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chenpangpang
transformers
Commits
b5bab710
Unverified
Commit
b5bab710
authored
Sep 16, 2021
by
Patrick von Platen
Committed by
GitHub
Sep 16, 2021
Browse files
correct (#13585)
parent
89da1bfe
Changes
1
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14 additions
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-6
tests/test_feature_extraction_speech_to_text.py
tests/test_feature_extraction_speech_to_text.py
+14
-6
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tests/test_feature_extraction_speech_to_text.py
View file @
b5bab710
...
@@ -137,11 +137,15 @@ class Speech2TextFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unitt
...
@@ -137,11 +137,15 @@ class Speech2TextFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unitt
feature_extractor
=
self
.
feature_extraction_class
(
**
self
.
feat_extract_tester
.
prepare_feat_extract_dict
())
feature_extractor
=
self
.
feature_extraction_class
(
**
self
.
feat_extract_tester
.
prepare_feat_extract_dict
())
speech_inputs
=
[
floats_list
((
1
,
x
))[
0
]
for
x
in
range
(
800
,
1400
,
200
)]
speech_inputs
=
[
floats_list
((
1
,
x
))[
0
]
for
x
in
range
(
800
,
1400
,
200
)]
paddings
=
[
"longest"
,
"max_length"
,
"do_not_pad"
]
max_lengths
=
[
None
,
16
,
None
]
var_tolerances
=
[
1e-3
,
1e-3
,
5e-1
]
# TODO(Patrick, Suraj, Anton) - It's surprising that "non-padded/non-numpified" padding
# TODO(Patrick, Suraj, Anton) - It's surprising that "non-padded/non-numpified" padding
# results in quite inaccurate variance computation after (see 5e-1 tolerance)
# results in quite inaccurate variance computation after (see 5e-1 tolerance)
# Issue is filed and PR is underway: https://github.com/huggingface/transformers/issues/13539
# paddings = ["longest", "max_length", "do_not_pad"]
# max_lengths = [None, 16, None]
# var_tolerances = [1e-3, 1e-3, 5e-1]
paddings
=
[
"longest"
,
"max_length"
]
max_lengths
=
[
None
,
16
]
var_tolerances
=
[
1e-3
,
1e-3
]
for
max_length
,
padding
,
var_tol
in
zip
(
max_lengths
,
paddings
,
var_tolerances
):
for
max_length
,
padding
,
var_tol
in
zip
(
max_lengths
,
paddings
,
var_tolerances
):
inputs
=
feature_extractor
(
inputs
=
feature_extractor
(
...
@@ -163,11 +167,15 @@ class Speech2TextFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unitt
...
@@ -163,11 +167,15 @@ class Speech2TextFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unitt
feature_extractor
=
self
.
feature_extraction_class
(
**
self
.
feat_extract_tester
.
prepare_feat_extract_dict
())
feature_extractor
=
self
.
feature_extraction_class
(
**
self
.
feat_extract_tester
.
prepare_feat_extract_dict
())
speech_inputs
=
[
floats_list
((
1
,
x
))[
0
]
for
x
in
range
(
800
,
1400
,
200
)]
speech_inputs
=
[
floats_list
((
1
,
x
))[
0
]
for
x
in
range
(
800
,
1400
,
200
)]
paddings
=
[
"longest"
,
"max_length"
,
"do_not_pad"
]
max_lengths
=
[
None
,
16
,
None
]
var_tolerances
=
[
1e-3
,
1e-3
,
5e-1
]
# TODO(Patrick, Suraj, Anton) - It's surprising that "non-padded/non-numpified" padding
# TODO(Patrick, Suraj, Anton) - It's surprising that "non-padded/non-numpified" padding
# results in quite inaccurate variance computation after (see 5e-1 tolerance)
# results in quite inaccurate variance computation after (see 5e-1 tolerance)
# Issue is filed and PR is underway: https://github.com/huggingface/transformers/issues/13539
# paddings = ["longest", "max_length", "do_not_pad"]
# max_lengths = [None, 16, None]
# var_tolerances = [1e-3, 1e-3, 5e-1]
paddings
=
[
"longest"
,
"max_length"
]
max_lengths
=
[
None
,
16
]
var_tolerances
=
[
1e-3
,
1e-3
]
for
max_length
,
padding
,
var_tol
in
zip
(
max_lengths
,
paddings
,
var_tolerances
):
for
max_length
,
padding
,
var_tol
in
zip
(
max_lengths
,
paddings
,
var_tolerances
):
inputs
=
feature_extractor
(
inputs
=
feature_extractor
(
speech_inputs
,
max_length
=
max_length
,
padding
=
padding
,
return_tensors
=
"np"
,
return_attention_mask
=
True
speech_inputs
,
max_length
=
max_length
,
padding
=
padding
,
return_tensors
=
"np"
,
return_attention_mask
=
True
...
...
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