From 0f77687483e78bdb599fae90dbb2c3c13640afae Mon Sep 17 00:00:00 2001
From: arjunverma2004 <163740749+arjunverma2004@users.noreply.github.com>
Date: Fri, 15 Aug 2025 14:41:32 +0530
Subject: [PATCH 1/8] [OpenVINO backend] Support numpy.diagonal issue 29115

---
 .../openvino/excluded_concrete_tests.txt      |  1 -
 keras/src/backend/openvino/numpy.py           | 72 +++++++++++++++++++
 2 files changed, 72 insertions(+), 1 deletion(-)

diff --git a/keras/src/backend/openvino/excluded_concrete_tests.txt b/keras/src/backend/openvino/excluded_concrete_tests.txt
index b89a56260802..4ef116fcc6a4 100644
--- a/keras/src/backend/openvino/excluded_concrete_tests.txt
+++ b/keras/src/backend/openvino/excluded_concrete_tests.txt
@@ -86,7 +86,6 @@ NumpyOneInputOpsCorrectnessTest::test_corrcoef
 NumpyOneInputOpsCorrectnessTest::test_correlate
 NumpyOneInputOpsCorrectnessTest::test_cumprod
 NumpyOneInputOpsCorrectnessTest::test_diag
-NumpyOneInputOpsCorrectnessTest::test_diagonal
 NumpyOneInputOpsCorrectnessTest::test_exp2
 NumpyOneInputOpsCorrectnessTest::test_flip
 NumpyOneInputOpsCorrectnessTest::test_floor_divide
diff --git a/keras/src/backend/openvino/numpy.py b/keras/src/backend/openvino/numpy.py
index 8b3c5e0b5a96..345cae4470ad 100644
--- a/keras/src/backend/openvino/numpy.py
+++ b/keras/src/backend/openvino/numpy.py
@@ -15,6 +15,78 @@
 from keras.src.backend.openvino.core import convert_to_tensor
 from keras.src.backend.openvino.core import get_ov_output
 from keras.src.backend.openvino.core import ov_to_keras_type
+# --- Chnage for issue 29115 ---
+import openvino.runtime.opset14 as ov
+
+from .core import OpenVINOKerasTensor  # already present in file
+from .core import _convert_to_node, _wrap_node  # adapt if your file names differ
+
+def diagonal(x, offset=0, axis1=0, axis2=1):
+    """OpenVINO backend decomposition for keras.ops.diagonal."""
+    x_node = _convert_to_node(x)  # -> ov.Node
+    offset_const = ov.constant(int(offset), dtype="i64")
+
+    # rank & normalize axes
+    shape = ov.shape_of(x_node)                       # i64 vector
+    rank = ov.shape_of(shape)                         # scalar i64 (len of shape)
+    rank_val = ov.squeeze(rank)                       # [] -> scalar
+    axis1_node = ov.mod(ov.add(ov.constant(int(axis1), dtype="i64"), rank_val), rank_val)
+    axis2_node = ov.mod(ov.add(ov.constant(int(axis2), dtype="i64"), rank_val), rank_val)
+
+    # If axis1 == axis2, behavior should match numpy error; Keras tests don't hit this,
+    # so we skip explicit assert to keep graph-friendly.
+
+    # Build permutation to move axis1, axis2 to the end
+    # perm = [all axes except axis1/axis2 in order] + [axis1, axis2]
+    arange = ov.range(ov.constant(0, dtype="i64"), rank_val, ov.constant(1, dtype="i64"))
+    mask1 = ov.equal(arange, axis1_node)
+    mask2 = ov.equal(arange, axis2_node)
+    not12 = ov.logical_not(ov.logical_or(mask1, mask2))
+    others = ov.squeeze(ov.non_zero(not12), [1])  # gather positions != axis1, axis2
+    perm = ov.concat([others, ov.reshape(axis1_node, [1]), ov.reshape(axis2_node, [1])], 0)
+
+    x_perm = ov.transpose(x_node, perm)
+    permuted_shape = ov.shape_of(x_perm)
+    # last two dims
+    last2 = ov.gather(permuted_shape, ov.constant([-2, -1], dtype="i64"), ov.constant(0, dtype="i64"))
+    d1 = ov.gather(permuted_shape, ov.constant([-2], dtype="i64"), ov.constant(0, dtype="i64"))
+    d2 = ov.gather(permuted_shape, ov.constant([-1], dtype="i64"), ov.constant(0, dtype="i64"))
+    d1 = ov.squeeze(d1)  # scalar
+    d2 = ov.squeeze(d2)  # scalar
+
+    # start1 = max(0, offset), start2 = max(0, -offset)
+    zero = ov.constant(0, dtype="i64")
+    start1 = ov.maximum(zero, offset_const)
+    start2 = ov.maximum(zero, ov.negative(offset_const))
+
+    # L = min(d1 - start1, d2 - start2)
+    l1 = ov.subtract(d1, start1)
+    l2 = ov.subtract(d2, start2)
+    L = ov.minimum(l1, l2)
+
+    # r = range(0, L, 1)  -> shape [L]
+    r = ov.range(zero, L, ov.constant(1, dtype="i64"))
+    idx_row = ov.add(r, start1)
+    idx_col = ov.add(r, start2)
+    idx_row = ov.unsqueeze(idx_row, ov.constant(1, dtype="i64"))  # [L,1]
+    idx_col = ov.unsqueeze(idx_col, ov.constant(1, dtype="i64"))  # [L,1]
+    diag_idx = ov.concat([idx_row, idx_col], 1)  # [L,2]
+
+    # Broadcast indices to batch dims: target shape = (*batch, L, 2)
+    # batch_rank = rank(x) - 2
+    two = ov.constant(2, dtype="i64")
+    batch_rank = ov.subtract(rank_val, two)
+    # build target shape: concat(permuted_shape[:batch_rank], [L, 2])
+    batch_shape = ov.slice(permuted_shape, ov.constant([0], dtype="i64"),
+                           ov.reshape(batch_rank, [1]), ov.constant([1], dtype="i64"))
+    target_shape = ov.concat([batch_shape, ov.reshape(L, [1]), ov.constant([2], dtype="i64")], 0)
+    bcast_idx = ov.broadcast(diag_idx, target_shape)
+
+    # GatherND with batch_dims = batch_rank
+    gathered = ov.gather_nd(x_perm, bcast_idx, batch_rank)
+
+    return OpenVINOKerasTensor(gathered)
+
 
 
 def add(x1, x2):

From ea0a40fa6be565afc5eca5c3a6516e0b23efdcad Mon Sep 17 00:00:00 2001
From: arjunverma2004 <163740749+arjunverma2004@users.noreply.github.com>
Date: Fri, 15 Aug 2025 14:58:24 +0530
Subject: [PATCH 2/8] gmni comit

---
 keras/src/backend/openvino/numpy.py | 114 +++++++++++++++++-----------
 1 file changed, 69 insertions(+), 45 deletions(-)

diff --git a/keras/src/backend/openvino/numpy.py b/keras/src/backend/openvino/numpy.py
index 345cae4470ad..c4b70c253439 100644
--- a/keras/src/backend/openvino/numpy.py
+++ b/keras/src/backend/openvino/numpy.py
@@ -15,75 +15,99 @@
 from keras.src.backend.openvino.core import convert_to_tensor
 from keras.src.backend.openvino.core import get_ov_output
 from keras.src.backend.openvino.core import ov_to_keras_type
-# --- Chnage for issue 29115 ---
-import openvino.runtime.opset14 as ov
-
-from .core import OpenVINOKerasTensor  # already present in file
-from .core import _convert_to_node, _wrap_node  # adapt if your file names differ
+from .core import _convert_to_node
 
 def diagonal(x, offset=0, axis1=0, axis2=1):
     """OpenVINO backend decomposition for keras.ops.diagonal."""
     x_node = _convert_to_node(x)  # -> ov.Node
-    offset_const = ov.constant(int(offset), dtype="i64")
+    offset_const = ov_opset.constant(int(offset), dtype="i64")
 
     # rank & normalize axes
-    shape = ov.shape_of(x_node)                       # i64 vector
-    rank = ov.shape_of(shape)                         # scalar i64 (len of shape)
-    rank_val = ov.squeeze(rank)                       # [] -> scalar
-    axis1_node = ov.mod(ov.add(ov.constant(int(axis1), dtype="i64"), rank_val), rank_val)
-    axis2_node = ov.mod(ov.add(ov.constant(int(axis2), dtype="i64"), rank_val), rank_val)
+    shape = ov_opset.shape_of(x_node)  # i64 vector
+    rank = ov_opset.shape_of(shape)  # scalar i64 (len of shape)
+    rank_val = ov_opset.squeeze(rank)  # [] -> scalar
+    axis1_node = ov_opset.floor_mod(
+        ov_opset.add(ov_opset.constant(int(axis1), dtype="i64"), rank_val), rank_val
+    )
+    axis2_node = ov_opset.floor_mod(
+        ov_opset.add(ov_opset.constant(int(axis2), dtype="i64"), rank_val), rank_val
+    )
 
     # If axis1 == axis2, behavior should match numpy error; Keras tests don't hit this,
     # so we skip explicit assert to keep graph-friendly.
 
     # Build permutation to move axis1, axis2 to the end
     # perm = [all axes except axis1/axis2 in order] + [axis1, axis2]
-    arange = ov.range(ov.constant(0, dtype="i64"), rank_val, ov.constant(1, dtype="i64"))
-    mask1 = ov.equal(arange, axis1_node)
-    mask2 = ov.equal(arange, axis2_node)
-    not12 = ov.logical_not(ov.logical_or(mask1, mask2))
-    others = ov.squeeze(ov.non_zero(not12), [1])  # gather positions != axis1, axis2
-    perm = ov.concat([others, ov.reshape(axis1_node, [1]), ov.reshape(axis2_node, [1])], 0)
-
-    x_perm = ov.transpose(x_node, perm)
-    permuted_shape = ov.shape_of(x_perm)
-    # last two dims
-    last2 = ov.gather(permuted_shape, ov.constant([-2, -1], dtype="i64"), ov.constant(0, dtype="i64"))
-    d1 = ov.gather(permuted_shape, ov.constant([-2], dtype="i64"), ov.constant(0, dtype="i64"))
-    d2 = ov.gather(permuted_shape, ov.constant([-1], dtype="i64"), ov.constant(0, dtype="i64"))
-    d1 = ov.squeeze(d1)  # scalar
-    d2 = ov.squeeze(d2)  # scalar
+    arange = ov_opset.range(
+        ov_opset.constant(0, dtype="i64"), rank_val, ov_opset.constant(1, dtype="i64")
+    )
+    mask1 = ov_opset.equal(arange, axis1_node)
+    mask2 = ov_opset.equal(arange, axis2_node)
+    not12 = ov_opset.logical_not(ov_opset.logical_or(mask1, mask2))
+    others = ov_opset.squeeze(
+        ov_opset.non_zero(not12), [1]
+    )  # gather positions != axis1, axis2
+    perm = ov_opset.concat(
+        [others, ov_opset.reshape(axis1_node, [1]), ov_opset.reshape(axis2_node, [1])], 0
+    )
+
+    x_perm = ov_opset.transpose(x_node, perm)
+    permuted_shape = ov_opset.shape_of(x_perm)
+    d1 = ov_opset.gather(
+        permuted_shape,
+        ov_opset.constant([-2], dtype="i64"),
+        ov_opset.constant(0, dtype="i64"),
+    )
+    d2 = ov_opset.gather(
+        permuted_shape,
+        ov_opset.constant([-1], dtype="i64"),
+        ov_opset.constant(0, dtype="i64"),
+    )
+    d1 = ov_opset.squeeze(d1)  # scalar
+    d2 = ov_opset.squeeze(d2)  # scalar
 
     # start1 = max(0, offset), start2 = max(0, -offset)
-    zero = ov.constant(0, dtype="i64")
-    start1 = ov.maximum(zero, offset_const)
-    start2 = ov.maximum(zero, ov.negative(offset_const))
+    zero = ov_opset.constant(0, dtype="i64")
+    start1 = ov_opset.maximum(zero, offset_const)
+    start2 = ov_opset.maximum(zero, ov_opset.negative(offset_const))
 
     # L = min(d1 - start1, d2 - start2)
-    l1 = ov.subtract(d1, start1)
-    l2 = ov.subtract(d2, start2)
-    L = ov.minimum(l1, l2)
+    l1 = ov_opset.subtract(d1, start1)
+    l2 = ov_opset.subtract(d2, start2)
+    L = ov_opset.minimum(l1, l2)
 
     # r = range(0, L, 1)  -> shape [L]
-    r = ov.range(zero, L, ov.constant(1, dtype="i64"))
-    idx_row = ov.add(r, start1)
-    idx_col = ov.add(r, start2)
-    idx_row = ov.unsqueeze(idx_row, ov.constant(1, dtype="i64"))  # [L,1]
-    idx_col = ov.unsqueeze(idx_col, ov.constant(1, dtype="i64"))  # [L,1]
-    diag_idx = ov.concat([idx_row, idx_col], 1)  # [L,2]
+    r = ov_opset.range(zero, L, ov_opset.constant(1, dtype="i64"))
+    idx_row = ov_opset.add(r, start1)
+    idx_col = ov_opset.add(r, start2)
+    idx_row = ov_opset.unsqueeze(
+        idx_row, ov_opset.constant(1, dtype="i64")
+    )  # [L,1]
+    idx_col = ov_opset.unsqueeze(
+        idx_col, ov_opset.constant(1, dtype="i64")
+    )  # [L,1]
+    diag_idx = ov_opset.concat([idx_row, idx_col], 1)  # [L,2]
 
     # Broadcast indices to batch dims: target shape = (*batch, L, 2)
     # batch_rank = rank(x) - 2
-    two = ov.constant(2, dtype="i64")
-    batch_rank = ov.subtract(rank_val, two)
+    two = ov_opset.constant(2, dtype="i64")
+    batch_rank = ov_opset.subtract(rank_val, two)
     # build target shape: concat(permuted_shape[:batch_rank], [L, 2])
-    batch_shape = ov.slice(permuted_shape, ov.constant([0], dtype="i64"),
-                           ov.reshape(batch_rank, [1]), ov.constant([1], dtype="i64"))
-    target_shape = ov.concat([batch_shape, ov.reshape(L, [1]), ov.constant([2], dtype="i64")], 0)
-    bcast_idx = ov.broadcast(diag_idx, target_shape)
+    batch_shape = ov_opset.strided_slice(
+        permuted_shape,
+        begin=ov_opset.constant([0], dtype="i64"),
+        end=ov_opset.reshape(batch_rank, [1]),
+        strides=ov_opset.constant([1], dtype="i64"),
+        begin_mask=[0],
+        end_mask=[0],
+    )
+    target_shape = ov_opset.concat(
+        [batch_shape, ov_opset.reshape(L, [1]), ov_opset.constant([2], dtype="i64")], 0
+    )
+    bcast_idx = ov_opset.broadcast(diag_idx, target_shape)
 
     # GatherND with batch_dims = batch_rank
-    gathered = ov.gather_nd(x_perm, bcast_idx, batch_rank)
+    gathered = ov_opset.gather_nd(x_perm, bcast_idx, batch_rank)
 
     return OpenVINOKerasTensor(gathered)
 

From df028d02c1381a6f0caa6362048600e54b774b91 Mon Sep 17 00:00:00 2001
From: arjunverma2004 <163740749+arjunverma2004@users.noreply.github.com>
Date: Fri, 15 Aug 2025 16:44:31 +0530
Subject: [PATCH 3/8] fixxx

---
 keras/src/backend/openvino/numpy.py | 9 ---------
 1 file changed, 9 deletions(-)

diff --git a/keras/src/backend/openvino/numpy.py b/keras/src/backend/openvino/numpy.py
index c4b70c253439..71bd78775068 100644
--- a/keras/src/backend/openvino/numpy.py
+++ b/keras/src/backend/openvino/numpy.py
@@ -33,11 +33,7 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
         ov_opset.add(ov_opset.constant(int(axis2), dtype="i64"), rank_val), rank_val
     )
 
-    # If axis1 == axis2, behavior should match numpy error; Keras tests don't hit this,
-    # so we skip explicit assert to keep graph-friendly.
 
-    # Build permutation to move axis1, axis2 to the end
-    # perm = [all axes except axis1/axis2 in order] + [axis1, axis2]
     arange = ov_opset.range(
         ov_opset.constant(0, dtype="i64"), rank_val, ov_opset.constant(1, dtype="i64")
     )
@@ -773,11 +769,6 @@ def diag(x, k=0):
     raise NotImplementedError("`diag` is not supported with openvino backend")
 
 
-def diagonal(x, offset=0, axis1=0, axis2=1):
-    raise NotImplementedError(
-        "`diagonal` is not supported with openvino backend"
-    )
-
 
 def diff(a, n=1, axis=-1):
     if n == 0:

From 1635157e59afb70d371cce2bf5bb37879d81466b Mon Sep 17 00:00:00 2001
From: arjunverma2004 <163740749+arjunverma2004@users.noreply.github.com>
Date: Fri, 15 Aug 2025 16:48:59 +0530
Subject: [PATCH 4/8] convertcde

---
 keras/src/backend/openvino/numpy.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/keras/src/backend/openvino/numpy.py b/keras/src/backend/openvino/numpy.py
index 71bd78775068..86b7c7fcae9f 100644
--- a/keras/src/backend/openvino/numpy.py
+++ b/keras/src/backend/openvino/numpy.py
@@ -15,11 +15,14 @@
 from keras.src.backend.openvino.core import convert_to_tensor
 from keras.src.backend.openvino.core import get_ov_output
 from keras.src.backend.openvino.core import ov_to_keras_type
-from .core import _convert_to_node
+import numpy as np
+from openvino.runtime import opset13 as ov
+
+
 
 def diagonal(x, offset=0, axis1=0, axis2=1):
     """OpenVINO backend decomposition for keras.ops.diagonal."""
-    x_node = _convert_to_node(x)  # -> ov.Node
+    x_node = ov.constant(x)  # -> ov.Node
     offset_const = ov_opset.constant(int(offset), dtype="i64")
 
     # rank & normalize axes

From 96802c5987c8c317aa856411a8bbbcc043ec4680 Mon Sep 17 00:00:00 2001
From: arjunverma2004 <163740749+arjunverma2004@users.noreply.github.com>
Date: Fri, 15 Aug 2025 17:31:37 +0530
Subject: [PATCH 5/8] Update numpy.py

---
 keras/src/backend/openvino/numpy.py | 37 ++++++++++++++++-------------
 1 file changed, 21 insertions(+), 16 deletions(-)

diff --git a/keras/src/backend/openvino/numpy.py b/keras/src/backend/openvino/numpy.py
index 86b7c7fcae9f..a9ccc1c094ce 100644
--- a/keras/src/backend/openvino/numpy.py
+++ b/keras/src/backend/openvino/numpy.py
@@ -1,6 +1,7 @@
 import numpy as np
 import openvino.opset14 as ov_opset
 from openvino import Type
+from openvino.runtime import opset13 as ov
 
 from keras.src.backend import config
 from keras.src.backend.common import dtypes
@@ -15,13 +16,9 @@
 from keras.src.backend.openvino.core import convert_to_tensor
 from keras.src.backend.openvino.core import get_ov_output
 from keras.src.backend.openvino.core import ov_to_keras_type
-import numpy as np
-from openvino.runtime import opset13 as ov
-
 
 
 def diagonal(x, offset=0, axis1=0, axis2=1):
-    """OpenVINO backend decomposition for keras.ops.diagonal."""
     x_node = ov.constant(x)  # -> ov.Node
     offset_const = ov_opset.constant(int(offset), dtype="i64")
 
@@ -30,15 +27,17 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
     rank = ov_opset.shape_of(shape)  # scalar i64 (len of shape)
     rank_val = ov_opset.squeeze(rank)  # [] -> scalar
     axis1_node = ov_opset.floor_mod(
-        ov_opset.add(ov_opset.constant(int(axis1), dtype="i64"), rank_val), rank_val
+        ov_opset.add(ov_opset.constant(int(axis1), dtype="i64"), rank_val),
+        rank_val,
     )
     axis2_node = ov_opset.floor_mod(
-        ov_opset.add(ov_opset.constant(int(axis2), dtype="i64"), rank_val), rank_val
+        ov_opset.add(ov_opset.constant(int(axis2), dtype="i64"), rank_val),
+        rank_val,
     )
-
-
     arange = ov_opset.range(
-        ov_opset.constant(0, dtype="i64"), rank_val, ov_opset.constant(1, dtype="i64")
+        ov_opset.constant(0, dtype="i64"),
+        rank_val,
+        ov_opset.constant(1, dtype="i64"),
     )
     mask1 = ov_opset.equal(arange, axis1_node)
     mask2 = ov_opset.equal(arange, axis2_node)
@@ -47,9 +46,14 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
         ov_opset.non_zero(not12), [1]
     )  # gather positions != axis1, axis2
     perm = ov_opset.concat(
-        [others, ov_opset.reshape(axis1_node, [1]), ov_opset.reshape(axis2_node, [1])], 0
+        [
+            others,
+            ov_opset.reshape(axis1_node, [1]),
+            ov_opset.reshape(axis2_node, [1]),
+        ],
+        0,
     )
-
+    
     x_perm = ov_opset.transpose(x_node, perm)
     permuted_shape = ov_opset.shape_of(x_perm)
     d1 = ov_opset.gather(
@@ -101,7 +105,12 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
         end_mask=[0],
     )
     target_shape = ov_opset.concat(
-        [batch_shape, ov_opset.reshape(L, [1]), ov_opset.constant([2], dtype="i64")], 0
+        [
+            batch_shape,
+            ov_opset.reshape(L, [1]),
+            ov_opset.constant([2], dtype="i64"),
+        ],
+        0,
     )
     bcast_idx = ov_opset.broadcast(diag_idx, target_shape)
 
@@ -110,8 +119,6 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
 
     return OpenVINOKerasTensor(gathered)
 
-
-
 def add(x1, x2):
     element_type = None
     if isinstance(x1, OpenVINOKerasTensor):
@@ -771,8 +778,6 @@ def deg2rad(x):
 def diag(x, k=0):
     raise NotImplementedError("`diag` is not supported with openvino backend")
 
-
-
 def diff(a, n=1, axis=-1):
     if n == 0:
         return OpenVINOKerasTensor(get_ov_output(a))

From f450869e198589fad9713f531c20931f96ea72a0 Mon Sep 17 00:00:00 2001
From: arjunverma2004 <163740749+arjunverma2004@users.noreply.github.com>
Date: Fri, 15 Aug 2025 12:08:33 +0000
Subject: [PATCH 6/8] Run api-gen hook and update API directory

---
 keras/src/backend/openvino/numpy.py | 32 ++++++++++++++++++-----------
 1 file changed, 20 insertions(+), 12 deletions(-)

diff --git a/keras/src/backend/openvino/numpy.py b/keras/src/backend/openvino/numpy.py
index 86b7c7fcae9f..bc01bbe93ac4 100644
--- a/keras/src/backend/openvino/numpy.py
+++ b/keras/src/backend/openvino/numpy.py
@@ -1,6 +1,7 @@
 import numpy as np
 import openvino.opset14 as ov_opset
 from openvino import Type
+from openvino.runtime import opset13 as ov
 
 from keras.src.backend import config
 from keras.src.backend.common import dtypes
@@ -15,13 +16,9 @@
 from keras.src.backend.openvino.core import convert_to_tensor
 from keras.src.backend.openvino.core import get_ov_output
 from keras.src.backend.openvino.core import ov_to_keras_type
-import numpy as np
-from openvino.runtime import opset13 as ov
-
 
 
 def diagonal(x, offset=0, axis1=0, axis2=1):
-    """OpenVINO backend decomposition for keras.ops.diagonal."""
     x_node = ov.constant(x)  # -> ov.Node
     offset_const = ov_opset.constant(int(offset), dtype="i64")
 
@@ -30,15 +27,18 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
     rank = ov_opset.shape_of(shape)  # scalar i64 (len of shape)
     rank_val = ov_opset.squeeze(rank)  # [] -> scalar
     axis1_node = ov_opset.floor_mod(
-        ov_opset.add(ov_opset.constant(int(axis1), dtype="i64"), rank_val), rank_val
+        ov_opset.add(ov_opset.constant(int(axis1), dtype="i64"), rank_val),
+        rank_val,
     )
     axis2_node = ov_opset.floor_mod(
-        ov_opset.add(ov_opset.constant(int(axis2), dtype="i64"), rank_val), rank_val
+        ov_opset.add(ov_opset.constant(int(axis2), dtype="i64"), rank_val),
+        rank_val,
     )
 
-
     arange = ov_opset.range(
-        ov_opset.constant(0, dtype="i64"), rank_val, ov_opset.constant(1, dtype="i64")
+        ov_opset.constant(0, dtype="i64"),
+        rank_val,
+        ov_opset.constant(1, dtype="i64"),
     )
     mask1 = ov_opset.equal(arange, axis1_node)
     mask2 = ov_opset.equal(arange, axis2_node)
@@ -47,7 +47,12 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
         ov_opset.non_zero(not12), [1]
     )  # gather positions != axis1, axis2
     perm = ov_opset.concat(
-        [others, ov_opset.reshape(axis1_node, [1]), ov_opset.reshape(axis2_node, [1])], 0
+        [
+            others,
+            ov_opset.reshape(axis1_node, [1]),
+            ov_opset.reshape(axis2_node, [1]),
+        ],
+        0,
     )
 
     x_perm = ov_opset.transpose(x_node, perm)
@@ -101,7 +106,12 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
         end_mask=[0],
     )
     target_shape = ov_opset.concat(
-        [batch_shape, ov_opset.reshape(L, [1]), ov_opset.constant([2], dtype="i64")], 0
+        [
+            batch_shape,
+            ov_opset.reshape(L, [1]),
+            ov_opset.constant([2], dtype="i64"),
+        ],
+        0,
     )
     bcast_idx = ov_opset.broadcast(diag_idx, target_shape)
 
@@ -111,7 +121,6 @@ def diagonal(x, offset=0, axis1=0, axis2=1):
     return OpenVINOKerasTensor(gathered)
 
 
-
 def add(x1, x2):
     element_type = None
     if isinstance(x1, OpenVINOKerasTensor):
@@ -772,7 +781,6 @@ def diag(x, k=0):
     raise NotImplementedError("`diag` is not supported with openvino backend")
 
 
-
 def diff(a, n=1, axis=-1):
     if n == 0:
         return OpenVINOKerasTensor(get_ov_output(a))

From 5ac523ef0bad8150f9b30e0e44f2f8d70eb28fba Mon Sep 17 00:00:00 2001
From: arjunverma2004 <163740749+arjunverma2004@users.noreply.github.com>
Date: Sat, 23 Aug 2025 09:18:48 +0000
Subject: [PATCH 7/8] Run api-gen and commit generated API directory

---
 .github/workflows/scripts/labeler.js | 70 ++++++++++++++++++----------
 1 file changed, 46 insertions(+), 24 deletions(-)

diff --git a/.github/workflows/scripts/labeler.js b/.github/workflows/scripts/labeler.js
index 769683174688..a9084c187b7f 100644
--- a/.github/workflows/scripts/labeler.js
+++ b/.github/workflows/scripts/labeler.js
@@ -13,37 +13,59 @@ You may obtain a copy of the License at
  limitations under the License.
 */
 
-
 /**
  * Invoked from labeler.yaml file to add
  * label 'Gemma' to the issue and PR for which have gemma keyword present.
  * @param {!Object.<string,!Object>} github contains pre defined functions.
- *  context Information about the workflow run.
+ * context Information about the workflow run.
  */
 
 module.exports = async ({ github, context }) => {
-    const issue_title = context.payload.issue ?  context.payload.issue.title : context.payload.pull_request.title
-    const issue_description = context.payload.issue ? context.payload.issue.body : context.payload.pull_request.body
-    const issue_number = context.payload.issue ? context.payload.issue.number : context.payload.pull_request.number
+    // Determine if the event is an issue or a pull request.
+    const isIssue = !!context.payload.issue;
+
+    // Get the issue/PR title, description, and number from the payload.
+    // Use an empty string for the description if it's null to prevent runtime errors.
+    const issue_title = isIssue ? context.payload.issue.title : context.payload.pull_request.title;
+    const issue_description = (isIssue ? context.payload.issue.body : context.payload.pull_request.body) || '';
+    const issue_number = isIssue ? context.payload.issue.number : context.payload.pull_request.number;
+    
+    // Define the keyword-to-label mapping.
     const keyword_label =  {
-         gemma:'Gemma'
-    }
-    const labelsToAdd = []
-    console.log(issue_title,issue_description,issue_number)
+         gemma: 'Gemma'
+    };
     
-    for(const [keyword, label] of Object.entries(keyword_label)){
-     if(issue_title.toLowerCase().indexOf(keyword) !=-1 || issue_description.toLowerCase().indexOf(keyword) !=-1 ){
-        console.log(`'${keyword}'keyword is present inside the title or description. Pushing label '${label}' to row.`)
-        labelsToAdd.push(label)
+    // Array to hold labels that need to be added.
+    const labelsToAdd = [];
+
+    console.log(`Processing event for issue/PR #${issue_number}: "${issue_title}"`);
+    
+    // Loop through the keywords and check if they exist in the title or description.
+    for (const [keyword, label] of Object.entries(keyword_label)) {
+        // Use .includes() for a cleaner and more modern check.
+        if (issue_title.toLowerCase().includes(keyword) || issue_description.toLowerCase().includes(keyword)) {
+            console.log(`'${keyword}' keyword is present in the title or description. Pushing label '${label}' to the array.`);
+            labelsToAdd.push(label);
+        }
+    }
+
+    // Add labels if the labelsToAdd array is not empty.
+    if (labelsToAdd.length > 0) {
+        console.log(`Adding labels ${labelsToAdd} to issue/PR '#${issue_number}'.`);
+        
+        try {
+            // Await the asynchronous API call to ensure it completes.
+            await github.rest.issues.addLabels({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                issue_number: issue_number, // Use the correct issue_number variable
+                labels: labelsToAdd
+            });
+            console.log(`Successfully added labels.`);
+        } catch (error) {
+            console.error(`Failed to add labels: ${error.message}`);
+        }
+    } else {
+        console.log("No matching keywords found. No labels to add.");
     }
-   }
-   if(labelsToAdd.length > 0){
-    console.log(`Adding labels ${labelsToAdd} to the issue '#${issue_number}'.`)
-     github.rest.issues.addLabels({
-        owner: context.repo.owner,
-        repo: context.repo.repo,
-        issue_number: context.issue.number,
-        labels: labelsToAdd
-     })
-   }
-};
\ No newline at end of file
+};

From 35071fd7a18bc6e525e523b2ed72e1ad897030cd Mon Sep 17 00:00:00 2001
From: arjunverma2004 <163740749+arjunverma2004@users.noreply.github.com>
Date: Sat, 23 Aug 2025 17:18:28 +0530
Subject: [PATCH 8/8] Update labeler.js

---
 .github/workflows/scripts/labeler.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/scripts/labeler.js b/.github/workflows/scripts/labeler.js
index a9084c187b7f..17205f47cca8 100644
--- a/.github/workflows/scripts/labeler.js
+++ b/.github/workflows/scripts/labeler.js
@@ -21,6 +21,7 @@ You may obtain a copy of the License at
  */
 
 module.exports = async ({ github, context }) => {
+
     // Determine if the event is an issue or a pull request.
     const isIssue = !!context.payload.issue;
 
@@ -34,7 +35,6 @@ module.exports = async ({ github, context }) => {
     const keyword_label =  {
          gemma: 'Gemma'
     };
-    
     // Array to hold labels that need to be added.
     const labelsToAdd = [];