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[OpenVINO Backend] Support numpy min operation #21168

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Merged
merged 4 commits into from
Apr 24, 2025
Merged

[OpenVINO Backend] Support numpy min operation #21168

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72673c1
Add numpy min for OV Backend
srinjoydutta03 Apr 14, 2025
a21dc25
Add boolean case
srinjoydutta03 Apr 14, 2025
e5839b0
Fix failing tests issue
srinjoydutta03 Apr 15, 2025
218158f
Update implementation
srinjoydutta03 Apr 19, 2025
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3 changes: 1 addition & 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 @@ -35,7 +35,7 @@ NumpyDtypeTest::test_max
NumpyDtypeTest::test_mean
NumpyDtypeTest::test_median
NumpyDtypeTest::test_meshgrid
NumpyDtypeTest::test_min
NumpyDtypeTest::test_minimum_python_types
NumpyDtypeTest::test_moveaxis
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Please add line with NumpyDtypeTest::test_minimum_python_types

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I have added it. Thank you!

NumpyDtypeTest::test_multiply
NumpyDtypeTest::test_nan
Expand Down Expand Up @@ -95,7 +95,6 @@ NumpyOneInputOpsCorrectnessTest::test_max
NumpyOneInputOpsCorrectnessTest::test_mean
NumpyOneInputOpsCorrectnessTest::test_median
NumpyOneInputOpsCorrectnessTest::test_meshgrid
NumpyOneInputOpsCorrectnessTest::test_min
NumpyOneInputOpsCorrectnessTest::test_moveaxis
NumpyOneInputOpsCorrectnessTest::test_nan_to_num
NumpyOneInputOpsCorrectnessTest::test_ndim
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41 changes: 40 additions & 1 deletion keras/src/backend/openvino/numpy.py
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Expand Up @@ -1006,7 +1006,46 @@ def meshgrid(*x, indexing="xy"):


def min(x, axis=None, keepdims=False, initial=None):
raise NotImplementedError("`min` is not supported with openvino backend")
x = get_ov_output(x)
original_type = x.get_element_type()
x_type = original_type
x_shape = x.get_partial_shape().to_shape()

is_bool = x_type == Type.boolean
if is_bool:
x = ov_opset.convert(x, Type.i32).output(0)
x_type = Type.i32

if isinstance(axis, tuple) and len(axis) == 0:
return OpenVINOKerasTensor(x)

if axis is None:
flatten_shape = ov_opset.constant([-1], Type.i32).output(0)
x = ov_opset.reshape(x, flatten_shape, False).output(0)
axis = 0

if isinstance(axis, tuple):
axis = list(axis)

axis_const = ov_opset.constant(axis, Type.i32).output(0)
min_result = ov_opset.reduce_min(x, axis_const, keepdims).output(0)

if initial is not None:
initial_tensor = ov_opset.constant(initial, x_type).output(0)
min_result = ov_opset.minimum(min_result, initial_tensor).output(0)

if keepdims:
result_shape = [1] * len(x_shape)
min_result = ov_opset.reshape(
min_result,
ov_opset.constant(result_shape, Type.i32).output(0),
False,
).output(0)

if is_bool:
min_result = ov_opset.convert(min_result, Type.boolean).output(0)

return OpenVINOKerasTensor(min_result)


def minimum(x1, x2):
Expand Down