Fixed the broadcast processing when x_scale is 1D 1Elem

PINTO0309 · Jan 22, 2025 · 068a9c2 · 068a9c2
1 parent a3b9ec0
commit 068a9c2
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Showing 3 changed files with 6 additions and 4 deletions.
diff --git a/README.md b/README.md
@@ -307,15 +307,15 @@ Video speed is adjusted approximately 50 times slower than actual speed.
   docker run --rm -it \
   -v `pwd`:/workdir \
   -w /workdir \
-  ghcr.io/pinto0309/onnx2tf:1.26.6
+  ghcr.io/pinto0309/onnx2tf:1.26.7
 
   or
 
   # Authentication is not required for pulls from Docker Hub.
   docker run --rm -it \
   -v `pwd`:/workdir \
   -w /workdir \
-  docker.io/pinto0309/onnx2tf:1.26.6
+  docker.io/pinto0309/onnx2tf:1.26.7
 
   or
 

diff --git a/onnx2tf/__init__.py b/onnx2tf/__init__.py
@@ -1,3 +1,3 @@
 from onnx2tf.onnx2tf import convert, main
 
-__version__ = '1.26.6'
+__version__ = '1.26.7'
diff --git a/onnx2tf/ops/DequantizeLinear.py b/onnx2tf/ops/DequantizeLinear.py
@@ -101,12 +101,14 @@ def make_node(
 
     # Reshape process is needed for per-axis dequantization
     # when scale is a 1-D tensor
-    if x_scale_rank == 1:
+    if x_scale_rank == 1 and x_scale_shape[0] != 1:
         shape_broadcast = list([1 for _ in range(axis)] + [input_tensor_shape[axis]] + [1 for _ in range(axis + 1, input_tensor_rank)])
         x_scale = tf.reshape(
             tensor=x_scale,
             shape=shape_broadcast,
         )
+    elif x_scale_rank == 1 and x_scale_shape[0] == 1:
+        shape_broadcast = [1 for i in range(input_tensor_rank)]
 
     subed_tensor = input_tensor
     if len(graph_node.inputs) >= 3 and input_tensor.dtype != tf.int32: