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A simple CRDNN based ASR model for my own understanding of how ASR works and are trained. (Work in progress) If anyone finds any error or have any suggestion please do let me know.

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asr asr-model librispeech pytorch pytorch-implementation pytorch-tutorial speech-recognition supervised-learning timit timit-dataset

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DefaultCPUAllocator: not enough memory:

Hi, when I run this repository code in Google collab, I am getting the following error:
[Traceback (most recent call last): File "main.py", line 81, in <module> training_model1(device, model, pipeline, no_of_batches, total, batch_audios, batch_transcriptions ) File "E:\PhD\Summer 2023\CRDNN Based ASR\training.py", line 31, in training_model1 output = model(padded_audios) File "E:\PhD\Summer 2023\CRDNN Based ASR\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\PhD\Summer 2023\CRDNN Based ASR\model\model.py", line 119, in forward x = self.layer1(x) File "E:\PhD\Summer 2023\CRDNN Based ASR\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\PhD\Summer 2023\CRDNN Based ASR\venv\lib\site-packages\torch\nn\modules\conv.py", line 313, in forward return self._conv_forward(input, self.weight, self.bias) File "E:\PhD\Summer 2023\CRDNN Based ASR\venv\lib\site-packages\torch\nn\modules\conv.py", line 309, in _conv_forward return F.conv1d(input, weight, bias, self.stride, RuntimeError: [enforce fail at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\c10\core\impl\alloc_cpu.cpp:72] data. DefaultCPUAllocator: not enough memory: you tried to allocate 31157667840 bytes.](url)

How can I solve this error?

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