o %ݫih" @sdZddlZddlZddlmZmZddlmZddlm Z ddl m Z eddGd d d Z d d Z d dZeddGdddZdddejfddZdeddde eidf ddZdS)z.possibly_consider) rr rminrrr listrange) r'target_batch_numelmax_batch_sizer(r)randint_generator bufferlen min_index max_indexr*r!to_addrr&rindices_around_random_pivot)s(-     r5iFc csFg} |r t|fi|}|D]h} |dur |dur || |} n|dur)| |} n |dur2|| } ntd|dur>| |ksF|durG| |krGqt| | } t| | t| |krw|| }g}t|ddD] }| |} || j qd||Vq| s| r|| }g}t|ddD] }| |} || j q||V| s|dSdSdS)a%Produce batches from a sorted buffer This function keeps a sorted buffer of the incoming samples. The samples can be filtered for min/max length. An external sampler is used to choose samples for each batch, which allows different dynamic batching algorithms to be used. Arguments --------- data : iterable An iterable source of samples, such as an IterableDataset. len_key : str, None The key in the sample dict to use to fetch the length of the sample, or None if no key should be used. len_fn : callable Called with sample[len_key] if len_key is not None, else sample. Needs to return the sample length as an integer. min_sample_len : int, None Discard samples with length lower than this. If None, no minimum is applied. max_sample_len : int, None Discard samples with length larger than this. If None, no maximum is applied. buffersize : int The size of the internal sorted buffer. The buffer is always filled up before yielding a batch of samples. collate_fn : callable Called with a list of samples. This should return a batch. By default, using the SpeechBrain PaddedBatch class, which works for dict-like samples, and pads any tensors. sampler_fn : callable Called with the sorted data buffer. Needs to return a list of indices, which make up the next batch. By default using ``indices_around_random_pivot`` sampler_kwargs : dict Keyword arguments, passed to sampler_fn. drop_end : bool After the data stream is exhausted, should batches be made until the data buffer is exhausted, or should the rest of the buffer be discarded. Without new samples, the last batches might not be efficient to process. Note: you can use ``.repeat`` on `webdataset` IterableDatasets to never run out of new samples, and then use `speechbrain.dataio.dataloader.LoopedLoader` to set a nominal epoch length. Yields ------ Batches Nz.Must specify at least one of len_key or len_fnT)reverse) r ValueErrorrbisectinsortrsortedpopr r )r len_keylen_fnmin_sample_lenmax_sample_len buffersize collate_fn sampler_fnsampler_kwargsdrop_endr'sampler itemindices batch_listirrrdynamic_bucketed_batchsH;         rJ)rr8random dataclassesrr functoolsrtypingrspeechbrain.dataio.batchrrrrrrandintr5rrJrrrrs8     ]