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BreezeWhite / oemer

End-to-end Optical Music Recognition (OMR) system. Transcribe phone-taken music sheet image into MusicXML, which can be edited and converted to MIDI.
https://breezewhite.github.io/oemer/
MIT License
394 stars 46 forks source link

Document Cuda dependencies #65

Open chrisspen opened 5 days ago

chrisspen commented 5 days ago

This is more of a feature request than bug report. Could you please document all the CUDA libraries that need to be installed? You currently have no documentation for the CUDA libraries you need, and pip install oemer doesn't install any. However, running oemer on any image returns these warnings and finally errors with a traceback:

2024-11-13 23:36:15.264024780 [E:onnxruntime:Default, provider_bridge_ort.cc:1862 TryGetProviderInfo_CUDA] /onnxruntime_src/onnxruntime/core/session/provider_bridge_ort.cc:1539 onnxruntime::Provider& onnxruntime::ProviderLibrary::Get() [ONNXRuntimeError] : 1 : FAIL : Failed to load library libonnxruntime_providers_cuda.so with error: libcudnn.so.9: cannot open shared object file: No such file or directory

2024-11-13 23:36:15.264039748 [W:onnxruntime:Default, onnxruntime_pybind_state.cc:993 CreateExecutionProviderInstance] Failed to create CUDAExecutionProvider. Require cuDNN 9.* and CUDA 12.*. Please install all dependencies as mentioned in the GPU requirements page (https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements), make sure they're in the PATH, and that your GPU is supported.
2280 1612
2024-11-13 23:36:50 Extracting layers of different symbols
2024-11-13 23:36:50.888872869 [E:onnxruntime:Default, provider_bridge_ort.cc:1862 TryGetProviderInfo_CUDA] /onnxruntime_src/onnxruntime/core/session/provider_bridge_ort.cc:1539 onnxruntime::Provider& onnxruntime::ProviderLibrary::Get() [ONNXRuntimeError] : 1 : FAIL : Failed to load library libonnxruntime_providers_cuda.so with error: libcudnn.so.9: cannot open shared object file: No such file or directory

2024-11-13 23:36:50.888888787 [W:onnxruntime:Default, onnxruntime_pybind_state.cc:993 CreateExecutionProviderInstance] Failed to create CUDAExecutionProvider. Require cuDNN 9.* and CUDA 12.*. Please install all dependencies as mentioned in the GPU requirements page (https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements), make sure they're in the PATH, and that your GPU is supported.
2280 1612
2024-11-13 23:38:03 Extracting stafflines
/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/staffline_extraction.py:296: RuntimeWarning: invalid value encountered in divide
  accum_x = accum_x / np.mean(accum_x)
Traceback (most recent call last):
  File "/home/chris/git/oemer/.env/bin/oemer", line 8, in <module>
    sys.exit(main())
             ^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/ete.py", line 280, in main
    mxl_path = extract(args)
               ^^^^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/ete.py", line 171, in extract
    staffs, zones = staff_extract()
                    ^^^^^^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/staffline_extraction.py", line 333, in extract
    zones, *_ = init_zones(staff_pred, splits=splits)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/staffline_extraction.py", line 298, in init_zones
    right_bound = min(max(xs) + 50, staff_pred.shape[1])
                      ^^^^^^^
ValueError: max() arg is an empty sequence

My nvidia-smi reports I have CUDA 12.6 installed, so it's not that I don't have the appropriate system packages available (Ubuntu 24).

And despite the link in the warning to https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements, which indicates that onnxruntime-gpu must be installed, that is infact already installed into my Python virtual environment

chrisspen commented 5 days ago

I also tried installing:

sudo apt-get -y install cudnn cudnn-cuda-12

but that had no effect on the error.

chrisspen commented 5 days ago

Attempting to install oemer[tf] fails even more quickly:

2024-11-13 23:54:05 Extracting staffline and symbols
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1731542045.168313   79636 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1731542045.171138   79636 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
Traceback (most recent call last):
  File "/home/chris/git/oemer/.env/bin/oemer", line 8, in <module>
    sys.exit(main())
             ^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/ete.py", line 280, in main
    mxl_path = extract(args)
               ^^^^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/ete.py", line 131, in extract
    staff, symbols, stems_rests, notehead, clefs_keys = generate_pred(str(img_path), use_tf=args.use_tf)
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/ete.py", line 51, in generate_pred
    staff_symbols_map, _ = inference(
                           ^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/oemer/inference.py", line 42, in inference
    model = tf.keras.models.model_from_json(open(arch_path, "r").read())
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/keras/src/models/model.py", line 752, in model_from_json
    return serialization_lib.deserialize_keras_object(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/keras/src/saving/serialization_lib.py", line 694, in deserialize_keras_object
    cls = _retrieve_class_or_fn(
          ^^^^^^^^^^^^^^^^^^^^^^
  File "/home/chris/git/oemer/.env/lib/python3.11/site-packages/keras/src/saving/serialization_lib.py", line 812, in _retrieve_class_or_fn
    raise TypeError(
TypeError: Could not locate class 'Functional'. Make sure custom classes are decorated with `@keras.saving.register_keras_serializable()`. Full object config: {'class_name': 'Functional', 'config': {'name': 'model', 'layers': [{'class_name': 'InputLayer', 'config': {'batch_input_shape': [None, 256, 256, 3], 'dtype': 'float32', 'sparse': False, 'ragged': False, 'name': 'input_score_48'}, 'name': 'input_score_48', 'inbound_nodes': []}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [7, 7], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d', 'inbound_nodes': [[['input_score_48', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation', 'inbound_nodes': [[['conv2d', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization', 'inbound_nodes': [[['activation', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout', 'inbound_nodes': [[['layer_normalization', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_1', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [2, 2], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_1', 'inbound_nodes': [[['dropout', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_1', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_1', 'inbound_nodes': [[['conv2d_1', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_1', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_1', 'inbound_nodes': [[['activation_1', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_1', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_1', 'inbound_nodes': [[['layer_normalization_1', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_2', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_2', 'inbound_nodes': [[['dropout_1', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_3', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [1, 1], 'strides': [2, 2], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_3', 'inbound_nodes': [[['conv2d', 0, 0, {}]]]}, {'class_name': 'Add', 'config': {'name': 'add', 'trainable': True, 'dtype': 'float32'}, 'name': 'add', 'inbound_nodes': [[['conv2d_2', 0, 0, {}], ['conv2d_3', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_2', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_2', 'inbound_nodes': [[['add', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_2', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_2', 'inbound_nodes': [[['activation_2', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_2', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_2', 'inbound_nodes': [[['layer_normalization_2', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_4', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_4', 'inbound_nodes': [[['dropout_2', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_3', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_3', 'inbound_nodes': [[['conv2d_4', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_3', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_3', 'inbound_nodes': [[['activation_3', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_3', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_3', 'inbound_nodes': [[['layer_normalization_3', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_5', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_5', 'inbound_nodes': [[['dropout_3', 0, 0, {}]]]}, {'class_name': 'Add', 'config': {'name': 'add_1', 'trainable': True, 'dtype': 'float32'}, 'name': 'add_1', 'inbound_nodes': [[['conv2d_5', 0, 0, {}], ['add', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_4', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_4', 'inbound_nodes': [[['add_1', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_4', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_4', 'inbound_nodes': [[['activation_4', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_4', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_4', 'inbound_nodes': [[['layer_normalization_4', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_6', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [2, 2], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_6', 'inbound_nodes': [[['dropout_4', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_5', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_5', 'inbound_nodes': [[['conv2d_6', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_5', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_5', 'inbound_nodes': [[['activation_5', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_5', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_5', 'inbound_nodes': [[['layer_normalization_5', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_7', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_7', 'inbound_nodes': [[['dropout_5', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_8', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [1, 1], 'strides': [2, 2], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_8', 'inbound_nodes': [[['add_1', 0, 0, {}]]]}, {'class_name': 'Add', 'config': {'name': 'add_2', 'trainable': True, 'dtype': 'float32'}, 'name': 'add_2', 'inbound_nodes': [[['conv2d_7', 0, 0, {}], ['conv2d_8', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_6', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_6', 'inbound_nodes': [[['add_2', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_6', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_6', 'inbound_nodes': [[['activation_6', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_6', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_6', 'inbound_nodes': [[['layer_normalization_6', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_9', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_9', 'inbound_nodes': [[['dropout_6', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_7', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_7', 'inbound_nodes': [[['conv2d_9', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_7', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_7', 'inbound_nodes': [[['activation_7', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_7', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_7', 'inbound_nodes': [[['layer_normalization_7', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_10', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_10', 'inbound_nodes': [[['dropout_7', 0, 0, {}]]]}, {'class_name': 'Add', 'config': {'name': 'add_3', 'trainable': True, 'dtype': 'float32'}, 'name': 'add_3', 'inbound_nodes': [[['conv2d_10', 0, 0, {}], ['add_2', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_8', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_8', 'inbound_nodes': [[['add_3', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_8', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_8', 'inbound_nodes': [[['activation_8', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_8', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_8', 'inbound_nodes': [[['layer_normalization_8', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_11', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_11', 'inbound_nodes': [[['dropout_8', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_9', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_9', 'inbound_nodes': [[['conv2d_11', 0, 0, {}]]]}, {'class_name': 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'config': {'name': 'layer_normalization_47', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_47', 'inbound_nodes': [[['activation_41', 0, 0, {}]]]}, {'class_name': 'Concatenate', 'config': {'name': 'concatenate_7', 'trainable': True, 'dtype': 'float32', 'axis': -1}, 'name': 'concatenate_7', 'inbound_nodes': [[['layer_normalization_46', 0, 0, {}], ['layer_normalization_47', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_38', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_38', 'inbound_nodes': [[['concatenate_7', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_46', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [1, 1], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_46', 'inbound_nodes': [[['dropout_38', 0, 0, {}]]]}, {'class_name': 'Add', 'config': {'name': 'add_20', 'trainable': True, 'dtype': 'float32'}, 'name': 'add_20', 'inbound_nodes': [[['conv2d_46', 0, 0, {}], ['add_19', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_42', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_42', 'inbound_nodes': [[['add_20', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_48', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_48', 'inbound_nodes': [[['activation_42', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_39', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_39', 'inbound_nodes': [[['layer_normalization_48', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'conv2d_47', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'conv2d_47', 'inbound_nodes': [[['dropout_39', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_43', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_43', 'inbound_nodes': [[['conv2d_47', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_49', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_49', 'inbound_nodes': [[['activation_43', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_40', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_40', 'inbound_nodes': [[['layer_normalization_49', 0, 0, {}]]]}, {'class_name': 'Conv2DTranspose', 'config': {'name': 'conv2d_transpose_6', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [3, 3], 'strides': [2, 2], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None, 'output_padding': None}, 'name': 'conv2d_transpose_6', 'inbound_nodes': [[['dropout_40', 0, 0, {}]]]}, {'class_name': 'Conv2DTranspose', 'config': {'name': 'conv2d_transpose_7', 'trainable': True, 'dtype': 'float32', 'filters': 128, 'kernel_size': [1, 1], 'strides': [2, 2], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None, 'output_padding': None}, 'name': 'conv2d_transpose_7', 'inbound_nodes': [[['add_20', 0, 0, {}]]]}, {'class_name': 'Add', 'config': {'name': 'add_21', 'trainable': True, 'dtype': 'float32'}, 'name': 'add_21', 'inbound_nodes': [[['conv2d_transpose_6', 0, 0, {}], ['conv2d_transpose_7', 0, 0, {}]]]}, {'class_name': 'Activation', 'config': {'name': 'activation_44', 'trainable': True, 'dtype': 'float32', 'activation': 'relu'}, 'name': 'activation_44', 'inbound_nodes': [[['add_21', 0, 0, {}]]]}, {'class_name': 'LayerNormalization', 'config': {'name': 'layer_normalization_50', 'trainable': True, 'dtype': 'float32', 'axis': [3], 'epsilon': 0.001, 'center': True, 'scale': True, 'beta_initializer': {'class_name': 'Zeros', 'config': {}}, 'gamma_initializer': {'class_name': 'Ones', 'config': {}}, 'beta_regularizer': None, 'gamma_regularizer': None, 'beta_constraint': None, 'gamma_constraint': None}, 'name': 'layer_normalization_50', 'inbound_nodes': [[['activation_44', 0, 0, {}]]]}, {'class_name': 'Dropout', 'config': {'name': 'dropout_41', 'trainable': True, 'dtype': 'float32', 'rate': 0.4, 'noise_shape': None, 'seed': None}, 'name': 'dropout_41', 'inbound_nodes': [[['layer_normalization_50', 0, 0, {}]]]}, {'class_name': 'Conv2D', 'config': {'name': 'prediction', 'trainable': True, 'dtype': 'float32', 'filters': 3, 'kernel_size': [1, 1], 'strides': [1, 1], 'padding': 'same', 'data_format': 'channels_last', 'dilation_rate': [1, 1], 'groups': 1, 'activation': 'softmax', 'use_bias': True, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'name': 'prediction', 'inbound_nodes': [[['dropout_41', 0, 0, {}]]]}], 'input_layers': [['input_score_48', 0, 0]], 'output_layers': [['prediction', 0, 0]]}, 'keras_version': '2.5.0', 'backend': 'tensorflow'}
BreezeWhite commented 3 days ago

I've updated the code and should fixed the problem now. If it still doesn't work, try apt-get install cudnn9-cuda-12 then run again. In my case, that should fix the problem.