move the batch to device Args: device (torch.device, str): torch device Returns: DataProto: the current Data

Return a tensor with the input `shape` as a view into the 1-D data starting at `start_index`.

Return a tensor with the input `shape` as a view into the 1-D data starting at `start_index`.

Returns arr[start] + ... + arr[end] :param start: (int) start position of the reduction (must be >= 0) :param end: (int) end

move the batch to device Args: device (torch.device, str): torch device Returns: DataProto: the current Data

If distributed is initialized, print only on rank 0.

Set browser variables to corresponding link, page HTML for URL

Pop a subset of the DataProto via `batch_keys` and `meta_info_keys` Args: batch_keys (list, optional): a list of strings indicati

Put the engine to sleep. The engine should not process any requests. The caller should guarantee that no requests are being processed

Pop a subset of the DataProto via `batch_keys` and `meta_info_keys` Args: batch_keys (list, optional): a list of strings indicati

Returns min(arr[start], ..., arr[end]) :param start: (int) start position of the reduction (must be >= 0) :param end: (int)

Wrapper for `receive` handler for performing search action on current page

Converts a sequence of ids in a string, using the tokenizer and vocabulary with options to remove special tokens and clean up tokeniz

Close the environment and release resources.

Split the batch among dim=0 into chunks. The meta_info is passed to each DataProto after split. Args: chunks (int): the number of

Redirect to the search page with the given session ID

overrides ai2thor.controller.Controller.step() for smooth navigation and goal_condition updates

Concat a list of DataProto. The batch is concatenated among dim=0. The meta_info is assumed to be identical and will use the first one.

Create a DataProto from a dict of tensors. This assumes that 1. All the tensor in tensors have the same dim0 2. Only dim0 is the batch

Execute text actions and return the next state, rewards, done flags, and additional information. Parameters: - text_

Copy src from hdfs to local if src is on hdfs or directly return src. If cache_dir is None, we will use the default cache dir of the system. Note

Split the batch among dim=0 into chunks. The meta_info is passed to each DataProto after split. Args: chunks (int): the number of

Copy src from hdfs to local if src is on hdfs or directly return src. If cache_dir is None, we will use the default cache dir of the system. Note

Write the sequence of args, with no separators, to the console and output files (if you've configured an output file).

Union with another DataProto. Union batch and meta_info separately. Throw an error if - there are conflict keys in batch and they are

Union with another DataProto. Union batch and meta_info separately. Throw an error if - there are conflict keys in batch and they are

bit complicated to avoid memory explosion when high arity predicates take * num_obs ^ arity space. take space for individual arg types only; * must

Select a subset of the DataProto via batch_keys and meta_info_keys Args: batch_keys (list, optional): a list of strings indicatin

Create a huggingface pretrained tokenizer which correctness handles eos and pad tokens. Args: name (str): The name of the tokenizer.