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Question

When I export tflite model with opt --nms
python export.py --weights yolov5s.pt --include tflite --nms
I got the following error:
.....
tf.expand_dims (TFOpLambda) (1, 25200, 1, 4) 0 tf.concat[0][0]

tf.math.multiply (TFOpLambda) (1, 25200, 2) 0 tf.operators.getitem_1[0][0]
tf.operators.getitem_2[0][0]

tf.image.combined_non_max_suppr CombinedNonMaxSuppre 0 tf.expand_dims[0][0]
tf.math.multiply[0][0]

Total params: 7,015,519
Trainable params: 0
Non-trainable params: 7,015,519

2022-02-27 14:40:41.858021: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider a
voiding using them.
Found untraced functions such as tf_conv_2_layer_call_fn, tf_conv_2_layer_call_and_return_conditional_losses, tf_conv_3_layer_call_fn, tf_conv_3_layer_call_and
_return_conditional_losses, tf_conv_4_layer_call_fn while saving (showing 5 of 520). These functions will not be directly callable after loading.
Found untraced functions such as tf_conv_2_layer_call_fn, tf_conv_2_layer_call_and_return_conditional_losses, tf_conv_3_layer_call_fn, tf_conv_3_layer_call_and
_return_conditional_losses, tf_conv_4_layer_call_fn while saving (showing 5 of 520). These functions will not be directly callable after loading.
Assets written to: last_saved_model\assets
TensorFlow SavedModel: export success, saved as last_saved_model (238.6 MB)

TensorFlow Lite: starting export with tensorflow 2.4.0...
Found untraced functions such as tf_conv_2_layer_call_fn, tf_conv_2_layer_call_and_return_conditional_losses, tf_conv_3_layer_call_fn, tf_conv_3_layer_call_and
_return_conditional_losses, tf_conv_4_layer_call_fn while saving (showing 5 of 520). These functions will not be directly callable after loading.
Found untraced functions such as tf_conv_2_layer_call_fn, tf_conv_2_layer_call_and_return_conditional_losses, tf_conv_3_layer_call_fn, tf_conv_3_layer_call_and
_return_conditional_losses, tf_conv_4_layer_call_fn while saving (showing 5 of 520). These functions will not be directly callable after loading.
Assets written to: C:\Users\kk\AppData\Local\Temp\tmp7pgu55vr\assets
2022-02-27 14:41:35.278574: I tensorflow/core/grappler/devices.cc:69] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 0
2022-02-27 14:41:35.281165: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session
2022-02-27 14:41:35.283499: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2022-02-27 14:41:35.297874: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:928] Optimization results for grappler item: graph_to_optimize
function_optimizer: function_optimizer did nothing. time = 0.001ms.
function_optimizer: function_optimizer did nothing. time = 0ms.

2022-02-27 14:41:36.286075: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:316] Ignored output_format.
2022-02-27 14:41:36.288583: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:319] Ignored drop_control_dependency.
2022-02-27 14:41:36.360661: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
loc(callsite("model/tf.image.combined_non_max_suppression/combined_non_max_suppression/CombinedNonMaxSuppression"("C:\Users\kk\Anaconda3\envs\pytorch_gpu\lib\s
ite-packages\tensorflow\python\eager\def_function.py":1205:0) at callsite("C:\Users\kk\Anaconda3\envs\pytorch_gpu\lib\site-packages\tensorflow\python\eager\def
_function.py":1299:0 at callsite("C:\Users\kk\Anaconda3\envs\pytorch_gpu\lib\site-packages\tensorflow\lite\python\lite.py":847:0 at callsite("export.py":324:0
at callsite("export.py":488:0 at callsite("C:\Users\kk\Anaconda3\envs\pytorch_gpu\lib\site-packages\torch\autograd\grad_mode.py":28:0 at callsite("export.py":5
39:0 at "export.py":544:0)))))))): error: 'tf.CombinedNonMaxSuppression' op is neither a custom op nor a flex op
error: failed while converting: 'main': Ops that can be supported by the flex runtime (enabled via setting the -emit-select-tf-ops flag):
tf.CombinedNonMaxSuppression {clip_boxes = false, device = "", pad_per_class = false}

TensorFlow Lite: export failure: C:\Users\kk\Anaconda3\envs\pytorch_gpu\lib\site-packages\tensorflow\python\eager\def_function.py:1205:0: error: 'tf.CombinedNo
nMaxSuppression' op is neither a custom op nor a flex op
C:\Users\kk\Anaconda3\envs\pytorch_gpu\lib\site-packages\tensorflow\python\eager\def_function.py:1299:0: note: called from
C:\Users\kk\Anaconda3\envs\pytorch_gpu\lib\site-packages\tensorflow\lite\python\lite.py:847:0: note: called from
export.py:324:0: note: called from
export.py:488:0: note: called from
C:\Users\kk\Anaconda3\envs\pytorch_gpu\lib\site-packages\torch\autograd\grad_mode.py:28:0: note: called from
export.py:539:0: note: called from
export.py:544:0: note: called from
### :0: error: failed while converting: 'main': Ops that can be supported by the flex runtime (enabled via setting the -emit-select-tf-ops flag):
tf.CombinedNonMaxSuppression {clip_boxes = false, device = "", pad_per_class = false}

Export complete (65.58s)
Results saved to E:\python_resource\code_resource\pytorch\yolov5-master
Detect: python detect.py --weights last_saved_model
PyTorch Hub: model = torch.hub.load('ultralytics/yolov5', 'custom', 'last_saved_model')
Validate: python val.py --weights last_saved_model
Visualize: https://netron.app

Any help will be appreciated!

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No response