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Support numpy.moveaxis operation #21189

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Support numpy.moveaxis operation #21189

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1165964
fixed test_moveaxis
Prabha14039 Apr 20, 2025
4a074a0
removed axis.insert[]
Prabha14039 Apr 21, 2025
8e8bdc5
reverted changes
Prabha14039 Apr 21, 2025
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2 changes: 0 additions & 2 deletions keras/src/backend/openvino/excluded_concrete_tests.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,6 @@ NumpyDtypeTest::test_mean
NumpyDtypeTest::test_median
NumpyDtypeTest::test_meshgrid
NumpyDtypeTest::test_min
NumpyDtypeTest::test_moveaxis
NumpyDtypeTest::test_multiply
NumpyDtypeTest::test_nan
NumpyDtypeTest::test_outer_
Expand Down Expand Up @@ -95,7 +94,6 @@ NumpyOneInputOpsCorrectnessTest::test_mean
NumpyOneInputOpsCorrectnessTest::test_median
NumpyOneInputOpsCorrectnessTest::test_meshgrid
NumpyOneInputOpsCorrectnessTest::test_min
NumpyOneInputOpsCorrectnessTest::test_moveaxis
NumpyOneInputOpsCorrectnessTest::test_nan_to_num
NumpyOneInputOpsCorrectnessTest::test_pad_float16_constant_2
NumpyOneInputOpsCorrectnessTest::test_pad_float32_constant_2
Expand Down
34 changes: 31 additions & 3 deletions keras/src/backend/openvino/numpy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1024,9 +1024,37 @@ def mod(x1, x2):


def moveaxis(x, source, destination):
raise NotImplementedError(
"`moveaxis` is not supported with openvino backend"
)
if isinstance(source, int):
source = [source]
if isinstance(destination, int):
destination = [destination]

x = get_ov_output(x)
x_shape = x.get_partial_shape()
rank = x_shape.rank.get_length()

source = [s + rank if s < 0 else s for s in source]
destination = [d + rank if d < 0 else d for d in destination]

axes = list(range(rank))

for axis in sorted(source, reverse=True):
axes.pop(axis)

for dest, src in sorted(zip(destination, source)):
axes.insert(dest, src)
Comment on lines +1041 to +1045
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@rkazants rkazants Apr 21, 2025 •
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I think it is more clear to code this as:

for dest, src in sorted(zip(destination, source)):
    axes[dest] = src

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i dont think we can do this because this results in broken permuation
as this assumes axes already has the correct length

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Can you share a concrete example that shows it will not work?

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image

This is happening because the following code assumes that the index is of equal length
but after popping the elements the length is not the same hence it results in index error if dest >= len(axes)

def moveaxis(x, source, destination):

    if isinstance(source, int):
        source = [source]
    if isinstance(destination, int):
        destination = [destination]

    x = get_ov_output(x)
    x_shape = x.get_partial_shape()
    rank = x_shape.rank.get_length()

    source = [s + rank if s < 0 else s for s in source]
    destination = [d + rank if d < 0 else d for d in destination]

    axes = list(range(rank))

    for axis in sorted(source, reverse=True):
        axes.pop(axis)

    for dest, src in sorted(zip(destination, source)):
        axes[dest] = src

    perm = ov_opset.constant(axes, dtype=Type.i32).output(0)

    x_type = x.get_element_type()
    if x_type == Type.bf16:
        x = ov_opset.convert(x, Type.f32).output(0)
        result = ov_opset.transpose(x, perm).output(0)
        return OpenVINOKerasTensor(
            ov_opset.convert(result, Type.bf16).output(0)
        )

    return OpenVINOKerasTensor(ov_opset.transpose(x, perm).output(0))

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@Prabha14039, once again. Share with me a concrete example with concrete values source and destination for which my code willn't work.

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i apologise here is the test case failing
image

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you need to remove as well:
{BB02C2C5-31A5-4E32-8BED-46BC31665DA8}

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image

i am facing the following issue after removing the axes.pop

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Here I don't see source and destination values. Please create standlalone code that proves my code does not work.

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@Prabha14039, any update on my latest comment? Thanks!


perm = ov_opset.constant(axes, dtype=Type.i32).output(0)

x_type = x.get_element_type()
if x_type == Type.bf16:
x = ov_opset.convert(x, Type.f32).output(0)
result = ov_opset.transpose(x, perm).output(0)
return OpenVINOKerasTensor(
ov_opset.convert(result, Type.bf16).output(0)
)

return OpenVINOKerasTensor(ov_opset.transpose(x, perm).output(0))


def nan_to_num(x, nan=0.0, posinf=None, neginf=None):
Expand Down