text:
TFLite converter effecientnet-b0 error

Пытаюсь конвертировать TF модель efficientnet-b0 из OpenModelZoo.  tflite_converter.py выдает ошибку с неподдерживаемым слоем __inference_swish_f32_730.
Пробовал с разными tensorflow, последний раз с tensorflow==2.12.0  и tensorflow-addons==0.19 tensorflow-estimator==2.12.0 tensorflow-probability==0.19
Строка конвертации:
python tflite_converter.py --model-path /home/vasiliev/_dev/itlab/public/efficientnet-b0/efficientnet-b0/saved_model --input-names sub --input-shapes [1,224,224,3] --source-framework tf --output-names logits

Вывод скрипта с ошибкой (часть, полный вывод по ссылке: https://gist.github.com/FenixFly/3c523abc679934a7df6b67ad006c7ad6 ):
[ INFO ] Loading TF model
[ INFO ] Loading saved model from /home/vasiliev/_dev/itlab/public/efficientnet-b0/efficientnet-b0/saved_model
2024-03-10 12:27:35.194661: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
2024-03-10 12:27:35.194910: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1956] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
INFO:tensorflow:Saver not created because there are no variables in the graph to restore
[ INFO ] Saver not created because there are no variables in the graph to restore
[ INFO ] Setting input shapes to ([1, 224, 224, 3],)
[ INFO ] Converting to tflite
[ WARNING ] Please consider providing the trackable_obj argument in the from_concrete_functions. Providing without the trackable_obj argument is deprecated and it will use the deprecated conversion path.
2024-03-10 12:27:35.778469: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
2024-03-10 12:27:35.778594: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1
loc(fused["__inference_swish_f32_73:", callsite("efficientnet-b0/model/blocks_4/se/swish_f32"("/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py":985:0) at callsite("/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py":836:0 at callsite("/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py":12:0 at callsite("/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py":142:0 at callsite("/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py":164:0 at "/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py":176:0)))))]): error: 'tf.LegacyCall' op is neither a custom op nor a flex op
loc(fused["__inference_swish_f32_73:", callsite("efficientnet-b0/model/head/swish_f32"("/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py":985:0) at callsite("/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py":836:0 at callsite("/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py":12:0 at callsite("/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py":142:0 at callsite("/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py":164:0 at "/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py":176:0)))))]): error: 'tf.LegacyCall' op is neither a custom op nor a flex op
2024-03-10 12:27:36.605790: W tensorflow/compiler/mlir/lite/flatbuffer_export.cc:2051] TFLite interpreter needs to link Flex delegate in order to run the model since it contains the following Select TFop(s):
Flex ops: FlexConv2D, FlexDepthwiseConv2dNative
Details:
	tf.Conv2D(tensor<*xf32>, tensor<1x1x10x240xf32>) -> (tensor<?x?x?x240xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x1152x192xf32>) -> (tensor<?x?x?x192xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x1152x320xf32>) -> (tensor<?x?x?x320xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x1152x48xf32>) -> (tensor<?x?x?x48xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x144x24xf32>) -> (tensor<?x?x?x24xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x144x40xf32>) -> (tensor<?x?x?x40xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x144x6xf32>) -> (tensor<?x?x?x6xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x20x480xf32>) -> (tensor<?x?x?x480xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x240x10xf32>) -> (tensor<?x?x?x10xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x240x40xf32>) -> (tensor<?x?x?x40xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x240x80xf32>) -> (tensor<?x?x?x80xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x28x672xf32>) -> (tensor<?x?x?x672xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x32x16xf32>) -> (tensor<?x?x?x16xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x32x8xf32>) -> (tensor<?x?x?x8xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x480x112xf32>) -> (tensor<?x?x?x112xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x480x20xf32>) -> (tensor<?x?x?x20xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x480x80xf32>) -> (tensor<?x?x?x80xf32>) : {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.Conv2D(tensor<*xf32>, tensor<1x1x48x1152xf32>) -> (tensor<?x?x?x1152xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}
	tf.DepthwiseConv2dNative(tensor<*xf32>, tensor<3x3x96x1xf32>) -> (tensor<?x?x?x96xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 2, 2, 1]}
	tf.DepthwiseConv2dNative(tensor<*xf32>, tensor<5x5x1152x1xf32>) -> (tensor<?x?x?x1152xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1]}
	tf.DepthwiseConv2dNative(tensor<*xf32>, tensor<5x5x144x1xf32>) -> (tensor<?x?x?x144xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 2, 2, 1]}
	tf.DepthwiseConv2dNative(tensor<*xf32>, tensor<5x5x240x1xf32>) -> (tensor<?x?x?x240xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1]}
	tf.DepthwiseConv2dNative(tensor<*xf32>, tensor<5x5x480x1xf32>) -> (tensor<?x?x?x480xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1]}
	tf.DepthwiseConv2dNative(tensor<*xf32>, tensor<5x5x672x1xf32>) -> (tensor<?x?x?x672xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1]}
	tf.DepthwiseConv2dNative(tensor<*xf32>, tensor<5x5x672x1xf32>) -> (tensor<?x?x?x672xf32>) : {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 2, 2, 1]}
See instructions: https://www.tensorflow.org/lite/guide/ops_select
error: failed while converting: 'main':
Some ops in the model are custom ops, See instructions to implement custom ops: https://www.tensorflow.org/lite/guide/ops_custom
Custom ops: __inference_swish_f32_730
Details:
	tf.LegacyCall(tensor<1x112x112x32xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x10xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x1152xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x1280xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x144xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x20xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x240xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x28xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x32xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x480xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x48xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x4xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x672xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x6xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x8xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x96xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}

Traceback (most recent call last):
  File "/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py", line 176, in <module>
    main()
  File "/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py", line 172, in main
    convert_to_tflite(model, output_file)
  File "/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py", line 85, in convert_to_tflite
    tflite_model = converter.convert()
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/lite.py", line 1897, in convert
    return super(TFLiteConverterV2, self).convert()
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/lite.py", line 962, in wrapper
    return self._convert_and_export_metrics(convert_func, *args, **kwargs)
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/lite.py", line 940, in _convert_and_export_metrics
    result = convert_func(self, *args, **kwargs)
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/lite.py", line 1546, in convert
    return super(TFLiteFrozenGraphConverterV2,
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/lite.py", line 1166, in convert
    result = _convert_graphdef(
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/convert_phase.py", line 212, in wrapper
    raise converter_error from None  # Re-throws the exception.
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/convert_phase.py", line 205, in wrapper
    return func(*args, **kwargs)
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/convert.py", line 817, in convert_graphdef
    data = convert(
  File "/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/lite/python/convert.py", line 322, in convert
    raise converter_error
tensorflow.lite.python.convert_phase.ConverterError: /home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: error: 'tf.LegacyCall' op is neither a custom op nor a flex op
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:836:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:12:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tensorflow_common.py:142:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:164:0: note: called from
/home/vasiliev/_dev/itlab/dl-benchmark-vasilev/src/model_converters/tf2tflite/tflite_converter.py:176:0: note: called from
/home/vasiliev/miniconda3/envs/vino/lib/python3.9/site-packages/tensorflow/python/saved_model/load.py:985:0: note: Error code: ERROR_NEEDS_CUSTOM_OPS
<unknown>:0: error: failed while converting: 'main':
Some ops in the model are custom ops, See instructions to implement custom ops: https://www.tensorflow.org/lite/guide/ops_custom
Custom ops: __inference_swish_f32_730
Details:
	tf.LegacyCall(tensor<1x112x112x32xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x10xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x1152xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x1280xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x144xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x20xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x240xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x28xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x32xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x480xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x48xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x4xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x672xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x6xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x8xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}
	tf.LegacyCall(tensor<?x?x?x96xf32>) -> (tensor<*xf32>) : {_disable_call_shape_inference = true, device = "", tfg.legacy_call = @__inference_swish_f32_730}

@n-berezina-nn Наталья, не могли бы вы помочь разобраться почему модель efficientnet-b0 из OpenModelZoo не конвертируется в формат tflite?

@n-berezina-nn, @FenixFly, сконвертировала модель с использованием следующего скрипта:
import tensorflow as tf

converter = tf.lite.TFLiteConverter.from_saved_model('./efficientnet-b0/saved_model/')
converter.target_spec.supported_ops = [
  tf.lite.OpsSet.TFLITE_BUILTINS, tf.lite.OpsSet.SELECT_TF_OPS
]
converter.allow_custom_ops=True
tflite_model = converter.convert()

with open('model.tflite', 'wb') as f:
  f.write(tflite_model)

Запускаю вывод средствами вот такой командной строки:
python3 ./inference_tensorflowlite.py -m ./efficientnet-b0/model.tflite -i ./data/ -b 1 -t classification --output_names logits -l ./labels/image_net_synset.txt --input_names sub[1,224,224,3]

Получаю следующий вывод:
2024-03-20 22:07:52.309100: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-03-20 22:07:52.309335: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.
2024-03-20 22:07:52.311233: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.
2024-03-20 22:07:52.334658: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-03-20 22:07:52.738092: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
[ INFO ] Loading network files:
         /home/itmm/Documents/kustikova_v/public/efficientnet-b0/efficientnet-b0/model.tflite
INFO: Created TensorFlow Lite delegate for select TF ops.
INFO: TfLiteFlexDelegate delegate: 64 nodes delegated out of 270 nodes with 64 partitions.

2024-03-20 22:07:52.998300: E tensorflow/core/framework/node_def_util.cc:676] NodeDef mentions attribute use_inter_op_parallelism which is not in the op definition: Op<name=DepthwiseConv2dNative; signature=input:T, filter:T -> output:T; attr=T:type,allowed=[DT_HALF, DT_BFLOAT16, DT_FLOAT, DT_DOUBLE]; attr=strides:list(int); attr=padding:string,allowed=["SAME", "VALID", "EXPLICIT"]; attr=explicit_paddings:list(int),default=[]; attr=data_format:string,default="NHWC",allowed=["NHWC", "NCHW"]; attr=dilations:list(int),default=[1, 1, 1, 1]> This may be expected if your graph generating binary is newer  than this binary. Unknown attributes will be ignored. NodeDef: {{node DepthwiseConv2dNative}}
[ INFO ] Shape for input layer sub:0: 1x224x224x3
[ INFO ] Preparing input data: ['/home/itmm/Documents/kustikova_v/data/']
[ INFO ] Starting inference (1 iterations)
INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
[ ERROR ] Traceback (most recent call last):
  File "/home/itmm/Documents/kustikova_v/upstream/dl-benchmark/src/inference/./inference_tensorflowlite.py", line 286, in main
    result, inference_time = inference_tflite(interpreter, args.number_iter, io.get_slice_input, args.time)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/itmm/Documents/kustikova_v/upstream/dl-benchmark/src/inference/./inference_tensorflowlite.py", line 191, in inference_tflite
    interpreter.allocate_tensors()
  File "/home/itmm/miniconda/envs/tflite_converter_env/lib/python3.11/site-packages/tensorflow/lite/python/interpreter.py", line 531, in allocate_tensors
    return self._interpreter.AllocateTensors()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Encountered unresolved custom op: swish_f320.
See instructions: https://www.tensorflow.org/lite/guide/ops_custom Node number 2 (swish_f320) failed to prepare.Encountered unresolved custom op: swish_f320.
See instructions: https://www.tensorflow.org/lite/guide/ops_custom Node number 2 (swish_f320) failed to prepare.

Если все правильно понимаю, то это означает, что конвертер посчитал, что оператор swich_f320 относится к числу кастомных, и реализация должна быть передана через делегат при запуске инференса, но стандартные делегаты не содержат его реализации.

@FenixFly, @n-berezina-nn, сравнила через netron модель из OMZ в формате saved_model, которую мы хотим сконвертировать, и присланную модель в формате tflite. В модели OMZ есть явный слой swish_f32 (схема ниже), в присланной модели таких преобразований вообще нет. Это означает, что либо для конвертации использована другая модель, либо эту модель как-то преобразовывали перед тем, как сконвертировать.

authors: FenixFly valentina-kustikova

repo: itlab-vision/dl-benchmark


text:
Helper script detected by AMSI when building

When building the script, the file src\02_Helpers.ps1 is blocked by AMSI.
C:\PATH\TO\PrivescCheck>powershell -ep bypass -c ".\Build.ps1"
[OK] Loaded module file 00_Main.ps1
[OK] Loaded module file 01_Win32.ps1
[KO] Failed to load module file 02_Helpers.ps1
[ERROR] At C:\_WORKSPACE\PrivescCheck\src\02_Helpers.ps1:1 char:1
+ function Test-IsRunningInConsole {
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This script contains malicious content and has been blocked by your antivirus software.
[OK] Loaded module file 03_User.ps1
[OK] Loaded module file 04_Services.ps1
[OK] Loaded module file 05_Applications.ps1
[OK] Loaded module file 06_ScheduledTasks.ps1
[OK] Loaded module file 07_Hardening.ps1
[OK] Loaded module file 08_Config.ps1
[OK] Loaded module file 09_Network.ps1
[OK] Loaded module file 10_Updates.ps1
[OK] Loaded module file 11_Credentials.ps1
[OK] Loaded module file 99_Misc.ps1

This can be worked around by disabling "Windows Security" during build, but it would be nice to improve the Builder script in order to bypass detection earlier in the process.

Slightly modified the Builder script.

Instead of trying to load each script, and then removing the comments, I remove the comments first, and then I try to load the resulting code block.
In addition to the comment blocks, I also remove comment lines. Another benefit is that this reduces the size of the final file even more.

That's it. Apparently, this does the trick because the script is no longer caught by AMSI. :partying_face:

source: gharchive/issue

license_type: permissive

license_source: github-api


text:
minecraft-server:java8 tag no longer starts with forge modpack

Describe the problem
Haven't started this server up in few weeks, today I pulled latest :java8 image and it won't extract the modpack. It prints out 1 error on 1st launch, and then more on 2nd launch. The modpack .zip nor docker-compose.yml have not changed since last successful run of the server.
edit: For what it's worth a similarly set up fabric modpack running on latest itzg/minecraft-server tag runs ok.
Container definition
version: '3'

services:
  mc_rlcraft:
    ports:
      - "25565:25565"
    environment:
      EULA: "true"
      TZ: "Europe/London"
      MAX_MEMORY: "8G"
      VERSION: "1.12.2"
      TYPE: "FORGE"
      FORGEVERSION: "14.23.5.2855"
      OPS: ${OPLIST}
      WHITELIST: ${WLIST}
      GENERIC_PACK: "/modpacks/RLCraft_Server_Pack_Beta_v2.8.2.zip"
      USE_MODPACK_START_SCRIPT: "false"
      ALLOW_FLIGHT: "true"
      MAX_TICK_TIME: "-1"
      VIEW_DISTANCE: 10
      MAX_PLAYERS: 5
      PVP: "false"
      OVERRIDE_SERVER_PROPERTIES: "true"
      LEVEL_TYPE: "BIOMESOP"
      ENABLE_ROLLING_LOGS: "true"
      USE_AIKAR_FLAGS: "true"
      DIFFICULTY: "normal"
    image: itzg/minecraft-server:java8
    container_name: mc-rlcraft
    restart: unless-stopped
    volumes:
      - ./data:/data
      - ./modpacks:/modpacks

Container logs
1st launch
mc-rlcraft    | [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | find: unrecognized: -printf
mc-rlcraft    | BusyBox v1.29.3 (2019-01-24 07:45:07 UTC) multi-call binary.
mc-rlcraft    |
mc-rlcraft    | Usage: find [-HL] [PATH]... [OPTIONS] [ACTIONS]
mc-rlcraft    |
mc-rlcraft    | Search for files and perform actions on them.
mc-rlcraft    | First failed action stops processing of current file.
mc-rlcraft    | Defaults: PATH is current directory, action is '-print'
mc-rlcraft    |
mc-rlcraft    |         -L,-follow      Follow symlinks
mc-rlcraft    |         -H              ...on command line only
mc-rlcraft    |         -xdev           Don't descend directories on other filesystems
mc-rlcraft    |         -maxdepth N     Descend at most N levels. -maxdepth 0 applies
mc-rlcraft    |                         actions to command line arguments only
mc-rlcraft    |         -mindepth N     Don't act on first N levels
mc-rlcraft    |         -depth          Act on directory *after* traversing it
mc-rlcraft    |
mc-rlcraft    | Actions:
mc-rlcraft    |         ( ACTIONS )     Group actions for -o / -a
mc-rlcraft    |         ! ACT           Invert ACT's success/failure
mc-rlcraft    |         ACT1 [-a] ACT2  If ACT1 fails, stop, else do ACT2
mc-rlcraft    |         ACT1 -o ACT2    If ACT1 succeeds, stop, else do ACT2
mc-rlcraft    |                         Note: -a has higher priority than -o
mc-rlcraft    |         -name PATTERN   Match file name (w/o directory name) to PATTERN
mc-rlcraft    |         -iname PATTERN  Case insensitive -name
mc-rlcraft    |         -path PATTERN   Match path to PATTERN
mc-rlcraft    |         -ipath PATTERN  Case insensitive -path
mc-rlcraft    |         -regex PATTERN  Match path to regex PATTERN
mc-rlcraft    |         -type X         File type is X (one of: f,d,l,b,c,s,p)
mc-rlcraft    |         -perm MASK      At least one mask bit (+MASK), all bits (-MASK),
mc-rlcraft    |                         or exactly MASK bits are set in file's mode
mc-rlcraft    |         -mtime DAYS     mtime is greater than (+N), less than (-N),
mc-rlcraft    |                         or exactly N days in the past
mc-rlcraft    |         -mmin MINS      mtime is greater than (+N), less than (-N),
mc-rlcraft    |                         or exactly N minutes in the past
mc-rlcraft    |         -newer FILE     mtime is more recent than FILE's
mc-rlcraft    |         -inum N         File has inode number N
mc-rlcraft    |         -user NAME/ID   File is owned by given user
mc-rlcraft    |         -group NAME/ID  File is owned by given group
mc-rlcraft    |         -size N[bck]    File size is N (c:bytes,k:kbytes,b:512 bytes(def.))
mc-rlcraft    |                         +/-N: file size is bigger/smaller than N
mc-rlcraft    |         -links N        Number of links is greater than (+N), less than (-N),
mc-rlcraft    |                         or exactly N
mc-rlcraft    |         -prune          If current file is directory, don't descend into it
mc-rlcraft    | If none of the following actions is specified, -print is assumed
mc-rlcraft    |         -print          Print file name
mc-rlcraft    |         -print0         Print file name, NUL terminated
mc-rlcraft    |         -exec CMD ARG ; Run CMD with all instances of {} replaced by
mc-rlcraft    |                         file name. Fails if CMD exits with nonzero
mc-rlcraft    |         -exec CMD ARG + Run CMD with {} replaced by list of file names
mc-rlcraft    |         -delete         Delete current file/directory. Turns on -depth option

2nd launch
mc-rlcraft    | [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input
mc-rlcraft    | replace config/adhooks/adhooks.cfg? [y]es, [n]o, [A]ll, [N]one, [r]ename: [init] Running as uid=1000 gid=1000 with /data as 'drwxrwxr-x   12 1000     1000          4096 Nov 21 20:53 /data'
mc-rlcraft    | [init] Resolved version given 1.12.2 into 1.12.2
mc-rlcraft    | [init] Resolving type given FORGE
mc-rlcraft    | [init] Checking Forge version information.
mc-rlcraft    | unzip: can't read standard input

Please switch to itzg/minecraft-server:java8-multiarch.

Many thanks that solved it!

I found a compatibility package that will resolve the original issue.

itzg/minecraft-server:java8 image is now fixed.

authors: hugalafutro itzg

repo: itzg/docker-minecraft-server


text:
Forge and Packwiz

Enhancement Type
Improve an existing feature
Describe the enhancement
Allow forge to also implement packwiz, instead of just fabric.

Just figured out the issue, I thought I could just git clone and point the url to the file instead.
PS: Should add in the readme that it does works with forge and fabric, instead of just fabric.

Just figured out the issue, I thought I could just git clone and point the url to the file instead.
PS: Should add in the readme that it does works with forge and fabric, instead of just fabric.

I don't see where it says only Fabric. Or was it the example that implied that?

I don't see where it says only Fabric. Or was it the example that implied that?

Pretty much, plus I was still kinda new to packwiz and was trying to get used to it. Some completely my bad.

authors: Extensivity itzg


text:
Minimal Setup with Kickstart.nvim & VimTeX

Minimal Setup
❯ tree ~/.config/nvim
/Users/kiryph/.config/nvim
├── after
│   └── plugin
│       └── defaults.lua
├── init.lua
└── lua
    └── custom
        └── plugins.lua

5 directories, 3 files

Minimal init.lua
Kickstart.nvim provides a minimal init.lua using Packer.nvim and installing by default luasnip, nvim-treesitter and few others:
init.lua
-- Install packer
local install_path = vim.fn.stdpath 'data' .. '/site/pack/packer/start/packer.nvim'
local is_bootstrap = false
if vim.fn.empty(vim.fn.glob(install_path)) > 0 then
  is_bootstrap = true
  vim.fn.system { 'git', 'clone', '--depth', '1', 'https://github.com/wbthomason/packer.nvim', install_path }
  vim.cmd [[packadd packer.nvim]]
end

require('packer').startup(function(use)
  -- Package manager
  use 'wbthomason/packer.nvim'

  use { -- LSP Configuration & Plugins
    'neovim/nvim-lspconfig',
    requires = {
      -- Automatically install LSPs to stdpath for neovim
      'williamboman/mason.nvim',
      'williamboman/mason-lspconfig.nvim',

      -- Useful status updates for LSP
      'j-hui/fidget.nvim',

      -- Additional lua configuration, makes nvim stuff amazing
      'folke/neodev.nvim',
    },
  }

  use { -- Autocompletion
    'hrsh7th/nvim-cmp',
    requires = { 'hrsh7th/cmp-nvim-lsp', 'L3MON4D3/LuaSnip', 'saadparwaiz1/cmp_luasnip' },
  }

  use { -- Highlight, edit, and navigate code
    'nvim-treesitter/nvim-treesitter',
    run = function()
      pcall(require('nvim-treesitter.install').update { with_sync = true })
    end,
  }

  use { -- Additional text objects via treesitter
    'nvim-treesitter/nvim-treesitter-textobjects',
    after = 'nvim-treesitter',
  }

  -- Git related plugins
  use 'tpope/vim-fugitive'
  use 'tpope/vim-rhubarb'
  use 'lewis6991/gitsigns.nvim'

  use 'navarasu/onedark.nvim' -- Theme inspired by Atom
  use 'nvim-lualine/lualine.nvim' -- Fancier statusline
  use 'lukas-reineke/indent-blankline.nvim' -- Add indentation guides even on blank lines
  use 'numToStr/Comment.nvim' -- "gc" to comment visual regions/lines
  use 'tpope/vim-sleuth' -- Detect tabstop and shiftwidth automatically

  -- Fuzzy Finder (files, lsp, etc)
  use { 'nvim-telescope/telescope.nvim', branch = '0.1.x', requires = { 'nvim-lua/plenary.nvim' } }

  -- Fuzzy Finder Algorithm which requires local dependencies to be built. Only load if `make` is available
  use { 'nvim-telescope/telescope-fzf-native.nvim', run = 'make', cond = vim.fn.executable 'make' == 1 }

  -- Add custom plugins to packer from ~/.config/nvim/lua/custom/plugins.lua
  local has_plugins, plugins = pcall(require, 'custom.plugins')
  if has_plugins then
    plugins(use)
  end

  if is_bootstrap then
    require('packer').sync()
  end
end)

-- When we are bootstrapping a configuration, it doesn't
-- make sense to execute the rest of the init.lua.
--
-- You'll need to restart nvim, and then it will work.
if is_bootstrap then
  print '=================================='
  print '    Plugins are being installed'
  print '    Wait until Packer completes,'
  print '       then restart nvim'
  print '=================================='
  return
end

-- Automatically source and re-compile packer whenever you save this init.lua
local packer_group = vim.api.nvim_create_augroup('Packer', { clear = true })
vim.api.nvim_create_autocmd('BufWritePost', {
  command = 'source <afile> | silent! LspStop | silent! LspStart | PackerCompile',
  group = packer_group,
  pattern = vim.fn.expand '$MYVIMRC',
})

-- [[ Setting options ]]
-- See `:help vim.o`

-- Set highlight on search
vim.o.hlsearch = false

-- Make line numbers default
vim.wo.number = true

-- Enable mouse mode
vim.o.mouse = 'a'

-- Enable break indent
vim.o.breakindent = true

-- Save undo history
vim.o.undofile = true

-- Case insensitive searching UNLESS /C or capital in search
vim.o.ignorecase = true
vim.o.smartcase = true

-- Decrease update time
vim.o.updatetime = 250
vim.wo.signcolumn = 'yes'

-- Set colorscheme
vim.o.termguicolors = true
vim.cmd [[colorscheme onedark]]

-- Set completeopt to have a better completion experience
vim.o.completeopt = 'menuone,noselect'

-- [[ Basic Keymaps ]]
-- Set <space> as the leader key
-- See `:help mapleader`
--  NOTE: Must happen before plugins are required (otherwise wrong leader will be used)
vim.g.mapleader = ' '
vim.g.maplocalleader = ' '

-- Keymaps for better default experience
-- See `:help vim.keymap.set()`
vim.keymap.set({ 'n', 'v' }, '<Space>', '<Nop>', { silent = true })

-- Remap for dealing with word wrap
vim.keymap.set('n', 'k', "v:count == 0 ? 'gk' : 'k'", { expr = true, silent = true })
vim.keymap.set('n', 'j', "v:count == 0 ? 'gj' : 'j'", { expr = true, silent = true })

-- [[ Highlight on yank ]]
-- See `:help vim.highlight.on_yank()`
local highlight_group = vim.api.nvim_create_augroup('YankHighlight', { clear = true })
vim.api.nvim_create_autocmd('TextYankPost', {
  callback = function()
    vim.highlight.on_yank()
  end,
  group = highlight_group,
  pattern = '*',
})

-- Set lualine as statusline
-- See `:help lualine.txt`
require('lualine').setup {
  options = {
    icons_enabled = false,
    theme = 'onedark',
    component_separators = '|',
    section_separators = '',
  },
}

-- Enable Comment.nvim
require('Comment').setup()

-- Enable `lukas-reineke/indent-blankline.nvim`
-- See `:help indent_blankline.txt`
require('indent_blankline').setup {
  char = '┊',
  show_trailing_blankline_indent = false,
}

-- Gitsigns
-- See `:help gitsigns.txt`
require('gitsigns').setup {
  signs = {
    add = { text = '+' },
    change = { text = '~' },
    delete = { text = '_' },
    topdelete = { text = '‾' },
    changedelete = { text = '~' },
  },
}

-- [[ Configure Telescope ]]
-- See `:help telescope` and `:help telescope.setup()`
require('telescope').setup {
  defaults = {
    mappings = {
      i = {
        ['<C-u>'] = false,
        ['<C-d>'] = false,
      },
    },
  },
}

-- Enable telescope fzf native, if installed
pcall(require('telescope').load_extension, 'fzf')

-- See `:help telescope.builtin`
vim.keymap.set('n', '<leader>?', require('telescope.builtin').oldfiles, { desc = '[?] Find recently opened files' })
vim.keymap.set('n', '<leader><space>', require('telescope.builtin').buffers, { desc = '[ ] Find existing buffers' })
vim.keymap.set('n', '<leader>/', function()
  -- You can pass additional configuration to telescope to change theme, layout, etc.
  require('telescope.builtin').current_buffer_fuzzy_find(require('telescope.themes').get_dropdown {
    winblend = 10,
    previewer = false,
  })
end, { desc = '[/] Fuzzily search in current buffer]' })

vim.keymap.set('n', '<leader>sf', require('telescope.builtin').find_files, { desc = '[S]earch [F]iles' })
vim.keymap.set('n', '<leader>sh', require('telescope.builtin').help_tags, { desc = '[S]earch [H]elp' })
vim.keymap.set('n', '<leader>sw', require('telescope.builtin').grep_string, { desc = '[S]earch current [W]ord' })
vim.keymap.set('n', '<leader>sg', require('telescope.builtin').live_grep, { desc = '[S]earch by [G]rep' })
vim.keymap.set('n', '<leader>sd', require('telescope.builtin').diagnostics, { desc = '[S]earch [D]iagnostics' })

-- [[ Configure Treesitter ]]
-- See `:help nvim-treesitter`
require('nvim-treesitter.configs').setup {
  -- Add languages to be installed here that you want installed for treesitter
  ensure_installed = { 'c', 'cpp', 'go', 'lua', 'python', 'rust', 'typescript', 'help', 'vim' },

  highlight = { enable = true },
  indent = { enable = true, disable = { 'python' } },
  incremental_selection = {
    enable = true,
    keymaps = {
      init_selection = '<c-space>',
      node_incremental = '<c-space>',
      scope_incremental = '<c-s>',
      node_decremental = '<c-backspace>',
    },
  },
  textobjects = {
    select = {
      enable = true,
      lookahead = true, -- Automatically jump forward to textobj, similar to targets.vim
      keymaps = {
        -- You can use the capture groups defined in textobjects.scm
        ['aa'] = '@parameter.outer',
        ['ia'] = '@parameter.inner',
        ['af'] = '@function.outer',
        ['if'] = '@function.inner',
        ['ac'] = '@class.outer',
        ['ic'] = '@class.inner',
      },
    },
    move = {
      enable = true,
      set_jumps = true, -- whether to set jumps in the jumplist
      goto_next_start = {
        [']m'] = '@function.outer',
        [']]'] = '@class.outer',
      },
      goto_next_end = {
        [']M'] = '@function.outer',
        [']['] = '@class.outer',
      },
      goto_previous_start = {
        ['[m'] = '@function.outer',
        ['[['] = '@class.outer',
      },
      goto_previous_end = {
        ['[M'] = '@function.outer',
        ['[]'] = '@class.outer',
      },
    },
    swap = {
      enable = true,
      swap_next = {
        ['<leader>a'] = '@parameter.inner',
      },
      swap_previous = {
        ['<leader>A'] = '@parameter.inner',
      },
    },
  },
}

-- Diagnostic keymaps
vim.keymap.set('n', '[d', vim.diagnostic.goto_prev)
vim.keymap.set('n', ']d', vim.diagnostic.goto_next)
vim.keymap.set('n', '<leader>e', vim.diagnostic.open_float)
vim.keymap.set('n', '<leader>q', vim.diagnostic.setloclist)

-- LSP settings.
--  This function gets run when an LSP connects to a particular buffer.
local on_attach = function(_, bufnr)
  -- NOTE: Remember that lua is a real programming language, and as such it is possible
  -- to define small helper and utility functions so you don't have to repeat yourself
  -- many times.
  --
  -- In this case, we create a function that lets us more easily define mappings specific
  -- for LSP related items. It sets the mode, buffer and description for us each time.
  local nmap = function(keys, func, desc)
    if desc then
      desc = 'LSP: ' .. desc
    end

    vim.keymap.set('n', keys, func, { buffer = bufnr, desc = desc })
  end

  nmap('<leader>rn', vim.lsp.buf.rename, '[R]e[n]ame')
  nmap('<leader>ca', vim.lsp.buf.code_action, '[C]ode [A]ction')

  nmap('gd', vim.lsp.buf.definition, '[G]oto [D]efinition')
  nmap('gr', require('telescope.builtin').lsp_references, '[G]oto [R]eferences')
  nmap('gI', vim.lsp.buf.implementation, '[G]oto [I]mplementation')
  nmap('<leader>D', vim.lsp.buf.type_definition, 'Type [D]efinition')
  nmap('<leader>ds', require('telescope.builtin').lsp_document_symbols, '[D]ocument [S]ymbols')
  nmap('<leader>ws', require('telescope.builtin').lsp_dynamic_workspace_symbols, '[W]orkspace [S]ymbols')

  -- See `:help K` for why this keymap
  nmap('K', vim.lsp.buf.hover, 'Hover Documentation')
  nmap('<C-k>', vim.lsp.buf.signature_help, 'Signature Documentation')

  -- Lesser used LSP functionality
  nmap('gD', vim.lsp.buf.declaration, '[G]oto [D]eclaration')
  nmap('<leader>wa', vim.lsp.buf.add_workspace_folder, '[W]orkspace [A]dd Folder')
  nmap('<leader>wr', vim.lsp.buf.remove_workspace_folder, '[W]orkspace [R]emove Folder')
  nmap('<leader>wl', function()
    print(vim.inspect(vim.lsp.buf.list_workspace_folders()))
  end, '[W]orkspace [L]ist Folders')

  -- Create a command `:Format` local to the LSP buffer
  vim.api.nvim_buf_create_user_command(bufnr, 'Format', function(_)
    vim.lsp.buf.format()
  end, { desc = 'Format current buffer with LSP' })
end

-- Enable the following language servers
--  Feel free to add/remove any LSPs that you want here. They will automatically be installed.
--
--  Add any additional override configuration in the following tables. They will be passed to
--  the `settings` field of the server config. You must look up that documentation yourself.
local servers = {
  -- clangd = {},
  -- gopls = {},
  -- pyright = {},
  -- rust_analyzer = {},
  -- tsserver = {},

  sumneko_lua = {
    Lua = {
      workspace = { checkThirdParty = false },
      telemetry = { enable = false },
    },
  },
}

-- Setup neovim lua configuration
require('neodev').setup()
--
-- nvim-cmp supports additional completion capabilities, so broadcast that to servers
local capabilities = vim.lsp.protocol.make_client_capabilities()
capabilities = require('cmp_nvim_lsp').default_capabilities(capabilities)

-- Setup mason so it can manage external tooling
require('mason').setup()

-- Ensure the servers above are installed
local mason_lspconfig = require 'mason-lspconfig'

mason_lspconfig.setup {
  ensure_installed = vim.tbl_keys(servers),
}

mason_lspconfig.setup_handlers {
  function(server_name)
    require('lspconfig')[server_name].setup {
      capabilities = capabilities,
      on_attach = on_attach,
      settings = servers[server_name],
    }
  end,
}

-- Turn on lsp status information
require('fidget').setup()

-- nvim-cmp setup
local cmp = require 'cmp'
local luasnip = require 'luasnip'

cmp.setup {
  snippet = {
    expand = function(args)
      luasnip.lsp_expand(args.body)
    end,
  },
  mapping = cmp.mapping.preset.insert {
    ['<C-d>'] = cmp.mapping.scroll_docs(-4),
    ['<C-f>'] = cmp.mapping.scroll_docs(4),
    ['<C-Space>'] = cmp.mapping.complete(),
    ['<CR>'] = cmp.mapping.confirm {
      behavior = cmp.ConfirmBehavior.Replace,
      select = true,
    },
    ['<Tab>'] = cmp.mapping(function(fallback)
      if cmp.visible() then
        cmp.select_next_item()
      elseif luasnip.expand_or_jumpable() then
        luasnip.expand_or_jump()
      else
        fallback()
      end
    end, { 'i', 's' }),
    ['<S-Tab>'] = cmp.mapping(function(fallback)
      if cmp.visible() then
        cmp.select_prev_item()
      elseif luasnip.jumpable(-1) then
        luasnip.jump(-1)
      else
        fallback()
      end
    end, { 'i', 's' }),
  },
  sources = {
    { name = 'nvim_lsp' },
    { name = 'luasnip' },
  },
}

-- The line beneath this is called `modeline`. See `:help modeline`
-- vim: ts=2 sts=2 sw=2 et

Additional Packages
I have added VimTeX and luasnip-latex-snippets.nvim as recommended by kickstart.nvim in the file ~/.config/nvim/lua/custom/plugins.lua:
return function(use)
  use "lervag/vimtex"
  use {
    "iurimateus/luasnip-latex-snippets.nvim",
    requires = { "L3MON4D3/LuaSnip", "lervag/vimtex" },
    config = function()
      require'luasnip-latex-snippets'.setup()
    end,
    ft = "tex",
  }
end

Customized settings
in ~/.config/nvim/after/plugin/defaults.lua
require'nvim-treesitter.configs'.setup {
  highlight = {
    -- `false` will disable the whole extension
    enable = true,

    -- NOTE: these are the names of the parsers and not the filetype. (for example if you want to
    -- disable highlighting for the `tex` filetype, you need to include `latex` in this list as this is
    -- the name of the parser)
    -- list of language that will be disabled
    disable = { "latex" },

  },
}

vim.g.tex_flavor = 'latex' -- IMPORTANT FOR snippets when using an empty file

local luasnip = require('luasnip')
luasnip.config.set_config {
    history = true,
    updateevents = 'TextChanged,TextChangedI',
}

However, no snippets are available when I edit a LaTeX file:
$ nvim demo.tex
:LuaSnipListAvailable
:lua require"luasnip.extras.snippet_list".open()
{
  all = {},
  tex = {}
}

What did I miss?

Not sure. I can't try rn, but could you try not lazy loading the plugin?
Remove ft = "tex" from packer.

authors: iurimateus kiryph


text:
Evaluation of existing SCT methods

In this PR, we evaluate the SCT methods for MS lesion segmentation:

sct_deepseg_lesion
sct_deepseg PSIR/STIR
sct_deepseg MP2RAGE

We perform evaluation on the test split of the MSD dataset and on the external dataset.

Reviewed ! Ready to be merged !

source: gharchive/pull-request

repo: ivadomed/ms-lesion-agnostic

license: MIT


text:
[FR] Support for vim mode commands "x", "p"

Currently, it doesn't work with vim mode.

I have set clipboard=unnamed  " Use system clipboard in my .obsidian.vimrc

repo: ivan-lednev/obsidian-persistent-links


text:
Is there a way to access the socket that emitted event?

I need to broadcast whatever changes happened from user1 to user2 (working on the same document) , i couldn't access the socket that emitted the event i'm pretty sure i'm missing something. Thanks in advance.

+1 here

authors: abdousfayhi odufuwa-segun


text:
ci(release): 3.0.1 [skip ci]

Automated changes by create-pull-request GitHub action

:tada: This PR is included in version 3.0.2 :tada:
The release is available on:

GitHub release
npm package (@latest dist-tag)

Your semantic-release bot :package::rocket:

repo: ivangabriele/bhala


text:
extendDictionary is not switching translations properly

Version
5.24.1
Describe the bug
If creating en-US as an extension of en, via extendDictionary, the locale switcher is not switching between en and en-US:
https://user-images.githubusercontent.com/84905165/222242546-a487a4a9-519e-436e-a56b-ded3c88a1299.mp4
Reproduction
Use the svelteKit example app (https://github.com/ivanhofer/typesafe-i18n-demo-sveltekit) and update all dependencies (ncu -u) and add en-US:

Logs
No response
Config
No response
Additional information
No response

My bad. I assumed lodash.merge works in an immutable way. But instead it alters the orginal object. I will need to find a replacement for this line: https://github.com/ivanhofer/typesafe-i18n/blob/main/packages/utils/src/extendDictionary.mts#L24

It seems merge({}, obj1, obj2) is the solution.

Should be fixed in version 5.24.3. Thanks for reporting this issue.

Thanks for the quick fix!