我用torch.save会报错,直接DataSource.write_pickle(model),会提示<trackeback: AttributeError: Can't pickle local object 'get_cosine_schedule_with_warmup.<locals>.lr_lambda'>解答已经解决了,model.schedulers = None就可以保存了标签AttributeErrorTransformer 评论 已经解决了,model.schedulers = None就可以...
AttributeError: Can't pickle local object 'DataLoader.init..' Anyone had similar issues ? read pickle cant pickle lambda functions but I wonder why the default implementation of pytorch is made this way ? Environment OS: Windows Python version: 3.6 PyTorch version: 1.1 CUDA/cuDNN version: 10...
save as dict'date':datetime.now().isoformat(),'version':__version__}try:importdillaspickleexcept(ImportError,AssertionError):importpickle# Save last, best and deletetorch.save(ckpt,self.last,pickle_module=pickle)ifself.best_fitness==self.fitness:torch.save(ckpt,self.best,pickle_module=pickle)...
m.save("m.pt") Example (using ``@torch.jit.ignore(drop=True)`` on a method): .. testcode:: import torch import torch.nn as nn class MyModule(nn.Module): @torch.jit.ignore(drop=True) def training_method(self, x):
.. note:: If you use ``torch.save`` on one process to checkpoint the module, and ``torch.load`` on some other processes to recover it, make sure that ``map_location`` is configured properly for every process. Without ``map_location``, ``torch.load`` would recover the module to ...
With PyTorch 2.1 (torch-neuronx), HF Trainer API’s use of XLA function .mesh_reduce causes "EOFError: Ran out of input" or "_pickle.UnpicklingError: invalid load key, '!'" errors during Neuron Parallel Compile. To work-around this issue, you can add the following code snippet (after...
Checklist The issue exists after disabling all extensions The issue exists on a clean installation of webui The issue is caused by an extension, but I believe it is caused by a bug in the webui The issue exists in the current version of ...
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("imf.tflite") # Convert TensorFlow model to TFLite # converter = tf.lite.TFLiteConverter.from_keras_model(tf_model) # tflite_model = converter.convert() # Save the TFLite model # with open('model.tflite', 'wb') as f: # f.write(tflite_model) # print("TFLite model saved as...
When selecting this in accelerate config: Do you wish to optimize your script with torch dynamo?[yes/NO]:yes ---Which dynamo backend wo...