forked from huggingface/diffusers
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathimport_utils.py
More file actions
1060 lines (822 loc) · 35.6 KB
/
Copy pathimport_utils.py
File metadata and controls
1060 lines (822 loc) · 35.6 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
# Copyright 2026 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Import utilities: Utilities related to imports and our lazy inits.
"""
import importlib.util
import inspect
import operator as op
import os
import sys
from collections import OrderedDict, defaultdict
from functools import lru_cache as cache
from itertools import chain
from types import ModuleType
from typing import Any
from huggingface_hub.utils import is_jinja_available # noqa: F401
from packaging.version import Version, parse
from . import logging
# The package importlib_metadata is in a different place, depending on the python version.
if sys.version_info < (3, 8):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
try:
_package_map = importlib_metadata.packages_distributions() # load-once to avoid expensive calls
except Exception:
_package_map = None
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
ENV_VARS_TRUE_VALUES = {"1", "ON", "YES", "TRUE"}
ENV_VARS_TRUE_AND_AUTO_VALUES = ENV_VARS_TRUE_VALUES.union({"AUTO"})
USE_TF = os.environ.get("USE_TF", "AUTO").upper()
USE_TORCH = os.environ.get("USE_TORCH", "AUTO").upper()
USE_JAX = os.environ.get("USE_FLAX", "AUTO").upper()
USE_SAFETENSORS = os.environ.get("USE_SAFETENSORS", "AUTO").upper()
DIFFUSERS_SLOW_IMPORT = os.environ.get("DIFFUSERS_SLOW_IMPORT", "FALSE").upper()
DIFFUSERS_SLOW_IMPORT = DIFFUSERS_SLOW_IMPORT in ENV_VARS_TRUE_VALUES
STR_OPERATION_TO_FUNC = {">": op.gt, ">=": op.ge, "==": op.eq, "!=": op.ne, "<=": op.le, "<": op.lt}
_is_google_colab = "google.colab" in sys.modules or any(k.startswith("COLAB_") for k in os.environ)
def _is_package_available(pkg_name: str, get_dist_name: bool = False) -> tuple[bool, str]:
global _package_map
pkg_exists = importlib.util.find_spec(pkg_name) is not None
pkg_version = "N/A"
if pkg_exists:
if _package_map is None:
_package_map = defaultdict(list)
try:
# Fallback for Python < 3.10
for dist in importlib_metadata.distributions():
_top_level_declared = (dist.read_text("top_level.txt") or "").split()
# Infer top-level package names from file structure
_inferred_opt_names = {
f.parts[0] if len(f.parts) > 1 else inspect.getmodulename(f) for f in (dist.files or [])
} - {None}
_top_level_inferred = filter(lambda name: "." not in name, _inferred_opt_names)
for pkg in _top_level_declared or _top_level_inferred:
_package_map[pkg].append(dist.metadata["Name"])
except Exception as _:
pass
try:
if get_dist_name and pkg_name in _package_map and _package_map[pkg_name]:
if len(_package_map[pkg_name]) > 1:
logger.warning(
f"Multiple distributions found for package {pkg_name}. Picked distribution: {_package_map[pkg_name][0]}"
)
pkg_name = _package_map[pkg_name][0]
pkg_version = importlib_metadata.version(pkg_name)
logger.debug(f"Successfully imported {pkg_name} version {pkg_version}")
except (ImportError, importlib_metadata.PackageNotFoundError):
pkg_exists = False
return pkg_exists, pkg_version
if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
_torch_available, _torch_version = _is_package_available("torch")
else:
logger.info("Disabling PyTorch because USE_TORCH is set")
_torch_available = False
_torch_version = "N/A"
_jax_version = "N/A"
_flax_version = "N/A"
if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
_flax_available = importlib.util.find_spec("jax") is not None and importlib.util.find_spec("flax") is not None
if _flax_available:
try:
_jax_version = importlib_metadata.version("jax")
_flax_version = importlib_metadata.version("flax")
logger.info(f"JAX version {_jax_version}, Flax version {_flax_version} available.")
except importlib_metadata.PackageNotFoundError:
_flax_available = False
else:
_flax_available = False
if USE_SAFETENSORS in ENV_VARS_TRUE_AND_AUTO_VALUES:
_safetensors_available, _safetensors_version = _is_package_available("safetensors")
else:
logger.info("Disabling Safetensors because USE_SAFETENSORS is set")
_safetensors_available = False
_onnxruntime_version = "N/A"
_onnx_available = importlib.util.find_spec("onnxruntime") is not None
if _onnx_available:
candidates = (
"onnxruntime",
"onnxruntime-cann",
"onnxruntime-directml",
"ort_nightly_directml",
"onnxruntime-gpu",
"ort_nightly_gpu",
"onnxruntime-migraphx",
"onnxruntime-openvino",
"onnxruntime-qnn",
"onnxruntime-rocm",
"onnxruntime-training",
"onnxruntime-vitisai",
)
_onnxruntime_version = None
# For the metadata, we have to look for both onnxruntime and onnxruntime-x
for pkg in candidates:
try:
_onnxruntime_version = importlib_metadata.version(pkg)
break
except importlib_metadata.PackageNotFoundError:
pass
_onnx_available = _onnxruntime_version is not None
if _onnx_available:
logger.debug(f"Successfully imported onnxruntime version {_onnxruntime_version}")
# (sayakpaul): importlib.util.find_spec("opencv-python") returns None even when it's installed.
# _opencv_available = importlib.util.find_spec("opencv-python") is not None
try:
candidates = (
"opencv-python",
"opencv-contrib-python",
"opencv-python-headless",
"opencv-contrib-python-headless",
)
_opencv_version = None
for pkg in candidates:
try:
_opencv_version = importlib_metadata.version(pkg)
break
except importlib_metadata.PackageNotFoundError:
pass
_opencv_available = _opencv_version is not None
if _opencv_available:
logger.debug(f"Successfully imported cv2 version {_opencv_version}")
except importlib_metadata.PackageNotFoundError:
_opencv_available = False
_bs4_available = importlib.util.find_spec("bs4") is not None
try:
# importlib metadata under different name
_bs4_version = importlib_metadata.version("beautifulsoup4")
logger.debug(f"Successfully imported ftfy version {_bs4_version}")
except importlib_metadata.PackageNotFoundError:
_bs4_available = False
_invisible_watermark_available = importlib.util.find_spec("imwatermark") is not None
try:
_invisible_watermark_version = importlib_metadata.version("invisible-watermark")
logger.debug(f"Successfully imported invisible-watermark version {_invisible_watermark_version}")
except importlib_metadata.PackageNotFoundError:
_invisible_watermark_available = False
_torch_xla_available, _torch_xla_version = _is_package_available("torch_xla")
_torch_npu_available, _torch_npu_version = _is_package_available("torch_npu")
_torch_mlu_available, _torch_mlu_version = _is_package_available("torch_mlu")
_torch_neuronx_available, _torch_neuronx_version = _is_package_available("torch_neuronx")
_transformers_available, _transformers_version = _is_package_available("transformers")
_hf_hub_available, _hf_hub_version = _is_package_available("huggingface_hub")
_kernels_available, _kernels_version = _is_package_available("kernels")
_inflect_available, _inflect_version = _is_package_available("inflect")
_unidecode_available, _unidecode_version = _is_package_available("unidecode")
_note_seq_available, _note_seq_version = _is_package_available("note_seq")
_wandb_available, _wandb_version = _is_package_available("wandb")
_tensorboard_available, _tensorboard_version = _is_package_available("tensorboard")
_compel_available, _compel_version = _is_package_available("compel")
_sentencepiece_available, _sentencepiece_version = _is_package_available("sentencepiece")
_outlines_available, _outlines_version = _is_package_available("outlines")
_torchsde_available, _torchsde_version = _is_package_available("torchsde")
_peft_available, _peft_version = _is_package_available("peft")
_torchvision_available, _torchvision_version = _is_package_available("torchvision")
_matplotlib_available, _matplotlib_version = _is_package_available("matplotlib")
_timm_available, _timm_version = _is_package_available("timm")
_bitsandbytes_available, _bitsandbytes_version = _is_package_available("bitsandbytes")
_imageio_available, _imageio_version = _is_package_available("imageio")
_ftfy_available, _ftfy_version = _is_package_available("ftfy")
_scipy_available, _scipy_version = _is_package_available("scipy")
_librosa_available, _librosa_version = _is_package_available("librosa")
_accelerate_available, _accelerate_version = _is_package_available("accelerate")
_xformers_available, _xformers_version = _is_package_available("xformers")
_gguf_available, _gguf_version = _is_package_available("gguf")
_torchao_available, _torchao_version = _is_package_available("torchao")
_bitsandbytes_available, _bitsandbytes_version = _is_package_available("bitsandbytes")
_optimum_quanto_available, _optimum_quanto_version = _is_package_available("optimum", get_dist_name=True)
_pytorch_retinaface_available, _pytorch_retinaface_version = _is_package_available("pytorch_retinaface")
_better_profanity_available, _better_profanity_version = _is_package_available("better_profanity")
_nltk_available, _nltk_version = _is_package_available("nltk")
_cosmos_guardrail_available, _cosmos_guardrail_version = _is_package_available("cosmos_guardrail")
_sageattention_available, _sageattention_version = _is_package_available("sageattention")
_flash_attn_available, _flash_attn_version = _is_package_available("flash_attn")
_flash_attn_3_available, _flash_attn_3_version = _is_package_available("flash_attn_3")
_aiter_available, _aiter_version = _is_package_available("aiter", get_dist_name=True)
_kornia_available, _kornia_version = _is_package_available("kornia")
_nvidia_modelopt_available, _nvidia_modelopt_version = _is_package_available("modelopt", get_dist_name=True)
_auto_round_available, _auto_round_version = _is_package_available("auto_round")
_flashpack_available, _flashpack_version = _is_package_available("flashpack")
_av_available, _av_version = _is_package_available("av")
def is_torch_available():
return _torch_available
def is_torch_xla_available():
return _torch_xla_available
def is_torch_npu_available():
return _torch_npu_available
def is_torch_mlu_available():
return _torch_mlu_available
def is_torch_neuronx_available():
return _torch_neuronx_available
def is_flax_available():
return _flax_available
def is_transformers_available():
return _transformers_available
def is_transformers_flax_compatible():
# Flax classes (e.g. FlaxCLIPTextModel, FlaxPreTrainedModel) were removed from
# transformers main on the path to its v5 release. Gate Flax pipeline registration
# on transformers still shipping them so `import diffusers` doesn't crash.
# Name avoids the `is_*_available()` pattern so utils/check_dummies.py keeps
# generating the `flax_and_transformers` backend group when this is combined with
# the legacy is_flax_available()/is_transformers_available() pair.
if not (_transformers_available and _flax_available):
return False
try:
import transformers
except ImportError:
return False
return hasattr(transformers, "FlaxPreTrainedModel")
def is_inflect_available():
return _inflect_available
def is_unidecode_available():
return _unidecode_available
def is_onnx_available():
return _onnx_available
def is_opencv_available():
return _opencv_available
def is_scipy_available():
return _scipy_available
def is_librosa_available():
return _librosa_available
def is_xformers_available():
return _xformers_available
def is_accelerate_available():
return _accelerate_available
def is_kernels_available():
return _kernels_available
def is_note_seq_available():
return _note_seq_available
def is_wandb_available():
return _wandb_available
def is_tensorboard_available():
return _tensorboard_available
def is_compel_available():
return _compel_available
def is_ftfy_available():
return _ftfy_available
def is_bs4_available():
return _bs4_available
def is_torchsde_available():
return _torchsde_available
def is_invisible_watermark_available():
return _invisible_watermark_available
def is_peft_available():
return _peft_available
def is_torchvision_available():
return _torchvision_available
def is_matplotlib_available():
return _matplotlib_available
def is_safetensors_available():
return _safetensors_available
def is_bitsandbytes_available():
return _bitsandbytes_available
def is_google_colab():
return _is_google_colab
def is_sentencepiece_available():
return _sentencepiece_available
def is_outlines_available():
return _outlines_available
def is_imageio_available():
return _imageio_available
def is_gguf_available():
return _gguf_available
def is_flashpack_available():
return _flashpack_available
def is_torchao_available():
return _torchao_available
def is_optimum_quanto_available():
return _optimum_quanto_available
def is_nvidia_modelopt_available():
return _nvidia_modelopt_available
def is_auto_round_available():
return _auto_round_available
def is_timm_available():
return _timm_available
def is_pytorch_retinaface_available():
return _pytorch_retinaface_available
def is_better_profanity_available():
return _better_profanity_available
def is_nltk_available():
return _nltk_available
def is_cosmos_guardrail_available():
return _cosmos_guardrail_available
def is_hpu_available():
return all(importlib.util.find_spec(lib) for lib in ("habana_frameworks", "habana_frameworks.torch"))
def is_sageattention_available():
return _sageattention_available
def is_flash_attn_available():
return _flash_attn_available
def is_flash_attn_3_available():
return _flash_attn_3_available
def is_aiter_available():
return _aiter_available
def is_kornia_available():
return _kornia_available
def is_av_available():
return _av_available
# docstyle-ignore
FLAX_IMPORT_ERROR = """
{0} requires the FLAX library but it was not found in your environment. Checkout the instructions on the
installation page: https://github.com/google/flax and follow the ones that match your environment.
"""
# docstyle-ignore
INFLECT_IMPORT_ERROR = """
{0} requires the inflect library but it was not found in your environment. You can install it with pip: `pip install
inflect`
"""
# docstyle-ignore
PYTORCH_IMPORT_ERROR = """
{0} requires the PyTorch library but it was not found in your environment. Checkout the instructions on the
installation page: https://pytorch.org/get-started/locally/ and follow the ones that match your environment.
"""
# docstyle-ignore
ONNX_IMPORT_ERROR = """
{0} requires the onnxruntime library but it was not found in your environment. You can install it with pip: `pip
install onnxruntime`
"""
# docstyle-ignore
OPENCV_IMPORT_ERROR = """
{0} requires the OpenCV library but it was not found in your environment. You can install it with pip: `pip
install opencv-python`
"""
# docstyle-ignore
SCIPY_IMPORT_ERROR = """
{0} requires the scipy library but it was not found in your environment. You can install it with pip: `pip install
scipy`
"""
# docstyle-ignore
LIBROSA_IMPORT_ERROR = """
{0} requires the librosa library but it was not found in your environment. Checkout the instructions on the
installation page: https://librosa.org/doc/latest/install.html and follow the ones that match your environment.
"""
# docstyle-ignore
TRANSFORMERS_IMPORT_ERROR = """
{0} requires the transformers library but it was not found in your environment. You can install it with pip: `pip
install transformers`
"""
# docstyle-ignore
UNIDECODE_IMPORT_ERROR = """
{0} requires the unidecode library but it was not found in your environment. You can install it with pip: `pip install
Unidecode`
"""
# docstyle-ignore
NOTE_SEQ_IMPORT_ERROR = """
{0} requires the note-seq library but it was not found in your environment. You can install it with pip: `pip
install note-seq`
"""
# docstyle-ignore
WANDB_IMPORT_ERROR = """
{0} requires the wandb library but it was not found in your environment. You can install it with pip: `pip
install wandb`
"""
# docstyle-ignore
TENSORBOARD_IMPORT_ERROR = """
{0} requires the tensorboard library but it was not found in your environment. You can install it with pip: `pip
install tensorboard`
"""
# docstyle-ignore
COMPEL_IMPORT_ERROR = """
{0} requires the compel library but it was not found in your environment. You can install it with pip: `pip install compel`
"""
# docstyle-ignore
BS4_IMPORT_ERROR = """
{0} requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:
`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.
"""
# docstyle-ignore
FTFY_IMPORT_ERROR = """
{0} requires the ftfy library but it was not found in your environment. Checkout the instructions on the
installation section: https://github.com/rspeer/python-ftfy/tree/master#installing and follow the ones
that match your environment. Please note that you may need to restart your runtime after installation.
"""
# docstyle-ignore
TORCHSDE_IMPORT_ERROR = """
{0} requires the torchsde library but it was not found in your environment. You can install it with pip: `pip install torchsde`
"""
# docstyle-ignore
INVISIBLE_WATERMARK_IMPORT_ERROR = """
{0} requires the invisible-watermark library but it was not found in your environment. You can install it with pip: `pip install invisible-watermark>=0.2.0`
"""
# docstyle-ignore
PEFT_IMPORT_ERROR = """
{0} requires the peft library but it was not found in your environment. You can install it with pip: `pip install peft`
"""
# docstyle-ignore
SAFETENSORS_IMPORT_ERROR = """
{0} requires the safetensors library but it was not found in your environment. You can install it with pip: `pip install safetensors`
"""
# docstyle-ignore
SENTENCEPIECE_IMPORT_ERROR = """
{0} requires the sentencepiece library but it was not found in your environment. You can install it with pip: `pip install sentencepiece`
"""
# docstyle-ignore
BITSANDBYTES_IMPORT_ERROR = """
{0} requires the bitsandbytes library but it was not found in your environment. You can install it with pip: `pip install bitsandbytes`
"""
# docstyle-ignore
IMAGEIO_IMPORT_ERROR = """
{0} requires the imageio library and ffmpeg but it was not found in your environment. You can install it with pip: `pip install imageio imageio-ffmpeg`
"""
# docstyle-ignore
GGUF_IMPORT_ERROR = """
{0} requires the gguf library but it was not found in your environment. You can install it with pip: `pip install gguf`
"""
TORCHAO_IMPORT_ERROR = """
{0} requires the torchao library but it was not found in your environment. You can install it with pip: `pip install
torchao`
"""
QUANTO_IMPORT_ERROR = """
{0} requires the optimum-quanto library but it was not found in your environment. You can install it with pip: `pip
install optimum-quanto`
"""
# docstyle-ignore
PYTORCH_RETINAFACE_IMPORT_ERROR = """
{0} requires the pytorch_retinaface library but it was not found in your environment. You can install it with pip: `pip install pytorch_retinaface`
"""
# docstyle-ignore
BETTER_PROFANITY_IMPORT_ERROR = """
{0} requires the better_profanity library but it was not found in your environment. You can install it with pip: `pip install better_profanity`
"""
# docstyle-ignore
NLTK_IMPORT_ERROR = """
{0} requires the nltk library but it was not found in your environment. You can install it with pip: `pip install nltk`
"""
TORCH_NEURONX_IMPORT_ERROR = """
{0} requires the torch_neuronx library (AWS Neuron SDK) but it was not found in your environment. Please install it
following the AWS Neuron documentation: https://awsdocs-neuron.readthedocs-hosted.com/en/latest/
"""
BACKENDS_MAPPING = OrderedDict(
[
("bs4", (is_bs4_available, BS4_IMPORT_ERROR)),
("flax", (is_flax_available, FLAX_IMPORT_ERROR)),
("inflect", (is_inflect_available, INFLECT_IMPORT_ERROR)),
("onnx", (is_onnx_available, ONNX_IMPORT_ERROR)),
("opencv", (is_opencv_available, OPENCV_IMPORT_ERROR)),
("scipy", (is_scipy_available, SCIPY_IMPORT_ERROR)),
("torch", (is_torch_available, PYTORCH_IMPORT_ERROR)),
("transformers", (is_transformers_available, TRANSFORMERS_IMPORT_ERROR)),
("unidecode", (is_unidecode_available, UNIDECODE_IMPORT_ERROR)),
("librosa", (is_librosa_available, LIBROSA_IMPORT_ERROR)),
("note_seq", (is_note_seq_available, NOTE_SEQ_IMPORT_ERROR)),
("wandb", (is_wandb_available, WANDB_IMPORT_ERROR)),
("tensorboard", (is_tensorboard_available, TENSORBOARD_IMPORT_ERROR)),
("compel", (is_compel_available, COMPEL_IMPORT_ERROR)),
("ftfy", (is_ftfy_available, FTFY_IMPORT_ERROR)),
("torchsde", (is_torchsde_available, TORCHSDE_IMPORT_ERROR)),
("invisible_watermark", (is_invisible_watermark_available, INVISIBLE_WATERMARK_IMPORT_ERROR)),
("peft", (is_peft_available, PEFT_IMPORT_ERROR)),
("safetensors", (is_safetensors_available, SAFETENSORS_IMPORT_ERROR)),
("bitsandbytes", (is_bitsandbytes_available, BITSANDBYTES_IMPORT_ERROR)),
("sentencepiece", (is_sentencepiece_available, SENTENCEPIECE_IMPORT_ERROR)),
("imageio", (is_imageio_available, IMAGEIO_IMPORT_ERROR)),
("gguf", (is_gguf_available, GGUF_IMPORT_ERROR)),
("torchao", (is_torchao_available, TORCHAO_IMPORT_ERROR)),
("quanto", (is_optimum_quanto_available, QUANTO_IMPORT_ERROR)),
("pytorch_retinaface", (is_pytorch_retinaface_available, PYTORCH_RETINAFACE_IMPORT_ERROR)),
("better_profanity", (is_better_profanity_available, BETTER_PROFANITY_IMPORT_ERROR)),
("nltk", (is_nltk_available, NLTK_IMPORT_ERROR)),
("torch_neuronx", (is_torch_neuronx_available, TORCH_NEURONX_IMPORT_ERROR)),
]
)
def requires_backends(obj, backends):
if not isinstance(backends, (list, tuple)):
backends = [backends]
name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
checks = (BACKENDS_MAPPING[backend] for backend in backends)
failed = [msg.format(name) for available, msg in checks if not available()]
if failed:
raise ImportError("".join(failed))
if name in [
"VersatileDiffusionTextToImagePipeline",
"VersatileDiffusionPipeline",
"VersatileDiffusionDualGuidedPipeline",
"StableDiffusionImageVariationPipeline",
"UnCLIPPipeline",
] and is_transformers_version("<", "4.25.0"):
raise ImportError(
f"You need to install `transformers>=4.25` in order to use {name}: \n```\n pip install"
" --upgrade transformers \n```"
)
if name in ["StableDiffusionDepth2ImgPipeline", "StableDiffusionPix2PixZeroPipeline"] and is_transformers_version(
"<", "4.26.0"
):
raise ImportError(
f"You need to install `transformers>=4.26` in order to use {name}: \n```\n pip install"
" --upgrade transformers \n```"
)
class DummyObject(type):
"""
Metaclass for the dummy objects. Any class inheriting from it will return the ImportError generated by
`requires_backend` each time a user tries to access any method of that class.
"""
def __getattr__(cls, key):
if key.startswith("_") and key not in ["_load_connected_pipes", "_is_onnx"]:
return super().__getattr__(cls, key)
requires_backends(cls, cls._backends)
# This function was copied from: https://github.com/huggingface/accelerate/blob/874c4967d94badd24f893064cc3bef45f57cadf7/src/accelerate/utils/versions.py#L319
def compare_versions(library_or_version: str | Version, operation: str, requirement_version: str):
"""
Compares a library version to some requirement using a given operation.
Args:
library_or_version (`str` or `packaging.version.Version`):
A library name or a version to check.
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`.
requirement_version (`str`):
The version to compare the library version against
"""
if operation not in STR_OPERATION_TO_FUNC.keys():
raise ValueError(f"`operation` must be one of {list(STR_OPERATION_TO_FUNC.keys())}, received {operation}")
operation = STR_OPERATION_TO_FUNC[operation]
if isinstance(library_or_version, str):
library_or_version = parse(importlib_metadata.version(library_or_version))
return operation(library_or_version, parse(requirement_version))
# This function was copied from: https://github.com/huggingface/accelerate/blob/874c4967d94badd24f893064cc3bef45f57cadf7/src/accelerate/utils/versions.py#L338
@cache
def is_torch_version(operation: str, version: str):
"""
Compares the current PyTorch version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A string version of PyTorch
"""
return compare_versions(parse(_torch_version), operation, version)
@cache
def is_torch_xla_version(operation: str, version: str):
"""
Compares the current torch_xla version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A string version of torch_xla
"""
if not is_torch_xla_available:
return False
return compare_versions(parse(_torch_xla_version), operation, version)
@cache
def is_transformers_version(operation: str, version: str):
"""
Compares the current Transformers version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _transformers_available:
return False
return compare_versions(parse(_transformers_version), operation, version)
@cache
def is_kernels_version(operation: str, version: str):
"""
Compares the current Kernels version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _kernels_available:
return False
return compare_versions(parse(_kernels_version), operation, version)
@cache
def is_hf_hub_version(operation: str, version: str):
"""
Compares the current Hugging Face Hub version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _hf_hub_available:
return False
return compare_versions(parse(_hf_hub_version), operation, version)
@cache
def is_accelerate_version(operation: str, version: str):
"""
Compares the current Accelerate version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _accelerate_available:
return False
return compare_versions(parse(_accelerate_version), operation, version)
@cache
def is_peft_version(operation: str, version: str):
"""
Compares the current PEFT version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _peft_available:
return False
return compare_versions(parse(_peft_version), operation, version)
@cache
def is_bitsandbytes_version(operation: str, version: str):
"""
Args:
Compares the current bitsandbytes version to a given reference with an operation.
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _bitsandbytes_available:
return False
return compare_versions(parse(_bitsandbytes_version), operation, version)
@cache
def is_gguf_version(operation: str, version: str):
"""
Compares the current Accelerate version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _gguf_available:
return False
return compare_versions(parse(_gguf_version), operation, version)
@cache
def is_torchao_version(operation: str, version: str):
"""
Compares the current torchao version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _torchao_available:
return False
return compare_versions(parse(_torchao_version), operation, version)
@cache
def is_optimum_quanto_version(operation: str, version: str):
"""
Compares the current Accelerate version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _optimum_quanto_available:
return False
return compare_versions(parse(_optimum_quanto_version), operation, version)
@cache
def is_nvidia_modelopt_version(operation: str, version: str):
"""
Compares the current Nvidia ModelOpt version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _nvidia_modelopt_available:
return False
return compare_versions(parse(_nvidia_modelopt_version), operation, version)
@cache
def is_xformers_version(operation: str, version: str):
"""
Compares the current xformers version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _xformers_available:
return False
return compare_versions(parse(_xformers_version), operation, version)
@cache
def is_sageattention_version(operation: str, version: str):
"""
Compares the current sageattention version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _sageattention_available:
return False
return compare_versions(parse(_sageattention_version), operation, version)
@cache
def is_flash_attn_version(operation: str, version: str):
"""
Compares the current flash-attention version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _flash_attn_available:
return False
return compare_versions(parse(_flash_attn_version), operation, version)
@cache
def is_aiter_version(operation: str, version: str):
"""
Compares the current aiter version to a given reference with an operation.
Args:
operation (`str`):
A string representation of an operator, such as `">"` or `"<="`
version (`str`):
A version string
"""
if not _aiter_available:
return False
return compare_versions(parse(_aiter_version), operation, version)
def get_objects_from_module(module):
"""
Returns a dict of object names and values in a module, while skipping private/internal objects
Args:
module (ModuleType):
Module to extract the objects from.
Returns:
dict: Dictionary of object names and corresponding values
"""
objects = {}
for name in dir(module):
if name.startswith("_"):
continue
objects[name] = getattr(module, name)
return objects
class OptionalDependencyNotAvailable(BaseException):
"""
An error indicating that an optional dependency of Diffusers was not found in the environment.
"""