8000 [BE] Do not use `numpy` in `torch._inductor.codegen.cpp` by malfet · Pull Request #109324 · pytorch/pytorch · GitHub
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[BE] Do not use numpy in torch._inductor.codegen.cpp #109324

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[BE] Do not use numpy in torch._inductor.codegen.cpp #109324

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11 changes: 5 additions & 6 deletions torch/_inductor/codegen/cpp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,6 @@
from copy import copy, deepcopy
from typing import Dict, List

import numpy
import sympy

import torch
Expand Down Expand Up @@ -2155,20 +2154,20 @@ def constant(val, dtype):
# VecKernel override dtype for constant
# Vectorization only support int32/fp32 now
# So if dtype = int64/fp64, we will cast it to int32/fp32 if possible
i32_iinfo = numpy.iinfo(numpy.int32)
i32_iinfo = torch.iinfo(torch.int32)
if (
dtype == torch.int64
and val <= i32_iinfo.max
and val >= i32_iinfo.min
):
opt_ctx.dtype = torch.int32

f32_iinfo = numpy.finfo(numpy.float32)
f32_iinfo = torch.finfo(torch.float32)
if dtype == torch.double:
if (
(val <= f32_iinfo.max and val >= f32_iinfo.min)
or (val == numpy.inf)
or (val == -numpy.inf)
or (val == torch.inf)
or (val == -torch.inf)
):
opt_ctx.dtype = torch.float32

Expand Down Expand Up @@ -2213,7 +2212,7 @@ def can_use_int32():

vars_ranges = {k: ValueRanges(0, v - 1) for k, v in sizes.items()}
if not vars_ranges or len(vars_ranges) != len(free_symbols):
i32_iinfo = numpy.iinfo(numpy.int32)
i32_iinfo = torch.iinfo(torch.int32)
return (
expr.is_number
and expr <= i32_iinfo.max
Expand Down
0