Colab报错

/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI
Use Language: en_US
2023-06-05 08:45:52.699775: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-06-05 08:45:54.602041: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
Running on local URL:  http://<IP_ADDRESS>:7860
Running on public URL: https://c75a05a3a9ed8fa300.gradio.live
This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run gradio deploy from Terminal to deploy to Spaces (https://huggingface.co/spaces)
start preprocess
['trainset_preprocess_pipeline_print.py', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/dataset/sunyanzi', '40000', '2', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi', 'False']
end preprocess
start preprocess
['trainset_preprocess_pipeline_print.py', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/dataset/sunyanzi', '40000', '2', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi', 'False']
end preprocess
['extract_f0_print.py', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi', '2', 'harvest']
todo-f0-1261
todo-f0-1260
f0ing,now-0,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/0_0.wav
f0ing,now-0,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/0_1.wav
f0ing,now-252,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/15_17.wav
f0ing,now-252,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/15_18.wav
f0ing,now-504,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/20_58.wav
f0ing,now-504,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/20_57.wav
f0ing,now-756,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/27_50.wav
f0ing,now-756,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/27_5.wav
f0ing,now-1008,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/3_21.wav
f0ing,now-1008,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/3_20.wav
f0ing,now-1260,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/9_9.wav
['extract_f0_print.py', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi', '2', 'harvest']
todo-f0-1261
f0ing,now-0,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/0_0.wav
todo-f0-1260
f0ing,now-0,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/0_1.wav
f0ing,now-252,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/15_17.wav
f0ing,now-252,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/15_18.wav
f0ing,now-504,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/20_58.wav
f0ing,now-504,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/20_57.wav
f0ing,now-756,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/27_50.wav
f0ing,now-756,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/27_5.wav
f0ing,now-1008,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/3_21.wav
f0ing,now-1008,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/3_20.wav
f0ing,now-1260,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/9_9.wav
2023-06-05 08:51:52.421884: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
['extract_feature_print.py', 'cuda:0', '1', '0', '0', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi', 'v1']
/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi
load model(s) from hubert_base.pt
2023-06-05 08:51:56 | INFO | fairseq.tasks.hubert_pretraining | current directory is /content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI
2023-06-05 08:51:56 | INFO | fairseq.tasks.hubert_pretraining | HubertPretrainingTask Config {'_name': 'hubert_pretraining', 'data': 'metadata', 'fine_tuning': False, 'labels': ['km'], 'label_dir': 'label', 'label_rate': 50.0, 'sample_rate': 16000, 'normalize': False, 'enable_padding': False, 'max_keep_size': None, 'max_sample_size': 250000, 'min_sample_size': 32000, 'single_target': False, 'random_crop': True, 'pad_audio': False}
2023-06-05 08:51:56 | INFO | fairseq.models.hubert.hubert | HubertModel Config: {'_name': 'hubert', 'label_rate': 50.0, 'extractor_mode': default, 'encoder_layers': 12, 'encoder_embed_dim': 768, 'encoder_ffn_embed_dim': 3072, 'encoder_attention_heads': 12, 'activation_fn': gelu, 'layer_type': transformer, 'dropout': 0.1, 'attention_dropout': 0.1, 'activation_dropout': 0.0, 'encoder_layerdrop': 0.05, 'dropout_input': 0.1, 'dropout_features': 0.1, 'final_dim': 256, 'untie_final_proj': True, 'layer_norm_first': False, 'conv_feature_layers': '[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 2', 'conv_bias': False, 'logit_temp': 0.1, 'target_glu': False, 'feature_grad_mult': 0.1, 'mask_length': 10, 'mask_prob': 0.8, 'mask_selection': static, 'mask_other': 0.0, 'no_mask_overlap': False, 'mask_min_space': 1, 'mask_channel_length': 10, 'mask_channel_prob': 0.0, 'mask_channel_selection': static, 'mask_channel_other': 0.0, 'no_mask_channel_overlap': False, 'mask_channel_min_space': 1, 'conv_pos': 128, 'conv_pos_groups': 16, 'latent_temp': [2.0, 0.5, 0.999995], 'skip_masked': False, 'skip_nomask': False, 'checkpoint_activations': False, 'required_seq_len_multiple': 2, 'depthwise_conv_kernel_size': 31, 'attn_type': '', 'pos_enc_type': 'abs', 'fp16': False}
move model to cuda
all-feature-2521
all-feature-done
['extract_f0_print.py', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi', '2', 'harvest']
todo-f0-1261
f0ing,now-0,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/0_0.wav
todo-f0-1260
f0ing,now-0,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/0_1.wav
f0ing,now-252,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/15_17.wav
f0ing,now-252,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/15_18.wav
f0ing,now-504,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/20_58.wav
f0ing,now-504,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/20_57.wav
f0ing,now-756,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/27_50.wav
f0ing,now-756,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/27_5.wav
f0ing,now-1008,all-1260,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/3_21.wav
f0ing,now-1008,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/3_20.wav
f0ing,now-1260,all-1261,-/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi/1_16k_wavs/9_9.wav
['extract_feature_print.py', 'cuda:0', '1', '0', '0', '/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi', 'v1']
/content/drive/MyDrive/Retrieval-based-Voice-Conversion-WebUI/logs/sunyanzi
load model(s) from hubert_base.pt
move model to cuda
all-feature-2521
all-feature-done
2023-06-05 08:52:04.399134: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:jaxlib.mlir._mlir_libs:Initializing MLIR with module: _site_initialize_0
DEBUG:jaxlib.mlir._mlir_libs:Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._site_initialize_0' from '/usr/local/lib/python3.10/dist-packages/jaxlib/mlir/_mlir_libs/_site_initialize_0.so'>
DEBUG:jax._src.path:etils.epath found. Using etils.epath for file I/O.
INFO:numexpr.utils:NumExpr defaulting to 2 threads.
2023-06-05 08:52:11.796595: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:jaxlib.mlir._mlir_libs:Initializing MLIR with module: _site_initialize_0
DEBUG:jaxlib.mlir._mlir_libs:Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._site_initialize_0' from '/usr/local/lib/python3.10/dist-packages/jaxlib/mlir/_mlir_libs/_site_initialize_0.so'>
DEBUG:jax._src.path:etils.epath found. Using etils.epath for file I/O.
INFO:numexpr.utils:NumExpr defaulting to 2 threads.
INFO:sunyanzi:{'train': {'log_interval': 200, 'seed': 1234, 'epochs': 20000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 5, 'fp16_run': True, 'lr_decay': 0.999875, 'segment_size': 12800, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'max_wav_value': 32768.0, 'sampling_rate': 40000, 'filter_length': 2048, 'hop_length': 400, 'win_length': 2048, 'n_mel_channels': 125, 'mel_fmin': 0.0, 'mel_fmax': None, 'training_files': './logs/sunyanzi/filelist.txt'}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 10, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'use_spectral_norm': False, 'gin_channels': 256, 'spk_embed_dim': 109}, 'model_dir': './logs/sunyanzi', 'experiment_dir': './logs/sunyanzi', 'save_every_epoch': 5, 'name': 'sunyanzi', 'total_epoch': 20, 'pretrainG': 'pretrained/f0G40k.pth', 'pretrainD': 'pretrained/f0D40k.pth', 'version': 'v1', 'gpus': '0', 'sample_rate': '40k', 'if_f0': 1, 'if_latest': 0, 'save_every_weights': '0', 'if_cache_data_in_gpu': 0}
INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0
INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes.
/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py:560: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
warnings.warn(_create_warning_msg(
gin_channels: 256 self.spk_embed_dim: 109
INFO:sunyanzi:loaded pretrained pretrained/f0G40k.pth pretrained/f0D40k.pth

2023-06-05 08:52:20.763214: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:jaxlib.mlir._mlir_libs:Initializing MLIR with module: _site_initialize_0
DEBUG:jaxlib.mlir._mlir_libs:Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._site_initialize_0' from '/usr/local/lib/python3.10/dist-packages/jaxlib/mlir/_mlir_libs/_site_initialize_0.so'>
DEBUG:jax._src.path:etils.epath found. Using etils.epath for file I/O.
INFO:numexpr.utils:NumExpr defaulting to 2 threads.
2023-06-05 08:52:28.830347: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:jaxlib.mlir._mlir_libs:Initializing MLIR with module: _site_initialize_0
DEBUG:jaxlib.mlir._mlir_libs:Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._site_initialize_0' from '/usr/local/lib/python3.10/dist-packages/jaxlib/mlir/_mlir_libs/_site_initialize_0.so'>
DEBUG:jax._src.path:etils.epath found. Using etils.epath for file I/O.
INFO:numexpr.utils:NumExpr defaulting to 2 threads.
2023-06-05 08:52:34.309728: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:jaxlib.mlir._mlir_libs:Initializing MLIR with module: _site_initialize_0
DEBUG:jaxlib.mlir._mlir_libs:Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._site_initialize_0' from '/usr/local/lib/python3.10/dist-packages/jaxlib/mlir/_mlir_libs/_site_initialize_0.so'>
DEBUG:jax._src.path:etils.epath found. Using etils.epath for file I/O.
INFO:numexpr.utils:NumExpr defaulting to 2 threads.
2023-06-05 08:52:40.451118: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:jaxlib.mlir._mlir_libs:Initializing MLIR with module: _site_initialize_0
DEBUG:jaxlib.mlir._mlir_libs:Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._site_initialize_0' from '/usr/local/lib/python3.10/dist-packages/jaxlib/mlir/_mlir_libs/_site_initialize_0.so'>
DEBUG:jax._src.path:etils.epath found. Using etils.epath for file I/O.
INFO:numexpr.utils:NumExpr defaulting to 2 threads.
/usr/local/lib/python3.10/dist-packages/torch/functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:862.)
return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]
/usr/local/lib/python3.10/dist-packages/torch/functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:862.)
return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]
min value is  tensor(-1.0989)
max value is  tensor(1.2246)
min value is  tensor(-1.1836)
max value is  tensor(1.0707)
/usr/local/lib/python3.10/dist-packages/torch/functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:862.)
return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]
/usr/local/lib/python3.10/dist-packages/torch/functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:862.)
return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]
max value is  tensor(1.2129)
min value is  tensor(-1.1116)
max value is  tensor(1.1650)
min value is  tensor(-1.1816)
max value is  tensor(1.1181)
min value is  tensor(-1.1390)
max value is  tensor(1.0994)
max value is  tensor(1.1771)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.1204)
max value is  tensor(1.0762)
max value is  tensor(1.2162)
max value is  tensor(1.1389)
max value is  tensor(1.0749)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.1479)
max value is  tensor(1.0918)
min value is  tensor(-1.1337)
max value is  tensor(1.1785)
min value is  tensor(-1.2318)
max value is  tensor(1.1816)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.1317)
max value is  tensor(1.1538)
min value is  tensor(-1.0723)
max value is  tensor(1.1246)
min value is  tensor(-1.2251)
min value is  tensor(-1.1592)
max value is  tensor(1.1165)
min value is  tensor(-1.1731)
min value is  tensor(-1.1229)
min value is  tensor(-1.0963)
min value is  tensor(-1.2180)
max value is  tensor(1.1446)
min value is  tensor(-1.0891)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.1103)
min value is  tensor(-1.1464)
max value is  tensor(1.1567)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.1220)
max value is  tensor(1.2041)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.0971)
min value is  tensor(-1.2690)
max value is  tensor(1.2498)
min value is  tensor(-1.1623)
min value is  tensor(-1.1263)
min value is  tensor(-1.1001)
min value is  tensor(-1.1442)
max value is  tensor(1.2262)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.1773)
max value is  tensor(1.1556)
max value is  tensor(1.1277)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
max value is  tensor(1.1607)
max value is  tensor(1.1267)
min value is  tensor(-1.1379)
min value is  tensor(-1.1027)
min value is  tensor(-1.0971)
max value is  tensor(1.0908)
max value is  tensor(1.0760)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.2573)
max value is  tensor(1.1159)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.0978)
max value is  tensor(1.1246)
min value is  tensor(-1.2838)
max value is  tensor(1.1162)
max value is  tensor(1.2531)
min value is  tensor(-1.1992)
max value is  tensor(1.1382)
min value is  tensor(-1.1170)
max value is  tensor(1.1204)
max value is  tensor(1.0775)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
max value is  tensor(1.1929)
max value is  tensor(1.1294)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.2433)
max value is  tensor(1.1529)
min value is  tensor(-1.1060)
min value is  tensor(-1.2651)
max value is  tensor(1.3001)
min value is  tensor(-1.1731)
max value is  tensor(1.1153)
min value is  tensor(-1.3167)
min value is  tensor(-1.0878)
min value is  tensor(-1.0872)
max value is  tensor(1.0733)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
max value is  tensor(1.1423)
min value is  tensor(-1.1139)
max value is  tensor(1.2035)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
max value is  tensor(1.1416)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
max value is  tensor(1.0954)
min value is  tensor(-1.1304)
max value is  tensor(1.1341)
min value is  tensor(-1.3094)
max value is  tensor(1.3143)
max value is  tensor(1.0962)
min value is  tensor(-1.2575)
max value is  tensor(1.0763)
min value is  tensor(-1.2838)
max value is  tensor(1.1162)
min value is  tensor(-1.2032)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
min value is  tensor(-1.1482)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
max value is  tensor(1.1629)
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
obj = _ForkingPickler.dumps(obj)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
File "/usr/local/lib/python3.10/dist-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
df = multiprocessing.reduction.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
return resource_sharer.DupFd(fd)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in init
self._id = _resource_sharer.register(send, close)
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
self._start()
File "/usr/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
self._listener = Listener(authkey=process.current_process().authkey)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 448, in init
self._listener = SocketListener(address, family, backlog)
File "/usr/lib/python3.10/multiprocessing/connection.py", line 591, in init
self._socket.bind(address)
OSError: [Errno 38] Function not implemented

TF-TRT Warning: Could not find TensorRT
感觉是不是显卡的问题？

me too.

我用web方式训练时，也报如下错误，不知如何解决？

did anyone find a workaround?

+1，所有依赖正确安装，运行go-web后，前两步数据集处理和特征提取是可以正常运行的，就是训练会报errno38的错误，后面我试着去把python版本改到3.8.10，但还是同样的报错，可见应该不是python版本的问题？看报错日志是生成converter这步出了问题？（没能找到解决方法，作为一点补充）

I have similar problem in WSL2 and Docker.
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/multiprocessing/queues.py", line 244, in _feed
    obj = _ForkingPickler.dumps(obj)
  File "/usr/local/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
    cls(buf, protocol).dump(obj)
  File "/usr/local/lib/python3.10/site-packages/torch/multiprocessing/reductions.py", line 370, in reduce_storage
    df = multiprocessing.reduction.DupFd(fd)
  File "/usr/local/lib/python3.10/multiprocessing/reduction.py", line 198, in DupFd
    return resource_sharer.DupFd(fd)
  File "/usr/local/lib/python3.10/multiprocessing/resource_sharer.py", line 53, in __init__
    self._id = _resource_sharer.register(send, close)
  File "/usr/local/lib/python3.10/multiprocessing/resource_sharer.py", line 76, in register
    self._start()
  File "/usr/local/lib/python3.10/multiprocessing/resource_sharer.py", line 126, in _start
    self._listener = Listener(authkey=process.current_process().authkey)
  File "/usr/local/lib/python3.10/multiprocessing/connection.py", line 448, in __init__
    self._listener = SocketListener(address, family, backlog)
  File "/usr/local/lib/python3.10/multiprocessing/connection.py", line 591, in __init__
    self._socket.bind(address)
OSError: [Errno 95] Operation not supported

Traceback (most recent call last):
  File "/usr/local/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap
    self.run()
  File "/usr/local/lib/python3.10/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "/app/train_nsf_sim_cache_sid_load_pretrain.py", line 228, in run
    train_and_evaluate(
  File "/app/train_nsf_sim_cache_sid_load_pretrain.py", line 358, in train_and_evaluate
    for batch_idx, info in data_iterator:
  File "/usr/local/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 633, in __next__
    data = self._next_data()
  File "/usr/local/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1328, in _next_data
    idx, data = self._get_data()
  File "/usr/local/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1284, in _get_data
    success, data = self._try_get_data()
  File "/usr/local/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1145, in _try_get_data
    raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str)) from e
RuntimeError: DataLoader worker (pid(s) 149) exited unexpectedly

Related issues: https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/issues/635 https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/issues/286

I bought a google colab subscription to be able to use RVC, and yet I get this annoying error!
OSError: [Errno 38] Function not implemented.
I don't have any background in coding,  just a frustrated musician. how can I solve this?

I stumbled upon this as well. For me ut turned out that cloning the repo into a mounted network drive (google drive) did not work. When I cloned the repo to the colab native filesystem it worked as expected.


No laptop preset for pulseeffects branch

When using fedora 38 with easy effects, the laptop preset is what i used. But now on Ubuntu 22.04 with pulse effects I cant seem to get a similar present even in the pulseeffects branch. Hopefully you could provide me with the laptop preset for easy effects that works for pulse effects as well thanks!

I'm not the author of the laptop preset. To make it compatible with the older PulseEffects version, there are two ways:

Load the preset on modern EasyEffects and take note of what plugins are loaded and with what settings, then replicate it with PulseEffects (easy)
Manually inspect the JSON files and map the settings (more difficult)

Anyway I'm on Ubuntu 22.04 too but I installed PipeWire and EasyEffects, it's just plain better, so if you can I would advise to join the PipeWire gang xD


Powertoys Peek has fluctuating cpu usage on laptop.

Microsoft PowerToys version
0.70.1
Installation method
Microsoft Store
Running as admin
None
Area(s) with issue?
Peek
Steps to reproduce
The PowerToys Peek is using more that 1% cpu sometimes and the cpu usage fluctuates. It might drain my laptop battery faster . I hope you will look into the matter if it is an issue.
✔ Expected Behavior
No response
❌ Actual Behavior
No response
Other Software
No response

same problem here
https://github.com/microsoft/PowerToys/assets/78062003/6240449c-e10c-4e66-bc67-572cf56396e2

Same issue in 0.74.0 on Windows 10, installed via EXE installer.

Are you still experiencing this issue? /needinfo

The issue is fixed on my laptop. Thank you.


Add files via upload

@Quyetsama Please provide us with:

the school official website URL
the school street address, including city and country
an URL of a page on the official website where the school offers an IT-related long-term (>1 year) course
a proof, which shows that the school recognizes the domain you are submitting as an official email domain for the students.

@Quyetsama You might miss my previous comment. Please react.

@Quyetsama I am sorry, this request remains unanswered for a while. I have to close it without merging. Please reopen and comment if you have an update regarding the aforementioned issue. Thank you for your understanding!


python manage.py train

I noticed the update allowing for training from external corpora, updated my chatterbot install and pulled the newest version of chatterbot, but when I try to train the chatbot by running the command python manage.py train as instructed in docs/django/training.rst, I just get the error Unknown command: 'train'.  Is there any additional step I am missing?

Sorry, when reinstalling the new Chatterbot, I forgot to run setup.py.  Issue is resolved now.

Awesome, glad this got resolved.


return 0 always

I have installed the package, setup the config file, but every time I run the command it returns 0
dd(Currency::conv('USD', 'KES', 10, 2));

Hi, @josiahke
what 'api-source' are you using?
Some sources have less currencies than others, ex: I don't think the European Central bank has Kenyan Shilling. The other sources should.

Oh I just realized another possible caveat: if you change api-sources you might have to clear your cache. Cache is enabled per default.

Oh I just realized another possible caveat: if you change api-sources you might have to clear your cache. Cache is enabled per default.

I forgot: each source is cached independently so that should not be the issue.
I did just test The European Central Bank as a source, and it was returning 0 bytes. An hour later it was working as normal. 🤔


Little error in GetBounds() ?

On line 3365 of clipper.engine.cpp, you have:
			if (pt.x < result.left) result.left = pt.x;
			else if (pt.x > result.right) result.right = pt.x;
If the very first vertex is also the right-most one, that "else" prevents result.right from being updated, and the final bounding box is incorrect. Same thing for result.bottom, two lines below.
(caught that little error through my C rewrite producing slightly different results)

Thanks, I'm was actually aware of that one, and considered this more a documentation error since this function is always called with multiple vertices. However, having said that, and on further reflection now, it is conceivable that a valid path could still always trigger the first condition so what I though was a minor optimization is probably unsafe.


[Snyk] Upgrade @types/react from 18.2.22 to 18.2.24

This PR was automatically created by Snyk using the credentials of a real user.Snyk has created this PR to upgrade @types/react from 18.2.22 to 18.2.24.
:information_source: Keep your dependencies up-to-date. This makes it easier to fix existing vulnerabilities and to more quickly identify and fix newly disclosed vulnerabilities when they affect your project.

The recommended version is 2 versions ahead of your current version.
The recommended version was released 22 days ago, on 2023-10-01.

Release notes

Package name: @types/react

18.2.24 - 2023-10-01

18.2.23 - 2023-09-26

18.2.22 - 2023-09-18

    from @types/react GitHub release notes

Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open upgrade PRs.
For more information:
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Windows 10 E5 license is missing

WIN10_VDA_E5: "WINDOWS 10 ENTERPRISE E5"

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 7c245452-161d-89a1-c026-99a0721cf071
Version Independent ID: 16dec59a-eb83-1837-4efd-4645e7aeaed2
Content: Product names and service plan identifiers for licensing - Azure AD
Content Source: articles/active-directory/users-groups-roles/licensing-service-plan-reference.md
Service: active-directory
Sub-service: users-groups-roles
GitHub Login: @ajayanti1
Microsoft Alias: arjay

@Oppedijk  Thank you for your feedback. We would check and update the document if necessary.

@ajayanti1 Aruna, could you check if Windows 10 Enterprise E5 needs to be added to the document ?

Added.

#please-close


Unify workflows for main push and pull requests

Originally I wanted to do much fore in this PR but since I'm not contracted by ASERVO anymore, I've reduced this PR to the absolute minimum that was originally planned...

This is a sensible change. Approved.


Nvidia usage is untested

My main system has an AMD GPU, so I can't test if the Nvidia parts of this actually work

Closing this in favor of tracking in #21


Cascading parameter values not working on IE

Dear ,
The Cascading parameter values enhancement  functionality not working well on IE browser , its keep saying updating parameters message.
Thanks

Hi @basharald, I just tested this out on a sample report of my own in IE 11.332.15063.0 and was not able to duplicate an issue. Could you give me more details about the version of IE that you're using? Possibly screenshots of what's happening as well as maybe the setup of parameters and cascading parameters so that I could try to duplicate it on my side?
Thanks,
Alan


Request for documentation

We notice in the code, the integration of verify Api but there's not example of code in readme of how to use it.
Same for the connection request widget.
Thanks

Hello @Fabrice-Fabio! Regarding the verify implementation you actually don't have to do nothing big, you can access the verifyContex (aka the result of the verification process) in the SessionProposalEvent. https://docs.walletconnect.com/web3wallet/verify?platform=flutter#implementation
_web3Wallet!.onSessionProposal.subscribe((SessionProposalEvent? args) {
  if (args != null) {
    final scamApp = args.verifyContext?.validation.scam;
    final invalidApp = args.verifyContext?.validation.invalid;
    final validApp = args.verifyContext?.validation.valid;
    final unknown = args.verifyContext?.validation.unknown;
  }
});

I'll update the example ASAP.
Regarding the "connection request widget", what do you mean exactly?

Thanks Alfreedom,
I've update the readme by creating a pull request, please check it there and merge it if it suit you : https://github.com/WalletConnect/WalletConnectFlutterV2/pull/227/commits
Thanks.


Doodle

🛠 Fixes Issue (Number)
closes #1568
✅ Check List (Check all the applicable boxes)

[x] My code doesn't break any part of the project
[x] This PR does not contain plagiarized content.
[x] My Addition/Changes works properly and matches the overall repo pattern.
[x] The title of my pull request is a short description of the requested changes.

📷 Screenshots

https://github.com/swapnilsparsh/30DaysOfJavaScript/assets/136808696/85be90ba-1717-4459-9cf5-1a0793ce425f

Please check now.

hey @swapnilsparsh please review

@AnanyaJain25 Check it here, without controlling it is getting played and speed is very fast as it should gradually increase when you play along the game.

@AnanyaJain25 Check it here, without controlling it is getting played and speed is very fast as it should gradually increase when you play along the game.

Sir without controlling it cannot be played there might be some combination of tiles which are consecutive which is why the doodle is jummping continously However i have done some changes and also added instruction panel now is it fine?
https://github.com/swapnilsparsh/30DaysOfJavaScript/assets/136808696/c55019be-e7c6-4dbc-9454-eed3a71f9fac

Spacing should be there to avoid automatic jump on different tiles.

that is random only ..sometimes they come closer in beginning and later you will get spaced also  sometimes from the beginning only those are spaced. I dont really understand the problem?

@AnanyaJain25 Check it here, without controlling it is getting played and speed is very fast as it should gradually increase when you play along the game.

Sir without controlling it cannot be played there might be some combination of tiles which are consecutive which is why the doodle is jummping continously However i have done some changes and also added instruction panel now is it fine?
Doodle.Jump.-.Google.Chrome.2024-06-11.07-23-26.1.mp4
what exactly is the problem there are automatic jumps if the tile is just above another and that happen in the game also apart from it we have to move when tiles are apart

Doodle.Jump.-.Google.Chrome.2024-06-11.07-23-26.1.mp4

what exactly is the problem there are automatic jumps if the tile is just above another and that happen in the game also apart from it we have to move when tiles are apart

You have to make a proper distance between two tiles to avoid automatic jump

@AnanyaJain25 Any update ?


Fix constant overriding in set_sreams function

This change is

Coverage increased (+1.08%) to 79.756% when pulling abacfaa666d9d5cf4660eef483834857b96276a9 on Scandie:a693933915022330_pytest_error into f6dc1d908aec27470735301ba6427d1f348cce43 on openprocurement:ea_core.


Set where merged contact is saved.

For those of us using Flock it wouldbe great to be able to set it as the place merged contacts are stored - rather than as a google contact.
https://github.com/WhisperSystems/Flock
I honestly have no idea how difficult this would be so it's just a suggestion.

This shouldn't be needed at all. Merging barely marks 2 contacts as being identical. This information is phone-local as far as I know.
As such there shouldn't be a need for this. Could you please elaborate what you are trying to do? I like whisper systems and would like to fix possible issues....
Am 11. Februar 2015 19:00:58 MEZ, schrieb padraic<EMAIL_ADDRESS>
For those of us using Flock it wouldbe great to be able to set it as
the place merged contacts are stored - rather than as a google contact.
https://github.com/WhisperSystems/Flock
I honestly have no idea how difficult this would be so it's just a
suggestion.

Reply to this email directly or view it on GitHub:
https://github.com/rtreffer/ContactMerger/issues/6

--
Diese Nachricht wurde von meinem Android-Mobiltelefon mit K-9 Mail gesendet.

Hi,
apolgies for the delay in responding.
At the moment I have Flock installed on my nexus 5 but haven't removed the different google apps and also use google contacts.
I ran Contact Merger and afterwards noticed that I had a number of '(No name)' contacts. All of which are Flock rather than google contacts.
I assumed that this was because Contact Manager savd the unified contact to google contacts and left an empty Flock contact. From what you ahve said I assume I was mistaken.


Refactor phase component registration

Pharos::Phases.components shouldn't contain anything but Pharos::Phases::Components, so:
      register_component(
        Pharos::Phases::Component.new(
          name: 'cri-o', version: Pharos::CRIO_VERSION, license: 'Apache License 2.0'
        )
      )

can become:
      register_component 'cri-o', version: Pharos::CRIO_VERSION, license: 'Apache License 2.0'

Also noticed kubeadm wasn't registered and cfssl version was hardcoded in the shell script and registered separately in the configure cfssl phase.

Partially happened in #327

Yep, the part about not having to register_component(Pharos::Phases::Component.new(..)).
Too conflicty, rewriting if relevant.


Add support for nodeSelector constraint for Helm DaemonSet template

/lgtm
Thanks for working on this!

/approve
(wow bot works ty whoever did that)


Progress bar - further PR review

This is a PR submitted by @drsimonmiles, there was a couple of bit of clean up I wanted to do as well as a more careful reading of the InterleavedComputation.

The low hanging clean up tasks are done and on this branch - nothing worth worrying about / reviewing.
I've moved onto the InterleavedComputation code. The code works, I've run the demo, the code looks neat and well written, and follows the conventions used in Indigo.
There is a couple of things I'd like to dig into further:

There are no tests - there might be good reasons for that but I'd like to try writing some to find out. Indigo is supposed to be testable. :-)
System.currentTimeMillis is used to time the operations, but this is a side effect, which may make testing difficult. Would like to try using gameTime.delta instead if possible.

Update on this PR.
This stuff looks easy enough but is actually quite fiddly.
Applying LongCompute to the progress bar example project appears to do the right thing if the tolerance is set to 0.05, which seems very small. Anything bigger and the units to attempt just climbs, anything much smaller and it only ever does one unit at a time. This seems a really unintuitive number, should we expose it? Is it problem (factorisation in the example) specific? Is it just broken in some unexpected way?

I've just tried LongCompute on my crowds simulation, where the computations are 'real' path searches. With the default tolerance of 0.05, the progress updates smoothly as with InterleavedComputation. Setting it to 0.1, the progress is glitchy with pauses and jumps. So I would conclude it is not a feature of the problem: the path search computations are individually much faster than the factorisation computations in the example.
If 0.05 always works, then I guess it is fine for it to be effectively hard-coded and hidden! But I don't know why that value would be the right one, so I'm not confident to say it is universal...

If 0.05 always works, then I guess it is fine for it to be effectively hard-coded and hidden! But I don't know why that value would be the right one, so I'm not confident to say it is universal...

I feel the same. Thank you for testing it! When I get a bit more free head space I'm going to have one more go at it and if I fail, hardcode to 0.05 and merge it.
Question 1: LongCompute is supposed to be an improved version of InterleavedComputation to allow for testing. Do you agree that that's the case or do you feel InterleavedComputation does anything better?
Question 2: Which name do you like better? I'm on the fence. LongCompute is shorter, InterleavedComputation is more accurate. :-) (or alternatively, can you think of another name?)

I'm probably biased by it being my own code, but I like that the original doesn't require any hidden quantities. It just takes the duration of the first step as the likely duration of future steps and adjusts later by averaging if that turns out to be inaccurate. If the client sets the relative size of the tasks appropriately, this should be a good approximation and give smooth interleaving in all cases, so it feels like the client has more straightforward control than adjusting LongCompute's tolerance. Clearly it is better to use GameTime.delta rather than currentTimeMillis for testability and probably other reasons, so if we could take that from LongCompute (and I don't see why we can't), that would be the ideal in my eyes.

In my mind, LongCompute better describes what it actually is as an artefact, while InterleavedComputation gives more clue as to how to use it. On the whole, I prefer LongCompute, i.e. better to be declarative (as well as short). The way it is used might be different in future versions of Indigo (e.g. maybe hiding the way it is called rather than the client having to do something each FrameTick), so InterleavedComputation might end up being a meaningless name while LongCompute would still be accurate.

When I have the brain capacity, I'm happy to try changing InterleavedComputation to use GameTime.delta.

Ok, if you're feeling inspired to give it a try I'm happy to merge that version instead of this one. There was some other clean up bits I did in this pr that we might need to recreate, but we can worry about that later.
The acid test is whether you can test it mind you. 😉

With regret, I'm going to close this PR down. It's a long way behind at this point, I still there's something here though.


Accumulating haproxy-check.sh and curl zombies

I'm seeing zombies from haproxy-check.sh and curl with release 0.29. I've about 125 of them on one node, mostly curl, some haproxy-check.sh. I'm currently not sure under what circumstances they occur but they don't seem to increase regularly. Regardless of the reason for this I think that kube-keepalived-vip either needs a zombie reaper (something like https://github.com/ramr/go-reaper) or kube-keepalived-vip needs to be started by tini or dumb-init. If we agree on one way or the other I could provide code.

I'm going to implement the Go option now.

@elemental-lf please use dumb-init


Cross platform build failed

When I tried to build from OS X for Linux, it says:
$ GOOS=linux GOARCH=amd64 go install
# github.com/mattn/go-sqlite3
../../../mattn/go-sqlite3/sqlite3.c:241 unknown #: if
../../../mattn/go-sqlite3/sqlite3.c:256 unknown #: if
../../../mattn/go-sqlite3/sqlite3.c:296 unknown #: if
../../../mattn/go-sqlite3/sqlite3.c:309 unknown #: if
../../../mattn/go-sqlite3/sqlite3.c:339 unknown #: if
../../../mattn/go-sqlite3/sqlite3.c:342 unknown #: elif
../../../mattn/go-sqlite3/sqlite3.c:343 macro redefined: SQLITE_INT_TO_PTR
../../../mattn/go-sqlite3/sqlite3.c:344 macro redefined: SQLITE_PTR_TO_INT
../../../mattn/go-sqlite3/sqlite3.c:345 unknown #: elif
../../../mattn/go-sqlite3/sqlite3.c:346 macro redefined: SQLITE_INT_TO_PTR
../../../mattn/go-sqlite3/sqlite3.c:347 macro redefined: SQLITE_PTR_TO_INT
too many errors

Hi,
I would like to compile to arm on osx.
With the following command:
GOOS=linux GOARCH=arm CGO_ENABLED=1 go build -o foo main.go
I get:
runtime/cgo
clang: error: argument unused during compilation: '-mno-thumb'
Thanks for every help :-)

Hi, this is how I cross compile binary for freescale/arm on i386 architecture:
CC=/tools/m1sdk-tiny-1.0.0/toolchain/gcc-4.4.4-glibc-2.11.1-multilib-1.0/arm-fsl-linux-gnueabi/bin/arm-linux-gcc CGO_ENABLED=1 GOOS=linux GOARCH=arm go build main.go

Thanks!

I have the same problem on osx, attempting to build linux/amd64 version for my program.
ld: unknown option: --build-id=none
clang: error: linker command failed with exit code 1 (use -v to see invocation)

try with export CC=gcc.

@mattn Hello,
$ CC=gcc-4.9 GOOS=linux GOARCH=amd64 CGO_ENABLED=1 godep go build                                                                                1 ↵ (go1.5.2<EMAIL_ADDRESS># runtime/cgo
gcc-4.9: warning: couldn't understand kern.osversion '14.3.0
# runtime/cgo
gcc-4.9: warning: couldn't understand kern.osversion '14.3.0
# runtime/cgo
gcc-4.9: warning: couldn't understand kern.osversion '14.3.0
/Users/hit9/github/oo/go/src/runtime/cgo/cgo.go:52:19: fatal error: errno.h: No such file or directory
compilation terminated.
godep: go exit status 2

are you doing cross-compiling? when you need to use cross-compiler not host-compiler.

@mattn Thanks.

Having a little problem Mac OS and not sure what's the cause :/
Command used
CGO_ENABLED=1 CC=gcc-5 GOARM=7 GOARCH=arm GOOS=linux go build
Error countered:
# runtime/cgo
gcc-5: error: unrecognized command line option '-marm'

Any hints please?

Ran into similar issue cross-compiling a linux binary on osx. Near as I can tell in my mini investigation, cross-compiling would work except that osx's implementation of the linker tool (ld) doesn't understand the --build-id=none flag, which is where it chokes. Both gcc and clang attempt to pass this flag along to ld regardless of what you do with the CC, GCO_ENABLED, etc environment variables, so it's simply not gonna work.
I have a simple work around using docker which will hopefully help others who don't want to go through the trouble of recompiling a linux version of ld for osx:
Note: Naturally a docker workaround will require that you have docker installed :)
@mattn If you think it's reasonable feel free to add it to your readme where it will be more visible. I can make a PR as well if you like.
docker run --rm -v $GOPATH:/go -w /go/src/path/to/app golang:latest go build -v

This will put your executable in the expected place, in this case, /go/src/path/to/app.
You just need to update that /go/src/path/to/app part to be your actual directory containing your app, for example, /go/src/path/github.com/username/awesomeSqliteApp
If you want this working in a script like I have (for example I use a python fabric script to build and deploy automatically), you can do the following to prep docker on osx, since otherwise it requires the "Docker Quickstart Terminal":
eval $(docker-machine env default)
docker run --rm -v $GOPATH:/go -w /go/src/path/to/app golang:latest go build -v

In theory this should work on any platform that can run docker, though I've only tried on osx.

@jeffbmartinez Thanks. Using docker is one of the way to do cross-compiling. So it's useful. If possible, could you please send me pull-request to update README.md?

Leaving this comment in the hopes it helps someone else in 2016.
Cross compiling Linux (Debian Jessie amd64) -> Windows (amd64) and OSX (amd64) worked for me with the following:
To Windows:
apt-get install gcc_mingw64
env CGO_ENABLED=1 GOOS=windows GOARCH=amd64 CC=x86_64-w64-mingw32-gcc go build $appname
To OSX:
Follow instructions at https://github.com/tpoechtrager/osxcross to build apple cross compiler
env CGO_ENABLED=1 GOOS=darwin GOARCH=amd64 CC=o64-clang go build $appname

@cprevallet Thank you, ubuntu is work.
apt-get install gcc-mingw-w64

for documentation purposes:
in order to cross compile 32bit ubuntu on a 64bit ubuntu system libc6-dev-i386 is required.
Setting `CC="gcc -m32" works.

@jeffbmartinez use docker run --rm with sqlite3 , i cannot build , sth is wrong ,  go build -v is nothing with hold..

Thanks @jeffbmartinez, it got me on the right track to get cross compilation working for Raspberry Pi 3. In case it's useful for anyone else, here's the Dockerfile I'm using for OSX:
FROM dockcross/linux-armv7:latest

# Largely copied from the official Golang image Dockerfile

RUN set -eux; \
  wget -O go.tgz "https://golang.org/dl/go1.9.1.linux-amd64.tar.gz"; \
  tar -C /usr/local -xzf go.tgz; \
  rm go.tgz; \
  export PATH="/usr/local/go/bin:$PATH"; \
	go version

ENV GOPATH /go
ENV PATH $GOPATH/bin:/usr/local/go/bin:$PATH

RUN mkdir -p "$GOPATH/src" "$GOPATH/bin" && chmod -R 777 "$GOPATH"
WORKDIR $GOPATH

And the command to build a package from the package directory:
PWD=$(pwd)
PROJECT="/go${PWD/"$GOPATH"/}"

docker run --rm -v $GOPATH:/go -w $PROJECT \
  -e "CGO_ENABLED=1" -e "GOARCH=arm" \
  go-arm-linux:latest go build .

After some searching, I found a way to cross compilation on OSX:

Install cross-compiler toolchains

brew install FiloSottile/musl-cross/musl-cross
brew install mingw-w64

Build with -ldflags "-linkmode external -extldflags -static"

Ex:
GOOS=linux GOARCH=amd64 CC="/usr/local/bin/x86_64-linux-musl-gcc" CGO_ENABLED=1 go build -ldflags "-linkmode external -extldflags -static" -o [OUTPUT_BINARY]

Reference: https://blog.filippo.io/easy-windows-and-linux-cross-compilers-for-macos/


TemplateNotFound: components/tabs.html

Describe the bug
TemplateNotFound: components/tabs.html
To Reproduce
My dataframe is confidential and cannot be provided here. But I ran the titanic.py file [from pandas-profiling/examples/titanic/titanic.py], completely unmodified, and got the same error.
Version information:
pandas==0.24.2
numpy==1.16.2
pandas-profiling==2.1.1
...etc.
Please see pip_freeze.txt file attached.
pip_freeze.txt
Additional context
Please see the screenshot and detailed information of the error I got in the attached PDF.
BugReport.pdf
I used pandas profiling last week, and it was working perfectly. When I pip installed it today to my new computer, somehow this error kept coming up. I am inexperienced in programming and I apologize in advance if it ends up being my mistake when using the package. Thank you!

Thank you so much!


TaxiBookingBloc

The superclass 'Bloc<TaxiBookingEvent, TaxiBookingState>' doesn't have a zero argument constructor.
Try declaring a zero argument constructor in 'Bloc<TaxiBookingEvent, TaxiBookingState>', or declaring a constructor in TaxiBookingBloc that explicitly invokes a constructor in 'Bloc<TaxiBookingEvent, TaxiBookingState>'.dart(no_default_super_constructor)

did u get it resolved ?

Its because , current version of bloc is 6.0.1, please replace bloc variable with cubit . It works

i didn't get it

Any solution to this issue?

error: The superclass 'Bloc<TaxiBookingEvent, TaxiBookingState>' doesn't have a zero argument constructor. (no_default_super_constructor at [taxi_app] lib\bloc\taxi_booking_bloc.dart:14)

Manually set version numbers of flutter bloc and bloc packages to 4.0.0
flutter_bloc: ^4.0.0
bloc: ^4.0.0


chore(common): Use Box::leak rather than mem::forget

Overview
Uses Box::leak to ensure that the files that are constructed from raw
file descriptors are kept alive for the static lifetime of the program,
rather than mem::forget.

[!WARNING]
This pull request is not mergeable via GitHub because a downstack PR is open. Once all requirements are satisfied, merge this PR as a stack on Graphite.
Learn more

#180  👈
#179
main

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Join @clabby and the rest of your teammates on  Graphite


check concepts by the CALC group

closing following discussion in https://github.com/lexibank/transnewguineaorg/issues/2


[bug]: Update directory for temperature file for x86 environments

VM System and eOS details:
root@embassy-butch-ribs:/home/start9# embassy-cli git-info
b885022a17b80c63c04e452a622e3b3987aa8bc9
root@embassy-butch-ribs:/home/start9# uname -a
Linux embassy-butch-ribs 5.10.0-19-amd64 #1 SMP Debian 5.10.149-2 (2022-10-21) x86_64 GNU/Linux

Error message:
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]: 2022-11-15T15:05:13.753869Z ERROR embassy::system: Could not get initial temperature: Filesystem I/O Error: /sys/class/thermal/thermal_zone0/temp: No such file or directory (os error 2)
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]: 2022-11-15T15:05:13.753890Z DEBUG embassy::system: Error { source:
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]:    0: /sys/class/thermal/thermal_zone0/temp: No such file or directory (os error 2)
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]:    1: No such file or directory (os error 2)
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]: Location:
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]:    /home/rust/src/libs/models/src/errors.rs:369
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]:   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SPANTRACE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]:    0: embassy::system::get_temp
Nov 15 15:05:13 embassy-butch-ribs embassyd[14231]:       at src/system.rs:507

Location on VM:
root@embassy-butch-ribs:/home/start9# ls -la /sys/class/thermal
total 0
drwxr-xr-x  2 root root 0 Nov 15 13:57 .
drwxr-xr-x 51 root root 0 Nov 15 13:57 ..
lrwxrwxrwx  1 root root 0 Nov 15 13:57 cooling_device0 -> ../../devices/virtual/thermal/cooling_device0
lrwxrwxrwx  1 root root 0 Nov 15 13:57 cooling_device1 -> ../../devices/virtual/thermal/cooling_device1
lrwxrwxrwx  1 root root 0 Nov 15 13:57 cooling_device2 -> ../../devices/virtual/thermal/cooling_device2
lrwxrwxrwx  1 root root 0 Nov 15 13:57 cooling_device3 -> ../../devices/virtual/thermal/cooling_device3

From @dr-bonez "That's intentional. It used to spam the logs. There is no temperature for the vm. But I want it to still log once if there's an issue on other devices so we can know if there's a problem"


[community] Update Crunchy's icon

Use svg+xml format in Crunchy's postgresql operator

Fixes #230
/cc @davi5e

Closing since the changes were added by another PR

Which PR?
Just tried the operator again, same error... Maybe not merged yet?


OPT-IML weights for smaller models

Hello,
Are you planning to release the OPT-IML weights for smaller OPT models (below 6.7B)?
This might be of help for those who have limited resources.
Thanks in advance,

@sriniiyer I'm looking forward to the OPT-IML weights for the OPT-6.7B model!


normalization issue in measure_heom_distance()

In the following function:
https://github.com/SepShr/MLCSHE/blob/cc5018836483c45b498e35d8bc4eff32a81e194f/CCEA.py#L594
I wonder if it's okay to normalize the data inside the function.
For example, the value of 1 can be normalized to 0.1 when X has the maximum value of 10 but 0.5 when X has the maximum value of 2.
This is not an issue if the calculated normalized distance is not compared to those from other Xs. Is this the case?

Issue acb74e86d0d79cf4d14e3f4f03a90557783362e3 addresses solves this issue by using absolute range of numeric values not the range available from data.


Bhavika Sachdeva:

What is your issue related to ?

[ ] Testing/Research

Description
What if both the partners miss on the routines ? you can have a reward system which would support healthy competition along with adherance to the routines.

@Bhavika2210 Can you elaborate your issue. Like how you want to add the reward system

Closing this issue due to inactivity


Icc develop

I added ICC profile support (as a field and a standalone model), histograms, admin graphs; refactored some of the spec architecture to allow non-image pipelines like numpy arrays, and some other things. Not sure if you guys are still developing this but thought you might want to have a look. Salud

With the release of ImageKit 1.0, the codebase has now significantly changed. I'd really love to see the continuance of this fork, since it had an awesome amount of features. So I'd encourage you to keep working on it!

Mr Veloso: thank you for your encouragement, and your work on this project -- django-imagekit has been one of the most useful Django packages I've found in the course of my development.
I have spun off two open projects while working on my fork of the earlier incarnation of django-imagekit:

django-signalqueue is asynchronous processing via the Django signal interface; and
django-delegate is a utility that simplifies the definition of queryset methods

I had a look at the new API -- it looks great, and very clean. One feature I've been working on that might be immediately of interest to you and other django-imagekit hackers is the method I came up with for writing Cython implementations of ImageProcessors that run automatically in place of the pure-Python processing code when present.
Additionally a number of my other features can be rolled into the 1.0 architecture easily:

Metadata (ICCMetaField, EXIFMetaField, hash fields, etc) which are already field-based implementations
Histograms and histogram channels are also implemented as fields (the implementation depends on NumPy)
The admin displays for histograms and ICC data

I am curious if any of these are of particular interest to you and your fellow developers.
Thanks again for all your work on django-imagekit!
-fish

@fish2000, with the new API, I'd say go for it. Matt has said a few times that he would like to see a library of processors and other features for the new ImageKit and I share his sentiment. If you'd like to take some time to get to know the new API and port those features over, we'd really appreciate it. :)


Describe default configuration in README

Is your feature request related to a problem? Please describe.
Currently I have no idea which option in the actions is "default". During testing I enabled download_translations: true and I got sidetracked from the actions uploading sources for some reason, and also requiring GITHUB_TOKEN environment variable for... something.
With no idea what the default configurations are I have no idea which one I need to override to have the action do exactly what I would like it to.
Describe the solution you'd like
Document the default configuration of the actions workflow in README or wiki.
Describe alternatives you've considered
No alternatives I have considered at this time.
Additional context
You can find my workflow below. (Renamed from .yml due to limitation of GitHub upload.)
crowdin-commit.txt

I just found out EXAMPLES.md exists; while this does help the particular workflow uploaded above, I'd still like to know what the defaults are for future reference.

agree - defaults are necessary, this made for some costly mistakes I had to clean up this week


fix implicitNotFound message of Plated

before:
scala> monocle.function.Plated.children(100)
<console>:11: error: Could not find an instance of Plated[{A}], please check Monocle instance location policy to find out which import is necessary
       monocle.function.Plated.children(100)
                                       ^

after:
scala> monocle.function.Plated.children(100)
<console>:11: error: Could not find an instance of Plated[Int], please check Monocle instance location policy to find out which import is necessary
       monocle.function.Plated.children(100)
                                       ^

:+1:

Thanks! :+1: