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72 lines
2.2 KiB
Python
Executable File
72 lines
2.2 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright (c) 2021 Xiaomi Corporation (authors: Fangjun Kuang)
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#
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# See ../../../../LICENSE for clarification regarding multiple authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import k2
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import torch
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from rnn_lm.dataset import LmDataset, LmDatasetCollate
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def main():
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sentences = k2.RaggedTensor(
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[[0, 1, 2], [1, 0, 1], [0, 1], [1, 3, 0, 2, 0], [3], [0, 2, 1]]
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)
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words = k2.RaggedTensor([[3, 6], [2, 8, 9, 3], [5], [5, 6, 7, 8, 9]])
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num_sentences = sentences.dim0
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sentence_lengths = [0] * num_sentences
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for i in range(num_sentences):
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word_ids = sentences[i]
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# NOTE: If word_ids is a tensor with only 1 entry,
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# token_ids is a torch.Tensor
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token_ids = words[word_ids]
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if isinstance(token_ids, k2.RaggedTensor):
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token_ids = token_ids.values
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# token_ids is a 1-D tensor containing the BPE tokens
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# of the current sentence
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sentence_lengths[i] = token_ids.numel()
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sentence_lengths = torch.tensor(sentence_lengths, dtype=torch.int32)
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indices = torch.argsort(sentence_lengths, descending=True)
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sentences = sentences[indices.to(torch.int32)]
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sentence_lengths = sentence_lengths[indices]
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dataset = LmDataset(
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sentences=sentences,
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words=words,
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sentence_lengths=sentence_lengths,
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max_sent_len=3,
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batch_size=4,
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)
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collate_fn = LmDatasetCollate(sos_id=1, eos_id=-1, blank_id=0)
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dataloader = torch.utils.data.DataLoader(
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dataset, batch_size=1, collate_fn=collate_fn
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)
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for i in dataloader:
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print(i)
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# I've checked the output manually; the output is as expected.
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if __name__ == "__main__":
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main()
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