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Unverified Commit 4e945660 authored by Sanchit Gandhi's avatar Sanchit Gandhi Committed by GitHub
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Fix audio feature extractor deps (#24636) 

* Fix audio feature extractor deps

* use audio utils window over torch window
parent cd4584e3
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Showing with 28 additions and 119 deletions
src/transformers/__init__.py
View file @ 4e945660
......@@ -285,6 +285,7 @@ _import_structure = {
"models.encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
"EncodecFeatureExtractor",
],
"models.encoder_decoder": ["EncoderDecoderConfig"],
"models.ernie": [
......@@ -388,7 +389,7 @@ _import_structure = {
"models.maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig", "MaskFormerSwinConfig"],
"models.mbart": ["MBartConfig"],
"models.mbart50": [],
"models.mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig", "MCTCTProcessor"],
"models.mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig", "MCTCTFeatureExtractor", "MCTCTProcessor"],
"models.mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig"],
"models.megatron_bert": ["MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegatronBertConfig"],
"models.megatron_gpt2": [],
......@@ -481,6 +482,7 @@ _import_structure = {
"SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP",
"SpeechT5Config",
"SpeechT5FeatureExtractor",
"SpeechT5HifiGanConfig",
"SpeechT5Processor",
],
......@@ -519,6 +521,7 @@ _import_structure = {
"models.tvlt": [
"TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TvltConfig",
"TvltFeatureExtractor",
"TvltProcessor",
],
"models.umt5": [],
......@@ -843,11 +846,7 @@ except OptionalDependencyNotAvailable:
]
else:
_import_structure["models.audio_spectrogram_transformer"].append("ASTFeatureExtractor")
_import_structure["models.encodec"].append("EncodecFeatureExtractor")
_import_structure["models.mctct"].append("MCTCTFeatureExtractor")
_import_structure["models.speech_to_text"].append("Speech2TextFeatureExtractor")
_import_structure["models.speecht5"].append("SpeechT5FeatureExtractor")
_import_structure["models.tvlt"].append("TvltFeatureExtractor")
# Tensorflow-text-specific objects
try:
......@@ -4170,6 +4169,7 @@ if TYPE_CHECKING:
from .models.encodec import (
ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
EncodecConfig,
EncodecFeatureExtractor,
)
from .models.encoder_decoder import EncoderDecoderConfig
from .models.ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig
......@@ -4265,7 +4265,7 @@ if TYPE_CHECKING:
from .models.mask2former import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, Mask2FormerConfig
from .models.maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig, MaskFormerSwinConfig
from .models.mbart import MBartConfig
from .models.mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig, MCTCTProcessor
from .models.mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig, MCTCTFeatureExtractor, MCTCTProcessor
from .models.mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig
from .models.megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig
from .models.mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig, MgpstrProcessor, MgpstrTokenizer
......@@ -4355,6 +4355,7 @@ if TYPE_CHECKING:
SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
SpeechT5Config,
SpeechT5FeatureExtractor,
SpeechT5HifiGanConfig,
SpeechT5Processor,
)
......@@ -4386,7 +4387,7 @@ if TYPE_CHECKING:
TransfoXLTokenizer,
)
from .models.trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig, TrOCRProcessor
from .models.tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig, TvltProcessor
from .models.tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig, TvltFeatureExtractor, TvltProcessor
from .models.unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig
from .models.unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig
from .models.upernet import UperNetConfig
......@@ -4681,11 +4682,7 @@ if TYPE_CHECKING:
from .utils.dummy_speech_objects import *
else:
from .models.audio_spectrogram_transformer import ASTFeatureExtractor
from .models.encodec import EncodecFeatureExtractor
from .models.mctct import MCTCTFeatureExtractor
from .models.speech_to_text import Speech2TextFeatureExtractor
from .models.speecht5 import SpeechT5FeatureExtractor
from .models.tvlt import TvltFeatureExtractor
try:
if not is_tensorflow_text_available():
......
src/transformers/models/mctct/__init__.py
View file @ 4e945660
......@@ -13,24 +13,16 @@
# limitations under the License.
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_import_structure = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTProcessor"],
}
try:
if not is_speech_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["feature_extraction_mctct"] = ["MCTCTFeatureExtractor"]
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
......@@ -47,16 +39,9 @@ else:
if TYPE_CHECKING:
from .configuration_mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig
from .feature_extraction_mctct import MCTCTFeatureExtractor
from .processing_mctct import MCTCTProcessor
try:
if not is_speech_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .feature_extraction_mctct import MCTCTFeatureExtractor
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
......
src/transformers/models/mctct/feature_extraction_mctct.py
View file @ 4e945660
......@@ -19,9 +19,8 @@ Feature extractor class for M-CTC-T
from typing import List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...file_utils import PaddingStrategy, TensorType
......@@ -110,11 +109,9 @@ class MCTCTFeatureExtractor(SequenceFeatureExtractor):
Extracts MFSC Features for one waveform vector (unbatched). Adapted from Flashlight's C++ MFSC code.
"""
if self.win_function == "hamming_window":
window = torch.hamming_window(window_length=self.sample_size, periodic=False, alpha=0.54, beta=0.46)
window = window_function(window_length=self.sample_size, name=self.win_function, periodic=False)
else:
window = getattr(torch, self.win_function)()
window = window.numpy()
window = window_function(window_length=self.sample_size, name=self.win_function)
fbanks = mel_filter_bank(
num_frequency_bins=self.n_freqs,
......
src/transformers/models/speecht5/__init__.py
View file @ 4e945660
......@@ -17,7 +17,6 @@ from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
......@@ -29,6 +28,7 @@ _import_structure = {
"SpeechT5Config",
"SpeechT5HifiGanConfig",
],
"feature_extraction_speecht5": ["SpeechT5FeatureExtractor"],
"processing_speecht5": ["SpeechT5Processor"],
}
......@@ -40,14 +40,6 @@ except OptionalDependencyNotAvailable:
else:
_import_structure["tokenization_speecht5"] = ["SpeechT5Tokenizer"]
try:
if not is_speech_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["feature_extraction_speecht5"] = ["SpeechT5FeatureExtractor"]
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
......@@ -71,6 +63,7 @@ if TYPE_CHECKING:
SpeechT5Config,
SpeechT5HifiGanConfig,
)
from .feature_extraction_speecht5 import SpeechT5FeatureExtractor
from .processing_speecht5 import SpeechT5Processor
try:
......@@ -81,14 +74,6 @@ if TYPE_CHECKING:
else:
from .tokenization_speecht5 import SpeechT5Tokenizer
try:
if not is_speech_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .feature_extraction_speecht5 import SpeechT5FeatureExtractor
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
......
src/transformers/models/speecht5/feature_extraction_speecht5.py
View file @ 4e945660
......@@ -18,9 +18,8 @@ import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
......@@ -113,8 +112,7 @@ class SpeechT5FeatureExtractor(SequenceFeatureExtractor):
self.n_fft = optimal_fft_length(self.sample_size)
self.n_freqs = (self.n_fft // 2) + 1
window = getattr(torch, self.win_function)(window_length=self.sample_size, periodic=True)
self.window = window.numpy().astype(np.float64)
self.window = window_function(window_length=self.sample_size, name=self.win_function, periodic=True)
self.mel_filters = mel_filter_bank(
num_frequency_bins=self.n_freqs,
......
src/transformers/models/tvlt/__init__.py
View file @ 4e945660
......@@ -20,7 +20,6 @@ from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_speech_available,
is_torch_available,
is_vision_available,
)
......@@ -28,6 +27,7 @@ from ...utils import (
_import_structure = {
"configuration_tvlt": ["TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP", "TvltConfig"],
"feature_extraction_tvlt": ["TvltFeatureExtractor"],
"processing_tvlt": ["TvltProcessor"],
}
......@@ -53,17 +53,11 @@ except OptionalDependencyNotAvailable:
else:
_import_structure["image_processing_tvlt"] = ["TvltImageProcessor"]
try:
if not is_speech_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["feature_extraction_tvlt"] = ["TvltFeatureExtractor"]
if TYPE_CHECKING:
from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
from .processing_tvlt import TvltProcessor
from .feature_extraction_tvlt import TvltFeatureExtractor
try:
if not is_torch_available():
......@@ -87,13 +81,6 @@ if TYPE_CHECKING:
else:
from .image_processing_tvlt import TvltImageProcessor
try:
if not is_speech_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .feature_extraction_tvlt import TvltFeatureExtractor
else:
import sys
......
src/transformers/utils/dummy_speech_objects.py
View file @ 4e945660
......@@ -9,36 +9,8 @@ class ASTFeatureExtractor(metaclass=DummyObject):
requires_backends(self, ["speech"])
class EncodecFeatureExtractor(metaclass=DummyObject):
_backends = ["speech"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["speech"])
class MCTCTFeatureExtractor(metaclass=DummyObject):
_backends = ["speech"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["speech"])
class Speech2TextFeatureExtractor(metaclass=DummyObject):
_backends = ["speech"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["speech"])
class SpeechT5FeatureExtractor(metaclass=DummyObject):
_backends = ["speech"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["speech"])
class TvltFeatureExtractor(metaclass=DummyObject):
_backends = ["speech"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["speech"])
tests/models/encodec/test_feature_extraction_encodec.py
View file @ 4e945660
......@@ -20,16 +20,13 @@ import unittest
import numpy as np
from transformers import is_speech_available
from transformers import EncodecFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
from transformers import EncodecFeatureExtractor
if is_torch_available():
import torch
......@@ -103,7 +100,7 @@ class EnCodecFeatureExtractionTester(unittest.TestCase):
@require_torch
class EnCodecFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.TestCase):
feature_extraction_class = EncodecFeatureExtractor if is_speech_available() else None
feature_extraction_class = EncodecFeatureExtractor
def setUp(self):
self.feat_extract_tester = EnCodecFeatureExtractionTester(self)
......
tests/models/mctct/test_feature_extraction_mctct.py
View file @ 4e945660
......@@ -20,15 +20,12 @@ import unittest
import numpy as np
from transformers import is_speech_available
from transformers import MCTCTFeatureExtractor
from transformers.testing_utils import require_torch
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
from transformers import MCTCTFeatureExtractor
global_rng = random.Random()
......@@ -102,7 +99,7 @@ class MCTCTFeatureExtractionTester(unittest.TestCase):
@require_torch
class MCTCTFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.TestCase):
feature_extraction_class = MCTCTFeatureExtractor if is_speech_available() else None
feature_extraction_class = MCTCTFeatureExtractor
def setUp(self):
self.feat_extract_tester = MCTCTFeatureExtractionTester(self)
......
tests/models/speecht5/test_feature_extraction_speecht5.py
View file @ 4e945660
......@@ -20,16 +20,13 @@ import unittest
import numpy as np
from transformers import BatchFeature, is_speech_available
from transformers import BatchFeature, SpeechT5FeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
from transformers import SpeechT5FeatureExtractor
if is_torch_available():
import torch
......@@ -142,7 +139,7 @@ class SpeechT5FeatureExtractionTester(unittest.TestCase):
@require_torch
class SpeechT5FeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.TestCase):
feature_extraction_class = SpeechT5FeatureExtractor if is_speech_available() else None
feature_extraction_class = SpeechT5FeatureExtractor
def setUp(self):
self.feat_extract_tester = SpeechT5FeatureExtractionTester(self)
......
tests/models/tvlt/test_feature_extraction_tvlt.py
View file @ 4e945660
......@@ -22,7 +22,7 @@ import unittest
import numpy as np
from transformers import is_datasets_available, is_speech_available
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
......@@ -35,9 +35,6 @@ if is_torch_available():
if is_datasets_available():
from datasets import load_dataset
if is_speech_available():
from transformers import TvltFeatureExtractor
global_rng = random.Random()
......@@ -111,7 +108,7 @@ class TvltFeatureExtractionTester(unittest.TestCase):
@require_torch
@require_torchaudio
class TvltFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.TestCase):
feature_extraction_class = TvltFeatureExtractor if is_speech_available() else None
feature_extraction_class = TvltFeatureExtractor
def setUp(self):
self.feat_extract_tester = TvltFeatureExtractionTester(self)
......
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