[tvm] branch main updated: [TFLite][Frontend] Fix test failures caused by div-by-zero (#15844)

[lu...@apache.org]

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lunderberg pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git


The following commit(s) were added to refs/heads/main by this push:
     new eb2a4bc8e2 [TFLite][Frontend] Fix test failures caused by div-by-zero (#15844)
eb2a4bc8e2 is described below

commit eb2a4bc8e2ca982427983f999dc61d7c0861088f
Author: Anatol Liu <an...@gmail.com>
AuthorDate: Tue Oct 10 10:35:54 2023 -0400

    [TFLite][Frontend] Fix test failures caused by div-by-zero (#15844)
    
    * [TFLite][Frontend] Support quantized floor_mod
    
    * [TVM][Frontend] Fix zero-point issues in quantized div/floor_div
    
    * [TVM][Frontend] Fix zero-point issues in quantized div/floor_div
---
 tests/python/frontend/tflite/test_forward.py | 15 ++++++++++++++-
 1 file changed, 14 insertions(+), 1 deletion(-)

diff --git a/tests/python/frontend/tflite/test_forward.py b/tests/python/frontend/tflite/test_forward.py
index d9a53fd517..f601667024 100644
--- a/tests/python/frontend/tflite/test_forward.py
+++ b/tests/python/frontend/tflite/test_forward.py
@@ -2452,6 +2452,7 @@ def _test_elemwise(
     qnn_op=None,
     same_qnn_params=False,
     comparison_op=False,
+    exclude_zero_point=False,
 ):
     """One iteration of elemwise"""
 
@@ -2480,6 +2481,16 @@ def _test_elemwise(
                 inq0_min, inq0_max = (out_min, out_max)
                 inq1_min, inq1_max = (out_min, out_max)
 
+            if exclude_zero_point:
+                if inq1_max == inq1_min:
+                    raise ZeroDivisionError("Input range is 0.")
+
+                # only compute for rhs.
+                quant_scale = 255 / (inq1_max - inq1_min)
+                zero_point = int(round(-inq1_min * quant_scale))
+                data[1][data[1] == zero_point] += 1
+                data[1][data[1] == 0] += 1
+
             # fake_quant will keep the tensors in float32 until the conversion in the session
             inq_data = [
                 tf.quantization.fake_quant_with_min_max_args(
@@ -2619,6 +2630,7 @@ def _test_div(data, fused_activation_function=None, quantized=False, qnn_op=None
         quantized,
         qnn_op,
         same_qnn_params=True,
+        exclude_zero_point=True,
     )
 
 
@@ -2802,6 +2814,7 @@ def _test_floor_divide(data, fused_activation_function=None, quantized=False, qn
         quantized,
         qnn_op,
         same_qnn_params=True,
+        exclude_zero_point=True,
     )
 
 
@@ -2882,7 +2895,7 @@ def _test_elemwise_qnn_out_range(qnn_op):
 
 
 def test_all_elemwise():
-    """All_elewise"""
+    """All_elemwise"""
     _test_forward_elemwise(_test_add)
     _test_forward_elemwise_quantized(_test_add)
     _test_forward_elemwise(partial(_test_add, fused_activation_function="RELU"))