




"""simple docstring"""




import hashlib
import unittest
from typing import Dict

import numpy as np

from transformers import (
    MODEL_FOR_MASK_GENERATION_MAPPING,
    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
    is_vision_available,
    pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)


if is_vision_available():
					from PIL import Image
else:






					class 					__magic_name__							:






									'''simple docstring'''





									@staticmethod
									def      _lowerCAmelCase       ( *_a	,				**_a				):





												"""simple docstring"""
												pass



def 					a__				(       snake_case__       )		->      str:
			lowerCamelCase       =      hashlib.mda(image.tobytes()       )
			return m.hexdigest()[:10]



def 					a__				(       snake_case__       )		->      Dict:
			lowerCamelCase       =      np.array(snake_case__       )
			lowerCamelCase       =      npimg.shape
			return {"hash": hashimage(snake_case__       ), "shape": shape}






@is_pipeline_test
@require_vision
@require_torch
class 					__magic_name__							( unittest.TestCase       ):






				'''simple docstring'''
				__UpperCamelCase    						=		dict(
				    (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()       ) if MODEL_FOR_MASK_GENERATION_MAPPING else [])       )
				__UpperCamelCase    						=		dict(
				    (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()       ) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])       )





				def      _lowerCAmelCase       ( self	,				_a	,				_a	,				_a				):





							"""simple docstring"""
							lowerCamelCase       =      MaskGenerationPipeline(model=_a	,				image_processor=_a				)
							return image_segmenter, [
							    "./tests/fixtures/tests_samples/COCO/000000039769.png",
							    "./tests/fixtures/tests_samples/COCO/000000039769.png",
							]





				def      _lowerCAmelCase       ( self	,				_a	,				_a				):





							"""simple docstring"""
							pass





				@require_tf
				@unittest.skip("""Image segmentation not implemented in TF"""				)
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							pass





				@slow
				@require_torch
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      pipeline("""mask-generation"""	,				model="""facebook/sam-vit-huge"""				)

							lowerCamelCase       =      image_segmenter("""http://images.cocodataset.org/val2017/000000039769.jpg"""	,				points_per_batch=256				)

							# Shortening by hashing
							lowerCamelCase       =      []
							for i, o in enumerate(outputs["""masks"""]				):
										new_outupt += [{"mask": mask_to_test_readable(_a				), "scores": outputs["scores"][i]}]

							# fmt: off
							self.assertEqual(
							    nested_simplify(_a	,				decimals=4				)	,				[
							        {"""mask""": {"""hash""": """115ad19f5f""", """shape""": (480, 640)}, """scores""": 1.0_444},
							        {"""mask""": {"""hash""": """6affa964c6""", """shape""": (480, 640)}, """scores""": 1.021},
							        {"""mask""": {"""hash""": """dfe28a0388""", """shape""": (480, 640)}, """scores""": 1.0_167},
							        {"""mask""": {"""hash""": """c0a5f4a318""", """shape""": (480, 640)}, """scores""": 1.0_132},
							        {"""mask""": {"""hash""": """fe8065c197""", """shape""": (480, 640)}, """scores""": 1.0_053},
							        {"""mask""": {"""hash""": """e2d0b7a0b7""", """shape""": (480, 640)}, """scores""": 0.9_967},
							        {"""mask""": {"""hash""": """453c7844bd""", """shape""": (480, 640)}, """scores""": 0.993},
							        {"""mask""": {"""hash""": """3d44f2926d""", """shape""": (480, 640)}, """scores""": 0.9_909},
							        {"""mask""": {"""hash""": """64033ddc3f""", """shape""": (480, 640)}, """scores""": 0.9_879},
							        {"""mask""": {"""hash""": """801064ff79""", """shape""": (480, 640)}, """scores""": 0.9_834},
							        {"""mask""": {"""hash""": """6172f276ef""", """shape""": (480, 640)}, """scores""": 0.9_716},
							        {"""mask""": {"""hash""": """b49e60e084""", """shape""": (480, 640)}, """scores""": 0.9_612},
							        {"""mask""": {"""hash""": """a811e775fd""", """shape""": (480, 640)}, """scores""": 0.9_599},
							        {"""mask""": {"""hash""": """a6a8ebcf4b""", """shape""": (480, 640)}, """scores""": 0.9_552},
							        {"""mask""": {"""hash""": """9d8257e080""", """shape""": (480, 640)}, """scores""": 0.9_532},
							        {"""mask""": {"""hash""": """32de6454a8""", """shape""": (480, 640)}, """scores""": 0.9_516},
							        {"""mask""": {"""hash""": """af3d4af2c8""", """shape""": (480, 640)}, """scores""": 0.9_499},
							        {"""mask""": {"""hash""": """3c6db475fb""", """shape""": (480, 640)}, """scores""": 0.9_483},
							        {"""mask""": {"""hash""": """c290813fb9""", """shape""": (480, 640)}, """scores""": 0.9_464},
							        {"""mask""": {"""hash""": """b6f0b8f606""", """shape""": (480, 640)}, """scores""": 0.943},
							        {"""mask""": {"""hash""": """92ce16bfdf""", """shape""": (480, 640)}, """scores""": 0.943},
							        {"""mask""": {"""hash""": """c749b25868""", """shape""": (480, 640)}, """scores""": 0.9_408},
							        {"""mask""": {"""hash""": """efb6cab859""", """shape""": (480, 640)}, """scores""": 0.9_335},
							        {"""mask""": {"""hash""": """1ff2eafb30""", """shape""": (480, 640)}, """scores""": 0.9_326},
							        {"""mask""": {"""hash""": """788b798e24""", """shape""": (480, 640)}, """scores""": 0.9_262},
							        {"""mask""": {"""hash""": """abea804f0e""", """shape""": (480, 640)}, """scores""": 0.8_999},
							        {"""mask""": {"""hash""": """7b9e8ddb73""", """shape""": (480, 640)}, """scores""": 0.8_986},
							        {"""mask""": {"""hash""": """cd24047c8a""", """shape""": (480, 640)}, """scores""": 0.8_984},
							        {"""mask""": {"""hash""": """6943e6bcbd""", """shape""": (480, 640)}, """scores""": 0.8_873},
							        {"""mask""": {"""hash""": """b5f47c9191""", """shape""": (480, 640)}, """scores""": 0.8_871}
							    ]	,				)
							# fmt: on





				@require_torch
				@slow
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      """facebook/sam-vit-huge"""
							lowerCamelCase       =      pipeline("""mask-generation"""	,				model=_a				)

							lowerCamelCase       =      image_segmenter(
							    """http://images.cocodataset.org/val2017/000000039769.jpg"""	,				pred_iou_thresh=1	,				points_per_batch=256				)

							# Shortening by hashing
							lowerCamelCase       =      []
							for i, o in enumerate(outputs["""masks"""]				):
										new_outupt += [{"mask": mask_to_test_readable(_a				), "scores": outputs["scores"][i]}]

							self.assertEqual(
							    nested_simplify(_a	,				decimals=4				)	,				[
							        {"""mask""": {"""hash""": """115ad19f5f""", """shape""": (480, 640)}, """scores""": 1.0_444},
							        {"""mask""": {"""hash""": """6affa964c6""", """shape""": (480, 640)}, """scores""": 1.0_210},
							        {"""mask""": {"""hash""": """dfe28a0388""", """shape""": (480, 640)}, """scores""": 1.0_167},
							        {"""mask""": {"""hash""": """c0a5f4a318""", """shape""": (480, 640)}, """scores""": 1.0_132},
							        {"""mask""": {"""hash""": """fe8065c197""", """shape""": (480, 640)}, """scores""": 1.0_053},
							    ]	,				)









"""simple docstring"""




import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


lowerCAmelCase							:    Optional[Any]  							=							"""sshleifer/bart-tiny-random"""
lowerCAmelCase							:    List[Any]  							=							"""patrickvonplaten/t5-tiny-random"""






@require_torch
class 					__magic_name__							( unittest.TestCase       ):






				'''simple docstring'''





				@cached_property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return AutoConfig.from_pretrained(_a				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase   ,     *lowerCamelCase       =      create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=1	,				d=1				)
							self.assertEqual(student.config.num_hidden_layers	,				1				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase   ,     *lowerCamelCase       =      create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=1	,				d=_a				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase   ,     *lowerCamelCase       =      create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=1	,				d=_a				)
							self.assertEqual(student.config.encoder_layers	,				1				)
							self.assertEqual(student.config.decoder_layers	,				self.teacher_config.encoder_layers				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase   ,     *lowerCamelCase       =      create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=1	,				d=1				)
							self.assertEqual(student.config.encoder_layers	,				1				)
							self.assertEqual(student.config.decoder_layers	,				1				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							with self.assertRaises(_a				):
										create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=_a	,				d=_a				)



