1.26.9

• ReduceL1, ReduceL2
  • Fixed the logic to avoid a TensorFlow bug that caused the output tensor of tf.norm() to be (None, None, None, None).
  • TensorFlow bugs when converting a model that includes ReduceL1 or ReduceL2.

    INFO: 20 / 819
    INFO: onnx_op_type: ReduceL2 onnx_op_name: wa/model/stages/stages.0/blocks/blocks.0/mlp/grn/ReduceL2
    INFO:  input_name.1: wa/model/stages/stages.0/blocks/blocks.0/mlp/act/Mul_1_output_0 shape: [1, 56, 56, 512] dtype: float32
    INFO:  output_name.1: wa/model/stages/stages.0/blocks/blocks.0/mlp/grn/ReduceL2_output_0 shape: [1, 1, 1, 512] dtype: float32
    INFO: tf_op_type: l2_normalize
    INFO:  input.1.x: name: tf.math.multiply_8/Mul:0 shape: (1, 56, 56, 512) dtype: <dtype: 'float32'> 
    INFO:  input.2.axis: val: [1, 2] 
    INFO:  output.1.output: name: tf.compat.v1.norm_6/norm/transpose_1:0 shape: (None, None, None, None) dtype: <dtype: 'float32'> 
    

• convnextv2_base timm model conversion fails #742

What's Changed

• Fixed the logic to avoid a TensorFlow bug that caused the output tensor of tf.norm() to be (None, None, None, None) by @PINTO0309 in #743

Full Changelog: 1.26.8...1.26.9