Loading fairseq/data/token_block_dataset.py +2 −2 Changes for fairseq/data/token_block_dataset.py: 2 added lines, 2 removed lines. Original line number Diff line number Diff line Loading @@ -47,7 +47,7 @@ class TokenBlockDataset(torch.utils.data.Dataset): self.slice_indices = [block_at(i) for i in range(length)] elif break_mode == 'complete': assert sizes is not None and sum(sizes) == len(tokens) assert sizes is not None and sum(sizes) == len(tokens), '{} != {}'.format(sum(sizes), len(tokens)) tok_idx = 0 sz_idx = 0 curr_size = 0 Loading @@ -62,7 +62,7 @@ class TokenBlockDataset(torch.utils.data.Dataset): if curr_size > 0: self.slice_indices.append((tok_idx, tok_idx + curr_size)) elif break_mode == 'eos': assert sizes is not None and sum(sizes) == len(tokens) assert sizes is not None and sum(sizes) == len(tokens), '{} != {}'.format(sum(sizes), len(tokens)) curr = 0 for sz in sizes: # skip samples with just 1 example (which would be just the eos token) Loading fairseq/tasks/language_modeling.py +1 −1 Changes for fairseq/tasks/language_modeling.py: 1 added line, 1 removed line. Original line number Diff line number Diff line Loading @@ -48,7 +48,7 @@ class LanguageModelingTask(FairseqTask): path = os.path.join(self.args.data, split) if self.args.raw_text and IndexedRawTextDataset.exists(path): ds = IndexedRawTextDataset(path, self.dictionary) tokens = ds.tokens_list tokens = [t for l in ds.tokens_list for t in l] elif not self.args.raw_text and IndexedInMemoryDataset.exists(path): ds = IndexedInMemoryDataset(path, fix_lua_indexing=True) tokens = ds.buffer Loading Loading
fairseq/data/token_block_dataset.py +2 −2 Changes for fairseq/data/token_block_dataset.py: 2 added lines, 2 removed lines. Original line number Diff line number Diff line Loading @@ -47,7 +47,7 @@ class TokenBlockDataset(torch.utils.data.Dataset): self.slice_indices = [block_at(i) for i in range(length)] elif break_mode == 'complete': assert sizes is not None and sum(sizes) == len(tokens) assert sizes is not None and sum(sizes) == len(tokens), '{} != {}'.format(sum(sizes), len(tokens)) tok_idx = 0 sz_idx = 0 curr_size = 0 Loading @@ -62,7 +62,7 @@ class TokenBlockDataset(torch.utils.data.Dataset): if curr_size > 0: self.slice_indices.append((tok_idx, tok_idx + curr_size)) elif break_mode == 'eos': assert sizes is not None and sum(sizes) == len(tokens) assert sizes is not None and sum(sizes) == len(tokens), '{} != {}'.format(sum(sizes), len(tokens)) curr = 0 for sz in sizes: # skip samples with just 1 example (which would be just the eos token) Loading
fairseq/tasks/language_modeling.py +1 −1 Changes for fairseq/tasks/language_modeling.py: 1 added line, 1 removed line. Original line number Diff line number Diff line Loading @@ -48,7 +48,7 @@ class LanguageModelingTask(FairseqTask): path = os.path.join(self.args.data, split) if self.args.raw_text and IndexedRawTextDataset.exists(path): ds = IndexedRawTextDataset(path, self.dictionary) tokens = ds.tokens_list tokens = [t for l in ds.tokens_list for t in l] elif not self.args.raw_text and IndexedInMemoryDataset.exists(path): ds = IndexedInMemoryDataset(path, fix_lua_indexing=True) tokens = ds.buffer Loading