Document Cuda dependencies #65

chrisspen · 2024-11-13T23:42:07Z

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

The text was updated successfully, but these errors were encountered:

chrisspen · 2024-11-13T23:51:48Z

I also tried installing:

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

but that had no effect on the error.

chrisspen · 2024-11-13T23:55:15Z

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 · 2024-11-16T10:23:19Z

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.

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Document Cuda dependencies #65

Document Cuda dependencies #65

chrisspen commented Nov 13, 2024

chrisspen commented Nov 13, 2024

chrisspen commented Nov 13, 2024

BreezeWhite commented Nov 16, 2024 •

edited

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Document Cuda dependencies #65

Document Cuda dependencies #65

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chrisspen commented Nov 13, 2024

chrisspen commented Nov 13, 2024

chrisspen commented Nov 13, 2024

BreezeWhite commented Nov 16, 2024 • edited Loading

BreezeWhite commented Nov 16, 2024 •

edited

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