Transducer Decoding: avoid alignments to store non-blank confidence#15315
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Transducer Decoding: avoid alignments to store non-blank confidence#15315
alignments to store non-blank confidence#15315Conversation
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
…es in `torch_impl`. Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
alignments to store non-blank confidencealignments to store non-blank confidence
alignments to store non-blank confidencealignments to store non-blank confidence
alignments to store non-blank confidencealignments to store non-blank confidence
# Conflicts: # nemo/collections/asr/parts/utils/rnnt_utils.py
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: artbataev <artbataev@users.noreply.github.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
…into vbataev/rnnt_decoding_refactor
8 tasks
8 tasks
lilithgrigoryan
requested changes
Jan 27, 2026
| self.reset_cuda_graphs_state() | ||
| return True | ||
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| # fusion models-related methods |
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Are these changes related to the PR? Seems like this is more related to per-stream biasing PR
8 tasks
# Conflicts: # nemo/collections/asr/parts/submodules/transducer_decoding/rnnt_label_looping.py # nemo/collections/asr/parts/submodules/transducer_decoding/tdt_label_looping.py
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
Signed-off-by: Vladimir Bataev <vbataev@nvidia.com>
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What does this PR do ?
Store non-blank confidence in
BatchedHypsto avoid costlyalignmentsstructure for confidence when possible (if blank label confidence is ignored):alignmentsmakes decoding significantly slowerAdditionally, this PR unifies and simplifies RNN-T and TDT decoding.
Collection: [ASR]
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