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Add math.log2 support #9416

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Merged
sklam merged 4 commits into from
Mar 15, 2024
Merged

Add math.log2 support #9416

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10ec751
Add math.log2 support
guilhermeleobas Feb 2, 2024
314381f
add release notes
guilhermeleobas Feb 2, 2024
10ca4a6
address reviewer comments
guilhermeleobas Feb 16, 2024
a819f10
Fix release notes
guilhermeleobas Feb 16, 2024
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4 changes: 4 additions & 0 deletions docs/upcoming_changes/9416.new_feature.rst
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Original file line number Diff line number Diff line change
@@ -0,0 +1,4 @@
Support math.log2
=================
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Support for ``math.log2`` is added.
1 change: 1 addition & 0 deletions numba/core/typing/mathdecl.py
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Expand Up @@ -14,6 +14,7 @@
@infer_global(math.log)
@infer_global(math.log1p)
@infer_global(math.log10)
@infer_global(math.log2)
@infer_global(math.sin)
@infer_global(math.cos)
@infer_global(math.tan)
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1 change: 1 addition & 0 deletions numba/cpython/mathimpl.py
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Expand Up @@ -176,6 +176,7 @@ def float_impl(context, builder, sig, args):
exp_impl = unary_math_intr(math.exp, 'llvm.exp')
log_impl = unary_math_intr(math.log, 'llvm.log')
log10_impl = unary_math_intr(math.log10, 'llvm.log10')
log2_impl = unary_math_intr(math.log2, 'llvm.log2')

@stuartarchibald stuartarchibald Feb 14, 2024

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Technically this implementation should raise ValueError('math domain error') for input values that are zero or negative, however, what is present is no different to e.g. log10 above which would suffer from the same issue.

@guilhermeleobas guilhermeleobas Feb 16, 2024

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I can tackle this in a follow-up PR if needed.

sin_impl = unary_math_intr(math.sin, 'llvm.sin')
cos_impl = unary_math_intr(math.cos, 'llvm.cos')

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12 changes: 12 additions & 0 deletions numba/tests/test_mathlib.py
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Expand Up @@ -91,6 +91,10 @@ def log10(x):
return math.log10(x)


def log2(x):
return math.log2(x)


def floor(x):
return math.floor(x)

Expand Down Expand Up @@ -285,6 +289,14 @@ def test_log10(self):
x_values = [1, 10, 100, 1000, 100000, 1000000, 0.1, 1.1]
self.run_unary(pyfunc, x_types, x_values)

def test_log2(self):
pyfunc = log2
x_types = [types.int16, types.int32, types.int64,
types.uint16, types.uint32, types.uint64,
types.float32, types.float64]
x_values = [1, 10, 100, 1000, 100000, 1000000, 0.1, 1.1]
self.run_unary(pyfunc, x_types, x_values)

def test_asin(self):
pyfunc = asin
x_types = [types.int16, types.int32, types.int64,
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