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Warn when lazy resampling upcasts non-float input to float32 (#6713) #9044

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7db60a6
Warn when lazy resampling upcasts non-float input to float32 (#6713)
vishnukannaujia Aug 3, 2026
7f081fe
Address review: warn with stacklevel=2, assert input unchanged, fix d…
vishnukannaujia Aug 3, 2026
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7 changes: 7 additions & 0 deletions monai/transforms/lazy/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -192,6 +192,13 @@ def resample(data: torch.Tensor, matrix: NdarrayOrTensor, kwargs: dict | None =
}
ndim = len(matrix) - 1
img = convert_to_tensor(data=data, track_meta=monai.data.get_track_meta())
if not (torch.is_floating_point(img) or torch.is_complex(img)):
warnings.warn(
f"Lazy resampling computes in floating point and converts the input of dtype {img.dtype} to "
"float32; the original data type is not preserved. For integer data such as label maps, set "
"`lazy=False` for the affected transforms (or cast back afterwards) if the data type must be preserved.",
stacklevel=2,
)
Comment on lines +195 to +201

@coderabbitai coderabbitai Bot Aug 3, 2026

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📐 Maintainability & Code Quality | 🟡 Minor | ⚡ Quick win

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
set -euo pipefail

echo "== locate file =="
git ls-files | grep -F 'monai/transforms/lazy/utils.py' || true

echo "== relevant lines =="
sed -n '160,215p' monai/transforms/lazy/utils.py | cat -n

echo "== surrounding function/docs =="
sed -n '1,130p' monai/transforms/lazy/utils.py | cat -n

echo "== imports in file =="
sed -n '1,40p' monai/transforms/lazy/utils.py | cat -n

echo "== warnings usages in file =="
rg -n "warnings\.warn|stacklevel|category=UserWarning|UserWarning" monai/transforms/lazy/utils.py

echo "== ruff availability/config references =="
(git ls-files | grep -E '(^|/)(pyproject\.toml|ruff\.toml|\.ruff\.toml)$' && rg -n '(^tool\.ruff|B028|PERF|warn|stacklevel)' pyproject.toml ruff.toml .ruff.toml 2>/dev/null || true) || true

Repository: Project-MONAI/MONAI

Length of output: 11556

🏁 Script executed:

#!/bin/bash
set -euo pipefail

echo "== resample def and full relevant section =="
rg -n -A 70 -B 20 "^def resample" monai/transforms/lazy/utils.py

echo "== pyproject ruff config =="
sed -n '45,80p' pyproject.toml | cat -n

echo "== Python warnings default stacklevel behavior probe =="
python3 - <<'PY'
import warnings

def f():
    warnings.warn("no stacklevel")
    warnings.warn("with stacklevel=2", stacklevel=2)

try:
    import ruff
except Exception as e:
    print("ruff import unavailable:", type(e).__name__, e)

f()
PY

Repository: Project-MONAI/MONAI

Length of output: 6928

Set an explicit caller-facing warning category and stack level.

warnings.warn defaults to UserWarning, but the dtype-conversion warning should pass it explicitly. Add stacklevel=2 so the message points to the caller instead of this helper.

Proposed fix 
         warnings.warn(
             f"Lazy resampling computes in floating point and converts the input of dtype {img.dtype} to "
-            "float32; the original data type is not preserved. For integer data such as label maps, set "
-            "`lazy=False` for the affected transforms (or cast back afterwards) if the data type must be preserved."
+            "float32; the original data type is not preserved. For integer data such as label maps, set "
+            "`lazy=False` for the affected transforms (or cast back afterwards) if the data type must be preserved.",
+            category=UserWarning,
+            stacklevel=2,
         )
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
if not (torch.is_floating_point(img) or torch.is_complex(img)):
warnings.warn(
f"Lazy resampling computes in floating point and converts the input of dtype {img.dtype} to "
"float32; the original data type is not preserved. For integer data such as label maps, set "
"`lazy=False` for the affected transforms (or cast back afterwards) if the data type must be preserved."
)
if not (torch.is_floating_point(img) or torch.is_complex(img)):
warnings.warn(
f"Lazy resampling computes in floating point and converts the input of dtype {img.dtype} to "
"float32; the original data type is not preserved. For integer data such as label maps, set "
"`lazy=False` for the affected transforms (or cast back afterwards) if the data type must be preserved.",
category=UserWarning,
stacklevel=2,
)
🧰 Tools
🪛 Ruff (0.16.0)

[warning] 196-196: No explicit stacklevel keyword argument found

Set stacklevel=2

(B028)

🤖 Prompt for AI Agents 
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@monai/transforms/lazy/utils.py` around lines 195 - 200, Update the
warnings.warn call in the lazy resampling dtype-check block to explicitly use
UserWarning and set stacklevel=2, preserving the existing warning message and
condition.

Source: Linters/SAST tools

init_affine = monai.data.to_affine_nd(ndim, img.affine)
spatial_size = kwargs.get(LazyAttr.SHAPE, None)
out_spatial_size = img.peek_pending_shape() if spatial_size is None else spatial_size
Expand Down
16 changes: 16 additions & 0 deletions tests/transforms/functional/test_resample.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@
from __future__ import annotations

import unittest
import warnings

import torch
from parameterized import parameterized
Expand Down Expand Up @@ -45,6 +46,21 @@ def test_resample_function_impl(self, img, matrix, expected):
out_1 = resample(img, matrix, {"lazy_resample_mode": "other value", "lazy_dtype": torch.float})
self.assertIs(out.dtype, out_1.dtype) # testing dtype in different lazy_resample_mode

def test_resample_warns_on_non_float_dtype(self):
"""Lazy resampling upcasts non-floating-point inputs to float32; the user should be warned (see issue #6713)."""
img = convert_to_tensor(get_arange_img((3, 3)), dtype=torch.uint8)
with self.assertWarns(Warning):
out = resample(img, torch.eye(3), {"lazy_resample_mode": "auto"})
self.assertIs(out.dtype, torch.float32)
Comment on lines +49 to +54

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🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
set -euo pipefail

# Locate the test file and inspect relevant test/source behavior.
if [ -f tests/transforms/functional/test_resample.py ]; then
  echo "== test file snippet =="
  cat -n tests/transforms/functional/test_resample.py | sed -n '1,100p'
else
  echo "tests/transforms/functional/test_resample.py not found"
  fd -i 'test_resample\.py'
fi

echo "== resample definitions/usages matching warning contract =="
rg -n "resample|lazy_resample_mode|converts the input|UserWarning|Warning" tests/transforms/functional/test_resample.py -S || true

echo "== likely implementation files =="
rg -n "def resample|class .*Resample|lazy_resample_mode|converts the input|UserWarning" -S --glob '*.py' | head -n 120

Repository: Project-MONAI/MONAI

Length of output: 4348

🏁 Script executed:

#!/bin/bash
set -euo pipefail

echo "== candidate files =="
fd -i 'functional\.py$' monai/transforms/lazy || true
fd -i 'lazy.*\.py$' monai/transforms || true
rg -n "def resample\b" --glob '*.py' | head -n 80
echo "== warning strings =="
rg -n "converts the input|dtype torch\.(uint8|float)|dtype .*float32|lazy_dtype|lazy_resample_mode" --glob '*.py' | head -n 200

echo "== inspect candidate implementation =="
while IFS= read -r f; do
  echo "--- $f ---"
  ast-grep outline "$f" --match 'resample' --view expanded || true
  cat -n "$f" | sed -n '1,220p'
done < <(fd -i 'functional\.py$' monai/transforms/lazy)

Repository: Project-MONAI/MONAI

Length of output: 215

🏁 Script executed:

#!/bin/bash
set -euo pipefail

echo "== resample definitions/usages =="
rg -n "def resample\b|class .*Resample|resample\b" --glob '*.py' | head -n 200 || true
echo "== warning strings and lazy options =="
rg -n "converts the input|lazy_dtype|lazy_resample_mode|warn\(|warnings\.warn|UserWarning|Warning" --glob '*.py' | head -n 250 || true

echo "== inspect monai/transforms/lazy/functional.py =="
wc -l monai/transforms/lazy/functional.py
cat -n monai/transforms/lazy/functional.py | sed -n '1,260p'

echo "== Python unittest assertWarns semantics probe =="
python3 - <<'PY'
import warnings, unittest

class Bad(unittest.TestCase):
    def pass_warning(self):
        with warnings.catch_warnings():
            warnings.simplefilter("error")
            with self.assertWarns(Warning):
                warnings.warn("hello", DeprecationWarning)
            with self.assertWarnsRegex(Warning, "hello"):
                warnings.warn("hello", DeprecationWarning)
try:
    Bad().pass_warning()
    print("both accept unrelated warning subtype under current semantics")
except Exception as e:
    print(type(e).__name__, e)
PY

Repository: Project-MONAI/MONAI

Length of output: 191

🏁 Script executed:

#!/bin/bash
set -u

echo "== locate functional.py =="
fd -a 'functional.py$' . | sed 's#^\./##' | grep 'monai/transforms/lazy/functional.py' || true

echo "== resample references =="
rg -n "def resample\b|lazy_dtype|lazy_resample_mode|warnings\.warn|UserWarning|Warning" -S --glob '*.py' . | head -n 300

echo "== inspect monai/transforms/lazy/functional.py =="
if [ -f monai/transforms/lazy/functional.py ]; then
  wc -l monai/transforms/lazy/functional.py
  cat -n monai/transforms/lazy/functional.py | sed -n '1,260p'
else
  echo "monai/transforms/lazy/functional.py missing"
fi

Repository: Project-MONAI/MONAI

Length of output: 47659

🏁 Script executed:

#!/bin/bash
set -u

python3 - <<'PY'
import ast
path = "monai/transforms/lazy/utils.py"
with open(path) as f:
    tree = ast.parse(f.read())

for node in ast.walk(tree):
    if isinstance(node, ast.FunctionDef) and node.name == "resample":
        file = node.lineno; col = node.col_offset
        print(f"resample starts line {file} col {col}")
        print(ast.get_source_segment(open(path).read(), node))
        break
else:
    print("resample function not found")

with open(path) as f:
    for i, line in enumerate(f, start=1):
        if 140 <= i <= 220:
            print(f"{i}: {line.rstrip()}")
PY

Repository: Project-MONAI/MONAI

Length of output: 9441

Assert the warning category and message.

self.assertWarns(Warning) only checks for any Warning subclass, while resample() emits a UserWarning with the dtype conversion message. Use assertWarnsRegex(UserWarning, ...) with a regex that covers the emitted text.

Proposed test change 
-        with self.assertWarns(Warning):
+        with self.assertWarnsRegex(
+            UserWarning, r"converts the input of dtype torch\.uint8 to float32"
+        ):
             out = resample(img, torch.eye(3), {"lazy_resample_mode": "auto"})
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
def test_resample_warns_on_non_float_dtype(self):
"""Lazy resampling upcasts non-floating-point inputs to float32; the user should be warned (see issue #6713)."""
img = convert_to_tensor(get_arange_img((3, 3)), dtype=torch.uint8)
with self.assertWarns(Warning):
out = resample(img, torch.eye(3), {"lazy_resample_mode": "auto"})
self.assertIs(out.dtype, torch.float32)
def test_resample_warns_on_non_float_dtype(self):
"""Lazy resampling upcasts non-floating-point inputs to float32; the user should be warned (see issue `#6713`)."""
img = convert_to_tensor(get_arange_img((3, 3)), dtype=torch.uint8)
with self.assertWarnsRegex(
UserWarning, r"converts the input of dtype torch\.uint8 to float32"
):
out = resample(img, torch.eye(3), {"lazy_resample_mode": "auto"})
self.assertIs(out.dtype, torch.float32)
🤖 Prompt for AI Agents 
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@tests/transforms/functional/test_resample.py` around lines 49 - 54, Update
test_resample_warns_on_non_float_dtype to assert the specific UserWarning
category and match the emitted dtype-conversion message with
assertWarnsRegex(UserWarning, ...), while preserving the existing resample call
and float32 dtype assertion.

Source: Path instructions

self.assertIs(img.dtype, torch.uint8) # the input tensor itself is not mutated

def test_resample_no_warning_for_float_dtype(self):
"""Float32 inputs do not trigger the lazy resampling dtype warning."""
img = convert_to_tensor(get_arange_img((3, 3)), dtype=torch.float32)
Comment thread
coderabbitai[bot] marked this conversation as resolved.
with warnings.catch_warnings():
warnings.simplefilter("error") # turn any warning into an error
resample(img, torch.eye(3), {"lazy_resample_mode": "auto"})


if __name__ == "__main__":
unittest.main()
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