to(tl.int32, bitcast=True)
return x * two_to_the_minus_32 max = 4.656613e-10 # = 1/MAX_INT = 1/2147483647.
x = tl.where(x < 0, -x - 1, x)
return x * max
@triton.jit @triton.jit