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Fix take_along_axis with TensorFlow with non-int32 indices. #21256

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Merged
merged 1 commit into from
May 7, 2025
Merged

Fix take_along_axis with TensorFlow with non-int32 indices. #21256

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6 changes: 5 additions & 1 deletion keras/src/backend/tensorflow/numpy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2330,7 +2330,11 @@ def take_along_axis(x, indices, axis=None):
indices = tf.broadcast_to(indices, indices_shape)

# Correct the indices using "fill" mode which is the same as in jax
indices = tf.where(indices < 0, indices + x_shape[static_axis], indices)
indices = tf.where(
indices < 0,
indices + tf.cast(x_shape[static_axis], dtype=indices.dtype),
indices,
)

x = swapaxes(x, static_axis, -1)
indices = swapaxes(indices, static_axis, -1)
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10 changes: 6 additions & 4 deletions keras/src/ops/numpy_test.py
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Expand Up @@ -8411,14 +8411,16 @@ def test_take(self, dtype):
expected_dtype,
)

@parameterized.named_parameters(named_product(dtype=ALL_DTYPES))
def test_take_along_axis(self, dtype):
@parameterized.named_parameters(
named_product(dtype=ALL_DTYPES, indices_dtype=INT_DTYPES)
)
def test_take_along_axis(self, dtype, indices_dtype):
import jax.numpy as jnp

x = knp.ones((1,), dtype=dtype)
indices = knp.zeros((1,), dtype="int32")
indices = knp.zeros((1,), dtype=indices_dtype)
x_jax = jnp.ones((1,), dtype=dtype)
indices_jax = jnp.zeros((1,), dtype="int32")
indices_jax = jnp.zeros((1,), dtype=indices_dtype)
expected_dtype = standardize_dtype(
jnp.take_along_axis(x_jax, indices_jax, 0).dtype
)
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