o pi @sHddlZddlZddlZddlmZddlmZGdddejjZ dS)N)is_multichannel)&MultichannelAudioNotSupportedExceptioncsLeZdZdZdZ d dededeffdd Zd de j efd d Z Z S) RandomCropz2Crop the audio to predefined length in max_length.Tseconds max_length sampling_ratemax_length_unitcsNtt|||_|dkrt|j||_dS|dkr#t||_dStd)a :param max_length: length to which samples are to be cropped. :sampling_rate: sampling rate of input samples. :max_length_unit: defines the unit of max_length. "seconds": Number of seconds "samples": Number of audio samples rsamplesz.max_length_unit must be "samples" or "seconds"N)superr__init__rint num_samples ValueError)selfrrr  __class__c/home/ubuntu/.local/lib/python3.10/site-packages/torch_audiomentations/augmentations/random_crop.pyr s zRandomCrop.__init__NcCs>|p|j}|dur tdt|dkrtd|jj|St|jdkr*tdt |rI|jd|jdkr=td|j sIt d |jj|jd|j krXtd |St d|jd|j |jdf}t j|jd|jd|j f|jd }t|D]\}}|ddddd|||||j f||<q|S) Nzsample_rate is requiredrz(An empty samples tensor was passed to {}ztorch-audiomentations expects input tensors to be three-dimensional, with dimension ordering like [batch_size, num_channels, num_samples]. If your audio is mono, you can use a shape like [batch_size, 1, num_samples].rzMultichannel audio must have channels first, not channels last. In other words, the shape must be (batch size, channels, samples), not (batch_size, samples, channels)z3{} only supports mono audio, not multichannel audioz&audio length less than cropping length)device)r RuntimeErrorlenwarningswarnformatr__name__shapersupports_multichannelrrtorchrandintemptyr enumerate unsqueeze)rr r sample_rate start_indicessamples_croppedisamplerrrforward!sJ    " zRandomCrop.forward)r)N) r __module__ __qualname____doc__rfloatr strr typingOptionalr* __classcell__rrrrrsr) r r0r(torch_audiomentations.utils.multichannelrcore.transforms_interfacernnModulerrrrrs