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] = {