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[OpenVINO backend] Support numpy.logaddexp #21522

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[OpenVINO backend] Support numpy.logaddexp #21522

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6fbaf64
feat: logaddexp for openvino backend
samthakur587 Jul 28, 2025
9c85bd1
feat: rebase with master
samthakur587 Aug 8, 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 @@ -37,7 +37,6 @@ NumpyDtypeTest::test_isinf
NumpyDtypeTest::test_isnan
NumpyDtypeTest::test_isneginf
NumpyDtypeTest::test_linspace
NumpyDtypeTest::test_logaddexp
NumpyDtypeTest::test_logspace
NumpyDtypeTest::test_matmul_
NumpyDtypeTest::test_max
Expand Down Expand Up @@ -96,7 +95,6 @@ NumpyOneInputOpsCorrectnessTest::test_imag
NumpyOneInputOpsCorrectnessTest::test_isfinite
NumpyOneInputOpsCorrectnessTest::test_isinf
NumpyOneInputOpsCorrectnessTest::test_isneginf
NumpyOneInputOpsCorrectnessTest::test_logaddexp
NumpyOneInputOpsCorrectnessTest::test_max
NumpyOneInputOpsCorrectnessTest::test_mean
NumpyOneInputOpsCorrectnessTest::test_median
Expand Down
50 changes: 47 additions & 3 deletions keras/src/backend/openvino/numpy.py
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Expand Up @@ -1031,9 +1031,53 @@ def log2(x):


def logaddexp(x1, x2):
raise NotImplementedError(
"`logaddexp` is not supported with openvino backend"
)
element_type = None
if isinstance(x1, OpenVINOKerasTensor):
element_type = x1.output.get_element_type()
if isinstance(x2, OpenVINOKerasTensor):
element_type = x2.output.get_element_type()
x1 = get_ov_output(x1, element_type)
x2 = get_ov_output(x2, element_type)
x1, x2 = _align_operand_types(x1, x2, "logaddexp()")

if x1.element_type.is_integral() or x2.element_type.is_integral():
float_dtype = OPENVINO_DTYPES[config.floatx()]
if x1.element_type.is_integral():
x1 = ov_opset.convert(x1, float_dtype)
if x2.element_type.is_integral():
x2 = ov_opset.convert(x2, float_dtype)

# Get the output nodes properly
max_val_node = ov_opset.maximum(x1, x2)
max_val = max_val_node.output(0)

# Compute absolute difference
sub_node = ov_opset.subtract(x1, x2)
abs_diff_node = ov_opset.abs(sub_node.output(0))
abs_diff = abs_diff_node.output(0)

# Compute negative absolute difference and its exponential
neg_abs_diff_node = ov_opset.negative(abs_diff)
neg_abs_diff = neg_abs_diff_node.output(0)
exp_neg_abs_node = ov_opset.exp(neg_abs_diff)
exp_neg_abs = exp_neg_abs_node.output(0)

# Get the element type from the node, not the output
element_type = exp_neg_abs_node.get_element_type()
one_node = ov_opset.constant(1, element_type)
one = one_node.output(0)

# Compute log term
one_plus_exp_node = ov_opset.add(one, exp_neg_abs)
one_plus_exp = one_plus_exp_node.output(0)
log_term_node = ov_opset.log(one_plus_exp)
log_term = log_term_node.output(0)

# Final result
result_node = ov_opset.add(max_val, log_term)
result = result_node.output(0)

return OpenVINOKerasTensor(result)


def logical_and(x1, x2):
Expand Down