针对您遇到的 NameError: name 'dataloader' is not defined 错误,我们可以按照您提供的 tips 来逐步分析和解决问题。以下是详细的解答: 1. 确认dataloader是否应该被定义 首先,您需要确认在您的代码中是否确实需要使用到 dataloader 这个变量。如果 dataloader 是您程序中用于加载数据的必要组件,那么它确实需要被定义...
if shuffle is not False: raise ValueError( "DataLoader with IterableDataset: expected unspecified " "shuffle option, but got shuffle={}".format(shuffle)) elif sampler is not None: # See NOTE [ Custom Samplers and IterableDataset ] raise ValueError( "DataLoader with IterableDataset: expected unsp...
setImmediate || setTimeout doesn't work and it throws setImmediate is not defined in this case, so we should check setImmediate with typeof. And some environments like Cloudflare Workers don't allow you to set setTimeout directly to another variable. https://github.com/graphql/dataloader/...
Expected Behavior DataLoader should gracefully fall back to setTimeout if setImmediate is not supported on the browser. Current Behavior It crashes with an error ReferenceError: setImmediate is not defined. Possible Solution dataloader/s...
if batch_sampler is not None: # 如果你设置了batch_size不是1,或者你设置了shuffle或者你设置了sampler,或者你设置了drop_last,这些都与batch_sampler是互斥的,总结一句话就是:你只要设置了batch_sampler就不需要设置batch_size了,因为你设置了batch_sampler就已经告诉PyTorch框架你的batch_size和以什么样的方式去...
Often there is not a 1:1 mapping of your batch loaded keys to the values returned.For example, let's assume you want to load users from a database, you could probably use a query that looks like this:SELECT * FROM User WHERE id IN (keys) ...
current_epochis not synchronized with dataloader and dataset in dataloader state, when num_workers is not defined fromlitdataimportStreamingDataLoader,StreamingDatasetdataset=StreamingDataset("my_optimized_dataset")dataloader=StreamingDataLoader(dataset,num_workers=0,batch_size=4)for_indataloader:passprint("...
_sampler_iter is None: self._reset() data = self._next_data() self._num_yielded += 1 if self._dataset_kind == _DatasetKind.Iterable and \ self._IterableDataset_len_called is not None and \ self._num_yielded > self._IterableDataset_len_called: warn_msg = ("Length of Iterable...
The PyTorch DataLoader supports supports both map-style and iterable-style datasets -- the latter, IterableDataset, is used for data streams, and hence its length is unknown, and as such, has no __len__() method implemented. This is not unlike tf.data.Dataset, which also does not require...
This is not quite as loose in a Java implementation as Java is a type safe language. A batch loader function is defined asBatchLoader<K, V>meaning for a key of typeKit returns a value of typeV. It can't just return someExceptionas an object of typeV. Type safety matters. ...