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new 60bb59d779 [Frontend][TFLite] Add TILE operator tests and edge cases
(#19400)
60bb59d779 is described below
commit 60bb59d7796aec149343d4f78fb2038294dc5d98
Author: Bana <[email protected]>
AuthorDate: Mon Apr 13 21:27:58 2026 +0300
[Frontend][TFLite] Add TILE operator tests and edge cases (#19400)
This PR adds non-quantized TILE coverage in `test_frontend_tflite.py`.
Related to #18971
What is included
1. One explicit Expected IR structural test for TILE
2. Parametrized TILE conversion tests covering:
- baseline 2D and higher-rank cases
- identity/no-op tiling
- larger repeat factors
- int32 non-quantized dtype path
_**Note:** SHAPE and RANGE are excluded from this PR and will be handled
separately because there's a related a bug in the frontend for them_
### Validation
```
pytest test_frontend_tflite.py -v -k "test_tile_ir or test_tile"
```
<img width="1164" height="26" alt="image"
src="https://github.com/user-attachments/assets/ede6c479-8b4d-4025-bb4a-2af8e132e162";
/>
---
tests/python/relax/test_frontend_tflite.py | 43 ++++++++++++++++++++++++++++++
1 file changed, 43 insertions(+)
diff --git a/tests/python/relax/test_frontend_tflite.py
b/tests/python/relax/test_frontend_tflite.py
index 58af46cbc9..37a6b9cd93 100644
--- a/tests/python/relax/test_frontend_tflite.py
+++ b/tests/python/relax/test_frontend_tflite.py
@@ -279,6 +279,49 @@ def test_reshape():
verify(Reshape, Expected)
+def test_tile_ir():
+ """TILE conversion with explicit Relax IR structural check."""
+
+ class Tile(tf.Module):
+ @tf.function(input_signature=[tf.TensorSpec(shape=(2, 3),
dtype=tf.float32)])
+ def func(self, x):
+ return tf.tile(x, [2, 1])
+
+ @I.ir_module
+ class Expected:
+ @R.function
+ def main(x: R.Tensor((2, 3), dtype="float32")) -> R.Tensor((4, 3),
dtype="float32"):
+ R.func_attr({"num_input": 1})
+ with R.dataflow():
+ gv: R.Tensor((4, 3), dtype="float32") = R.tile(x, repeats=[2,
1])
+ R.output(gv)
+ return gv
+
+ verify(Tile, Expected)
+
+
[email protected](
+ "input_shape, multiples, dtype",
+ [
+ ((2, 3), [2, 1], tf.float32),
+ ((1, 4, 2), [3, 1, 2], tf.float32),
+ ((2, 1, 3, 1), [1, 2, 1, 4], tf.float32),
+ ((2, 3), [1, 1], tf.float32),
+ ((3,), [2], tf.float32),
+ ((2, 3), [4, 2], tf.float32),
+ ((2, 2), [1, 3], tf.int32),
+ ],
+)
+def test_tile(input_shape, multiples, dtype):
+ """TILE conversion for non-quantized input and repeat factors."""
+
+ class Tile(tf.Module):
+ @tf.function(input_signature=[tf.TensorSpec(shape=input_shape,
dtype=dtype)])
+ def func(self, x):
+ return tf.tile(x, multiples)
+
+ verify(Tile)
+
def test_concat_v2():
class ConcatV2(tf.Module):
@tf.function(input_signature=[tf.TensorSpec(shape=(1, 30),
dtype=tf.float32)])
