[ASR] Add optimization util for linear sum assignment algorithm #6349

tango4j · 2023-04-03T02:07:07Z

What does this PR do ?

Add a optimization util file for linear sum assignment (LSA) solver algorithm for online-diarization/multi-speaker-ASR
LSA problem solver is needed for the following tasks in NeMo:
(1) Permutation Invariant Loss (PIL) for diarization model training
(2) Label permutation matching for online speaker diarzation
(3) Concatenated minimum-permutation Word Error Rate (cp-WER) calculation

What is LSA solver algorithm? Google OR-tools LSA Solver

The NeMo linear_sum_assignment function is compared with scipy.optimization.linear_sum_assingment.
In the unit-test for NeMo LSA solver, the result is compared with the scipy version of linear_sum_assignment.

Removing @torch.jit.script decorator in speaker_utils.py since it creates type-errors when the code is not used for production purpose.
Instead, all torch.jit.script required classes and functions are tested in test_diar_utils.py.
Take a look at these tests for checking jit_script = [True/False] and cuda = [True/False] (testing total 4 combinations)
Also refactored some of the functions in online diarization
- replaced scipy LSA solver to NeMo LSA solver in online_clustering.py.
Added a couple of functions in der.py for online diarization DER calculation.
- replaced scipy LSA solver to NeMo LSA solver in der.py.

Collection: [ASR]

Changelog

nemo/collections/asr/metrics/der.py
: replaced scipy LSA solver to NeMo LSA solver in calculate_session_cpWER function.
: Added two functions for online diarization evaluations: get_partial_ref_labels and get_online_DER_stats.
nemo/collections/asr/models/online_diarizer.py
: Made _perform_online_clustering function simpler by moving get_reduced_mat and match_labels into online clustering function.
nemo/collections/asr/parts/utils/offline_clustering.py
: Added laplacian = laplacian.float().to(torch.device('cpu')) to avoid jit-scripted module uses GPU even when CPU is specified or vice-versa. This behavior is always tested/checked in test_diar_utils.py.
nemo/collections/asr/parts/utils/online_clustering.py
: replaced scipy LSA solver to NeMo LSA solver in get_lsa_speaker_mapping function.
: Modified the docstrings of update_speaker_history_buffer to make the example easier.
nemo/collections/asr/parts/utils/optimization_utils.py
: Fully torch-jit-scriptable, linear sum assignment problem solver class and function were added.
nemo/collections/asr/parts/utils/speaker_utils.py
: Removed @torch.jit.script decorators since this creates unnecessary warning messages and type related errors when used without scripting.
tests/collections/asr/test_diar_metrics.py
: Added unit-tests for the newly added function get_partial_ref_labels and get_online_DER_stats.
tests/collections/asr/test_diar_utils.py
: Added tests for offline clustering and online clustering for many different cases including:
[jit-script=True, cuda=True],
[jit-script=True, cuda=False],
[jit-script=False, cuda=True],
[jit-script=False, cuda=False] cases
which is using the torch-jit-scripted NeMo linear_sum_assignment function.

Usage

from nemo.collections.asr.parts.utils.optimization_utils import linear_sum_assignment
#An example cost matrix to be solved
cost_matrix = \
torch.tensor([[7, 6, 2], [6, 2, 1], [5, 6, 8]])
row_ind_nm, col_ind_nm = linear_sum_assignment(cost_matrix)

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…diarization Signed-off-by: Taejin Park <[email protected]>

Signed-off-by: Taejin Park <[email protected]>

for more information, see https://pre-commit.ci

Signed-off-by: Taejin Park <[email protected]>

for more information, see https://pre-commit.ci

Signed-off-by: Taejin Park <[email protected]>

…fix/clus_spk_util_jit

Signed-off-by: Taejin Park <[email protected]>

for more information, see https://pre-commit.ci

Signed-off-by: Taejin Park <[email protected]>

…fix/clus_spk_util_jit

nemo/collections/asr/models/online_diarizer.py

nemo/collections/asr/metrics/der.py

Signed-off-by: Taejin Park <[email protected]>

for more information, see https://pre-commit.ci

Signed-off-by: Taejin Park <[email protected]>

…fix/clus_spk_util_jit

nemo/collections/asr/metrics/der.py

Signed-off-by: Taejin Park <[email protected]>

nemo/collections/asr/metrics/der.py

Signed-off-by: Taejin Park <[email protected]>

for more information, see https://pre-commit.ci

Signed-off-by: Taejin Park <[email protected]>

…fix/clus_spk_util_jit

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nithinraok

minor review. Will do thorough review tomorrow.
Very neat improvement, need to understand better from my end.

nithinraok · 2023-04-07T04:27:48Z

nemo/collections/asr/parts/utils/offline_clustering.py

@@ -552,12 +550,13 @@ def eigDecompose(
            device = torch.cuda.current_device()
        laplacian = laplacian.float().to(device)
    else:
+        laplacian = laplacian.float().to(torch.device('cpu'))
        laplacian = laplacian.float()


why same operation twice?

nithinraok · 2023-04-07T04:28:45Z

nemo/collections/asr/parts/utils/offline_clustering.py

        laplacian = laplacian.float()
    lambdas, diffusion_map = eigh(laplacian)
    return lambdas, diffusion_map


-def eigValueSh(laplacian: torch.Tensor, cuda: bool, device: torch.device = torch.device('cpu')) -> torch.Tensor:
+def eigValueSh(laplacian: torch.Tensor, cuda: bool, device: torch.device) -> torch.Tensor:


why cuda and device? Isn't only one sufficient

This was added long back because there are users setting cuda=True but device=cpu.
This is adding some flexibility to avoid errors on such cases.
If we need to remove this, lt requires a speparate PR since this involves whole diarization pipeline.

nithinraok · 2023-04-07T04:29:18Z

nemo/collections/asr/parts/utils/offline_clustering.py

+        laplacian = laplacian.float().to(torch.device('cpu'))
        laplacian = laplacian.float()


same here. laplacian.float() twice

nithinraok · 2023-04-07T04:30:31Z

nemo/collections/asr/parts/utils/online_clustering.py

-    stacked = np.hstack((enc_P, enc_Q))
-    cost = -1 * linear_kernel(stacked.T)[spk_count:, :spk_count]
-    row_ind, col_ind = linear_sum_assignment(cost)
+    PandQ_list: List[int] = [int(x.item()) for x in PandQ]


minor: mentioning dtype in variable name need to be avoided

Makes sense since types are strictly annotated for jit script functions.
Fixed.

nithinraok · 2023-04-07T21:22:29Z

nemo/collections/asr/parts/utils/optimization_utils.py

+        marked (Tensor): 2D matrix containing the marked zeros.
+    """
+
+    def __init__(self, cost_matrix):


minor, mention the dtype of cost_matrix here. Isn;t it necessary for jit scripting?

If there is no type annotation, jit compiler think of it as torch.Tensor.
So in general if it is not torch.Tensor, type annotation is needed.
Added type annotations

nithinraok · 2023-04-07T21:29:24Z

nemo/collections/asr/parts/utils/optimization_utils.py

+    if cost_matrix.shape[1] < cost_matrix.shape[0]:
+        cost_matrix = cost_matrix.T
+        transposed = True
+    else:
+        transposed = False


why extra transposed variable, Use the same col < row condition below?

This followed the original implementation in scipy.
If we don't use transposed variable, we need to create another variable to indicate that foo = cost_matrix.shape[1] < cost_matrix.shape[0].

nithinraok · 2023-04-07T21:30:53Z

nemo/collections/asr/parts/utils/optimization_utils.py

+# Copyright (c) 2008 Brian M. Clapper <[email protected]>, Gael Varoquaux
+# Author: Brian M. Clapper, Gael Varoquaux
+# License: 3-clause BSD
+


Do we have only one optimization algorithm yet? Thinking if we should move other funcs to this file as well

I think we can add other algorithms below this. (I mentioned "Linear Sum Assignment solver")
The copyright in the beginning of the code is the convention in the most of the project so I followed

nithinraok · 2023-04-07T22:02:47Z

nemo/collections/asr/metrics/der.py

+    for label in ref_labels:
+        start, end, speaker = label.split()
+        start, end = float(start), float(end)
+        # If the current [start, end] interval is latching the last prediction time


latching -> matching

Changed the expression (Checked by Elena)

Signed-off-by: Taejin Park <[email protected]>

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Signed-off-by: Taejin Park <[email protected]>

…fix/clus_spk_util_jit

nemo/collections/asr/parts/utils/online_clustering.py

@@ -31,67 +31,67 @@
 # https://arxiv.org/pdf/2003.02405.pdf and the implementation from
 # https://github.com/tango4j/Auto-Tuning-Spectral-Clustering.

-from typing import List, Tuple
+from typing import List, Set, Tuple


nithinraok

LGTM

…IA#6349) * [ASR] Add optimization utils for cpWER, diarization training, online diarization Signed-off-by: Taejin Park <[email protected]> * Fixed GPU/CPU issues for clustering Signed-off-by: Taejin Park <[email protected]> * Fixed unreachable state Signed-off-by: Taejin Park <[email protected]> * resolved jit script compile error for lsa algorithm Signed-off-by: Taejin Park <[email protected]> * Fixed errors and bugs, checked tests Signed-off-by: Taejin Park <[email protected]> * Fixed docstrings Signed-off-by: Taejin Park <[email protected]> * Update changes on test files Signed-off-by: Taejin Park <[email protected]> * Refactored functions Signed-off-by: Taejin Park <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Adding docstrings for the functions in der.py Signed-off-by: Taejin Park <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fixed wrong docstrings in der.py Signed-off-by: Taejin Park <[email protected]> * Fixed a wrong docstring Signed-off-by: Taejin Park <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Changed np.array input to Tensor for LSA solver in der.py Signed-off-by: Taejin Park <[email protected]> * Added code-QL issues and unit-tests for der.py functions Signed-off-by: Taejin Park <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Removed print line in der.py Signed-off-by: Taejin Park <[email protected]> * Fixed code QL redundant comparison Signed-off-by: Taejin Park <[email protected]> * Fixed code QL issue Signed-off-by: Taejin Park <[email protected]> * Added License for the reference code Signed-off-by: Taejin Park <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Added full license text of the original code Signed-off-by: Taejin Park <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Reflected comments Signed-off-by: Taejin Park <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Reflected review comments Signed-off-by: Taejin Park <[email protected]> --------- Signed-off-by: Taejin Park <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Signed-off-by: hsiehjackson <[email protected]>

tango4j added 9 commits March 24, 2023 09:51

[ASR] Add optimization utils for cpWER, diarization training, online …

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…diarization Signed-off-by: Taejin Park <[email protected]>

Fixed GPU/CPU issues for clustering

c8884bf

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Fixed unreachable state

c083836

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resolved jit script compile error for lsa algorithm

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Fixed errors and bugs, checked tests

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Fixed docstrings

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Update changes on test files

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Merge remote-tracking branch 'origin' into fix/clus_spk_util_jit

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[ASR] Add optimization util for linear sum assignment algorithm #6349

[ASR] Add optimization util for linear sum assignment algorithm #6349

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		laplacian = laplacian.float().to(torch.device('cpu'))
		laplacian = laplacian.float()

[ASR] Add optimization util for linear sum assignment algorithm #6349

[ASR] Add optimization util for linear sum assignment algorithm #6349

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tango4j commented Apr 3, 2023 • edited Loading

What does this PR do ?

Changelog

Usage

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