Merge pull request #692 from PINTO0309/fix_flatten_no_axis

Improved handling when `axis` attribute is not defined and the batch size of the first dimension is undefined.

README.md

@@ -299,15 +299,15 @@ Video speed is adjusted approximately 50 times slower than actual speed.
   docker run --rm -it \
   -v `pwd`:/workdir \
   -w /workdir \
-  ghcr.io/pinto0309/onnx2tf:1.25.11
+  ghcr.io/pinto0309/onnx2tf:1.25.12
 
   or
 
   # Authentication is not required for pulls from Docker Hub.
   docker run --rm -it \
   -v `pwd`:/workdir \
   -w /workdir \
-  docker.io/pinto0309/onnx2tf:1.25.11
+  docker.io/pinto0309/onnx2tf:1.25.12
 
   or
 
@@ -404,7 +404,7 @@ The given SavedModel SignatureDef contains the following input(s):
 The given SavedModel SignatureDef contains the following output(s):
   outputs['output_0'] tensor_info:
       dtype: DT_FLOAT
-      shape: (1, 1000) # <-- Model design bug in resnet18-v1-7.onnx
+      shape: (-1, 1000)
       name: PartitionedCall:0
 Method name is: tensorflow/serving/predict
 

onnx2tf/__init__.py

@@ -1,3 +1,3 @@
 from onnx2tf.onnx2tf import convert, main
 
-__version__ = '1.25.11'
+__version__ = '1.25.12'

onnx2tf/ops/Flatten.py

@@ -57,14 +57,17 @@ def make_node(
     output_shape = graph_node_output.shape
     dtype = graph_node_output.dtype
 
-    axis = graph_node.attrs.get("axis", 0)
-    if graph_node_input.shape is not None \
-        and axis < input_tensor_rank:
-        axis = convert_axis(
-            axis=axis,
-            tensor_rank=len(graph_node_input.shape),
-            before_op_output_shape_trans=before_op_output_shape_trans,
-        )
+    axis = graph_node.attrs.get("axis", None)
+    if axis is not None:
+        if graph_node_input.shape is not None \
+            and axis < input_tensor_rank:
+            axis = convert_axis(
+                axis=axis,
+                tensor_rank=len(graph_node_input.shape),
+                before_op_output_shape_trans=before_op_output_shape_trans,
+            )
+    else:
+        axis = input_tensor_rank - 1
 
     # Preserving Graph Structure (Dict)
     tf_layers_dict[graph_node_output.name] = {