Conv2D.Op/input_size_112_weight_size_5_input_channels_256_output_channels_120_stride_1_padding_same_0_is_signed_0,Fail
Conv2D.Op/input_size_112_weight_size_5_input_channels_256_output_channels_120_stride_1_padding_same_1_is_signed_0,Fail

Add.Op/input_size_112_weight_size_3_input_channels_32_output_channels_120_stride_1_padding_same_1_is_signed_0,Fail
Add.Op/input_size_112_weight_size_5_input_channels_32_output_channels_256_stride_1_padding_same_1_is_signed_0,Fail
Add.Op/input_size_5_weight_size_5_input_channels_32_output_channels_256_stride_1_padding_same_1_is_signed_0,Fail
Add.Op/input_size_5_weight_size_5_input_channels_32_output_channels_256_stride_2_padding_same_1_is_signed_0,Fail
Add.Op/input_size_80_weight_size_3_input_channels_32_output_channels_120_stride_1_padding_same_1_is_signed_0,Fail
Add.Op/input_size_80_weight_size_5_input_channels_32_output_channels_256_stride_1_padding_same_1_is_signed_0,Fail

# Something seems to have changed in TensorFlow Lite and it doesn't pass any more.
# Probably the implementation of TFLite_Detection_PostProcess is producing results in a different order.
# The model actually detects correctly.
Models.Op/mobiledet_ssdlite_mobiledet_coco_qat_postprocess,Fail

Models.Op/yolox_yolox,Fail
