



'''simple docstring'''




import argparse
import hashlib
import os
import urllib
import warnings

import torch
from torch import nn
from tqdm import tqdm

from transformers import WhisperConfig, WhisperForConditionalGeneration


UpperCamelCase__       :	Dict    = {
    '''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3dd57d32accea0b295c96e26691aa14d8822fac7d9d27d5dc00b4ca2826dd03/tiny.en.pt''',
    '''tiny''': '''https://openaipublic.azureedge.net/main/whisper/models/65147644a518d12f04e32d6f3b26facc3f8dd46e5390956a9424a650c0ce22b9/tiny.pt''',
    '''base.en''': '''https://openaipublic.azureedge.net/main/whisper/models/25a8566e1d0c1e2231d1c762132cd20e0f96a85d16145c3a00adf5d1ac670ead/base.en.pt''',
    '''base''': '''https://openaipublic.azureedge.net/main/whisper/models/ed3a0b6b1c0edf879ad9b11b1af5a0e6ab5db9205f891f668f8b0e6c6326e34e/base.pt''',
    '''small.en''': '''https://openaipublic.azureedge.net/main/whisper/models/f953ad0fd29cacd07d5a9eda5624af0f6bcf2258be67c92b79389873d91e0872/small.en.pt''',
    '''small''': '''https://openaipublic.azureedge.net/main/whisper/models/9ecf779972d90ba49c06d968637d720dd632c55bbf19d441fb42bf17a411e794/small.pt''',
    '''medium.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d7440d1dc186f76616474e0ff0b3b6b879abc9d1a4926b7adfa41db2d497ab4f/medium.en.pt''',
    '''medium''': '''https://openaipublic.azureedge.net/main/whisper/models/345ae4da62f9b3d59415adc60127b97c714f32e89e936602e85993674d08dcb1/medium.pt''',
    '''large''': '''https://openaipublic.azureedge.net/main/whisper/models/e4b87e7e0bf463eb8e6956e646f1e277e901512310def2c24bf0e11bd3c28e9a/large.pt''',
    '''large-v2''': '''https://openaipublic.azureedge.net/main/whisper/models/81f7c96c852ee8fc832187b0132e569d6c3065a3252ed18e56effd0b6a73e524/large-v2.pt''',
}


def 				lowerCAmelCase_   (	_lowerCamelCase:   Tuple					):
		__SCREAMING_SNAKE_CASE       :		Dict           =		["""layers""", """blocks"""]
		for k in ignore_keys:
				state_dict.pop(_lowerCamelCase       ,      _lowerCamelCase					)


UpperCamelCase__       :	str    = {
    '''blocks''': '''layers''',
    '''mlp.0''': '''fc1''',
    '''mlp.2''': '''fc2''',
    '''mlp_ln''': '''final_layer_norm''',
    '''.attn.query''': '''.self_attn.q_proj''',
    '''.attn.key''': '''.self_attn.k_proj''',
    '''.attn.value''': '''.self_attn.v_proj''',
    '''.attn_ln''': '''.self_attn_layer_norm''',
    '''.attn.out''': '''.self_attn.out_proj''',
    '''.cross_attn.query''': '''.encoder_attn.q_proj''',
    '''.cross_attn.key''': '''.encoder_attn.k_proj''',
    '''.cross_attn.value''': '''.encoder_attn.v_proj''',
    '''.cross_attn_ln''': '''.encoder_attn_layer_norm''',
    '''.cross_attn.out''': '''.encoder_attn.out_proj''',
    '''decoder.ln.''': '''decoder.layer_norm.''',
    '''encoder.ln.''': '''encoder.layer_norm.''',
    '''token_embedding''': '''embed_tokens''',
    '''encoder.positional_embedding''': '''encoder.embed_positions.weight''',
    '''decoder.positional_embedding''': '''decoder.embed_positions.weight''',
    '''ln_post''': '''layer_norm''',
}


def 				lowerCAmelCase_   (	_lowerCamelCase:   List[str]					):
		__SCREAMING_SNAKE_CASE       :		Optional[int]           =		list(s_dict.keys()					)
		for key in keys:
				__SCREAMING_SNAKE_CASE       :		Any           =		key
				for k, v in WHISPER_MAPPING.items():
						if k in key:
								__SCREAMING_SNAKE_CASE       :		Dict           =		new_key.replace(_lowerCamelCase       ,      _lowerCamelCase					)

				print(F"{key} -> {new_key}"					)

				__SCREAMING_SNAKE_CASE       :		List[Any]           =		s_dict.pop(_lowerCamelCase					)
		return s_dict


def 				lowerCAmelCase_   (	_lowerCamelCase:   Optional[int]					):
		__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Any           =		emb.weight.shape
		__SCREAMING_SNAKE_CASE       :		Optional[int]           =		nn.Linear(_lowerCamelCase       ,      _lowerCamelCase       ,      bias=_lowerCamelCase					)
		__SCREAMING_SNAKE_CASE       :		List[str]           =		emb.weight.data
		return lin_layer


def 				lowerCAmelCase_   (	_lowerCamelCase:   str       ,      _lowerCamelCase:   str					):
		os.makedirs(_lowerCamelCase       ,      exist_ok=_lowerCamelCase					)
		__SCREAMING_SNAKE_CASE       :		List[Any]           =		os.path.basename(_lowerCamelCase					)

		__SCREAMING_SNAKE_CASE       :		List[Any]           =		url.split("""/"""					)[-2]
		__SCREAMING_SNAKE_CASE       :		int           =		os.path.join(_lowerCamelCase       ,      _lowerCamelCase					)

		if os.path.exists(_lowerCamelCase					) and not os.path.isfile(_lowerCamelCase					):
				raise RuntimeError(F"{download_target} exists and is not a regular file"					)

		if os.path.isfile(_lowerCamelCase					):
				__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		open(_lowerCamelCase       ,      """rb"""					).read()
				if hashlib.shaaaa(_lowerCamelCase					).hexdigest() == expected_shaaaa:
						return model_bytes
				else:
						warnings.warn(F"{download_target} exists, but the SHA256 checksum does not match; re-downloading the file"					)

		with urllib.request.urlopen(_lowerCamelCase					) as source, open(_lowerCamelCase       ,      """wb"""					) as output:
				with tqdm(
				    total=int(source.info().get("""Content-Length"""					)					)       ,      ncols=80       ,      unit="""iB"""       ,      unit_scale=_lowerCamelCase       ,      unit_divisor=10_24					) as loop:
						while True:
								__SCREAMING_SNAKE_CASE       :		List[Any]           =		source.read(81_92					)
								if not buffer:
										break

								output.write(_lowerCamelCase					)
								loop.update(len(_lowerCamelCase					)					)

		__SCREAMING_SNAKE_CASE       :		Any           =		open(_lowerCamelCase       ,      """rb"""					).read()
		if hashlib.shaaaa(_lowerCamelCase					).hexdigest() != expected_shaaaa:
				raise RuntimeError(
				    """Model has been downloaded but the SHA256 checksum does not not match. Please retry loading the model."""					)

		return model_bytes


def 				lowerCAmelCase_   (	_lowerCamelCase:   Optional[int]       ,      _lowerCamelCase:   int					):
		if ".pt" not in checkpoint_path:
				__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		_download(_MODELS[checkpoint_path]					)
		else:
				__SCREAMING_SNAKE_CASE       :		Tuple           =		torch.load(_lowerCamelCase       ,      map_location="""cpu"""					)
		__SCREAMING_SNAKE_CASE       :		Tuple           =		original_checkpoint["""dims"""]
		__SCREAMING_SNAKE_CASE       :		int           =		original_checkpoint["""model_state_dict"""]
		__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		state_dict["""decoder.token_embedding.weight"""]
		remove_ignore_keys_(_lowerCamelCase					)
		rename_keys(_lowerCamelCase					)
		__SCREAMING_SNAKE_CASE       :		Optional[int]           =		True
		__SCREAMING_SNAKE_CASE       :		Any           =		state_dict["""decoder.layers.0.fc1.weight"""].shape[0]

		__SCREAMING_SNAKE_CASE       :		Optional[int]           =		WhisperConfig(
		    vocab_size=dimensions["""n_vocab"""]       ,      encoder_ffn_dim=_lowerCamelCase       ,      decoder_ffn_dim=_lowerCamelCase       ,      num_mel_bins=dimensions["""n_mels"""]       ,      d_model=dimensions["""n_audio_state"""]       ,      max_target_positions=dimensions["""n_text_ctx"""]       ,      encoder_layers=dimensions["""n_audio_layer"""]       ,      encoder_attention_heads=dimensions["""n_audio_head"""]       ,      decoder_layers=dimensions["""n_text_layer"""]       ,      decoder_attention_heads=dimensions["""n_text_state"""]       ,      max_source_positions=dimensions["""n_audio_ctx"""]       ,      )

		__SCREAMING_SNAKE_CASE       :		List[Any]           =		WhisperForConditionalGeneration(_lowerCamelCase					)
		__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Tuple           =		model.model.load_state_dict(_lowerCamelCase       ,      strict=_lowerCamelCase					)
		if len(_lowerCamelCase					) > 0 and not set(_lowerCamelCase					) <= {
		    "encoder.embed_positions.weights",
		    "decoder.embed_positions.weights",
		}:
				raise ValueError(
				    """Only `encoder.embed_positions.weights` and `decoder.embed_positions.weights`  are allowed to be missing,"""
				    F" but all the following weights are missing {missing}"					)

		if tie_embeds:
				__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		make_linear_from_emb(model.model.decoder.embed_tokens					)
		else:
				__SCREAMING_SNAKE_CASE       :		int           =		proj_out_weights

		model.save_pretrained(_lowerCamelCase					)


if __name__ == "__main__":
						UpperCamelCase__       :	int    = argparse.ArgumentParser()
						# # Required parameters
						parser.add_argument('''--checkpoint_path''', type=str, help='''Patht to the downloaded checkpoints''')
						parser.add_argument('''--pytorch_dump_folder_path''', default=None, type=str, help='''Path to the output PyTorch model.''')
						UpperCamelCase__       :	Optional[Any]    = parser.parse_args()

						convert_openai_whisper_to_tfms(args.checkpoint_path, args.pytorch_dump_folder_path)




'''simple docstring'''




import unittest

from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
						from PIL import Image
else:






						class 						_UpperCamelCase  :


									'''simple docstring'''

									@staticmethod
									def UpperCamelCase__					(							*lowerCAmelCase__     : Any							,     **lowerCAmelCase__     : Any						):





											"""simple docstring"""






											pass






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


			'''simple docstring'''

			_A      :		Optional[int]			    =		MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING

			def UpperCamelCase__					(							self     : str							,     lowerCAmelCase__     : Dict							,     lowerCAmelCase__     : Tuple							,     lowerCAmelCase__     : Optional[Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Any           =		pipeline(
					    """zero-shot-object-detection"""							,     model="""hf-internal-testing/tiny-random-owlvit-object-detection"""						)

					__SCREAMING_SNAKE_CASE       :		Any           =		[
					    {
					        """image""": """./tests/fixtures/tests_samples/COCO/000000039769.png""",
					        """candidate_labels""": ["""cat""", """remote""", """couch"""],
					    }
					]
					return object_detector, examples

			def UpperCamelCase__					(							self     : int							,     lowerCAmelCase__     : Optional[Any]							,     lowerCAmelCase__     : List[Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		object_detector(examples[0]							,     threshold=0.0						)

					__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		len(lowerCAmelCase__						)
					self.assertGreater(lowerCAmelCase__							,     0						)
					self.assertEqual(
					    lowerCAmelCase__							,     [
					        {
					            """score""": ANY(lowerCAmelCase__						),
					            """label""": ANY(lowerCAmelCase__						),
					            """box""": {"""xmin""": ANY(lowerCAmelCase__						), """ymin""": ANY(lowerCAmelCase__						), """xmax""": ANY(lowerCAmelCase__						), """ymax""": ANY(lowerCAmelCase__						)},
					        }
					        for i in range(lowerCAmelCase__						)
					    ]							,     )

			@require_tf
			@unittest.skip("""Zero Shot Object Detection not implemented in TF"""						)
			def UpperCamelCase__					(							self     : Optional[int]						):





					"""simple docstring"""






					pass

			@require_torch
			def UpperCamelCase__					(							self     : Optional[int]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		int           =		pipeline(
					    """zero-shot-object-detection"""							,     model="""hf-internal-testing/tiny-random-owlvit-object-detection"""						)

					__SCREAMING_SNAKE_CASE       :		int           =		object_detector(
					    """./tests/fixtures/tests_samples/COCO/000000039769.png"""							,     candidate_labels=["""cat""", """remote""", """couch"""]							,     threshold=0.64							,     )

					self.assertEqual(
					    nested_simplify(lowerCAmelCase__							,     decimals=4						)							,     [
					        {"""score""": 0.72_35, """label""": """cat""", """box""": {"""xmin""": 2_0_4, """ymin""": 1_6_7, """xmax""": 2_3_2, """ymax""": 1_9_0}},
					        {"""score""": 0.72_18, """label""": """remote""", """box""": {"""xmin""": 2_0_4, """ymin""": 1_6_7, """xmax""": 2_3_2, """ymax""": 1_9_0}},
					        {"""score""": 0.71_84, """label""": """couch""", """box""": {"""xmin""": 2_0_4, """ymin""": 1_6_7, """xmax""": 2_3_2, """ymax""": 1_9_0}},
					        {"""score""": 0.67_48, """label""": """remote""", """box""": {"""xmin""": 5_7_1, """ymin""": 8_3, """xmax""": 5_9_8, """ymax""": 1_0_3}},
					        {"""score""": 0.66_56, """label""": """cat""", """box""": {"""xmin""": 5_7_1, """ymin""": 8_3, """xmax""": 5_9_8, """ymax""": 1_0_3}},
					        {"""score""": 0.66_14, """label""": """couch""", """box""": {"""xmin""": 5_7_1, """ymin""": 8_3, """xmax""": 5_9_8, """ymax""": 1_0_3}},
					        {"""score""": 0.64_56, """label""": """remote""", """box""": {"""xmin""": 4_9_4, """ymin""": 1_0_5, """xmax""": 5_2_1, """ymax""": 1_2_7}},
					        {"""score""": 0.6_42, """label""": """remote""", """box""": {"""xmin""": 6_7, """ymin""": 2_7_4, """xmax""": 9_3, """ymax""": 2_9_7}},
					        {"""score""": 0.64_19, """label""": """cat""", """box""": {"""xmin""": 4_9_4, """ymin""": 1_0_5, """xmax""": 5_2_1, """ymax""": 1_2_7}},
					    ]							,     )

					__SCREAMING_SNAKE_CASE       :		List[Any]           =		object_detector(
					    [
					        {
					            """image""": """./tests/fixtures/tests_samples/COCO/000000039769.png""",
					            """candidate_labels""": ["""cat""", """remote""", """couch"""],
					        }
					    ]							,     threshold=0.64							,     )

					self.assertEqual(
					    nested_simplify(lowerCAmelCase__							,     decimals=4						)							,     [
					        [
					            {"""score""": 0.72_35, """label""": """cat""", """box""": {"""xmin""": 2_0_4, """ymin""": 1_6_7, """xmax""": 2_3_2, """ymax""": 1_9_0}},
					            {"""score""": 0.72_18, """label""": """remote""", """box""": {"""xmin""": 2_0_4, """ymin""": 1_6_7, """xmax""": 2_3_2, """ymax""": 1_9_0}},
					            {"""score""": 0.71_84, """label""": """couch""", """box""": {"""xmin""": 2_0_4, """ymin""": 1_6_7, """xmax""": 2_3_2, """ymax""": 1_9_0}},
					            {"""score""": 0.67_48, """label""": """remote""", """box""": {"""xmin""": 5_7_1, """ymin""": 8_3, """xmax""": 5_9_8, """ymax""": 1_0_3}},
					            {"""score""": 0.66_56, """label""": """cat""", """box""": {"""xmin""": 5_7_1, """ymin""": 8_3, """xmax""": 5_9_8, """ymax""": 1_0_3}},
					            {"""score""": 0.66_14, """label""": """couch""", """box""": {"""xmin""": 5_7_1, """ymin""": 8_3, """xmax""": 5_9_8, """ymax""": 1_0_3}},
					            {"""score""": 0.64_56, """label""": """remote""", """box""": {"""xmin""": 4_9_4, """ymin""": 1_0_5, """xmax""": 5_2_1, """ymax""": 1_2_7}},
					            {"""score""": 0.6_42, """label""": """remote""", """box""": {"""xmin""": 6_7, """ymin""": 2_7_4, """xmax""": 9_3, """ymax""": 2_9_7}},
					            {"""score""": 0.64_19, """label""": """cat""", """box""": {"""xmin""": 4_9_4, """ymin""": 1_0_5, """xmax""": 5_2_1, """ymax""": 1_2_7}},
					        ]
					    ]							,     )

			@require_torch
			@slow
			def UpperCamelCase__					(							self     : str						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Any           =		pipeline("""zero-shot-object-detection"""						)

					__SCREAMING_SNAKE_CASE       :		List[str]           =		object_detector(
					    """http://images.cocodataset.org/val2017/000000039769.jpg"""							,     candidate_labels=["""cat""", """remote""", """couch"""]							,     )
					self.assertEqual(
					    nested_simplify(lowerCAmelCase__							,     decimals=4						)							,     [
					        {"""score""": 0.28_68, """label""": """cat""", """box""": {"""xmin""": 3_2_4, """ymin""": 2_0, """xmax""": 6_4_0, """ymax""": 3_7_3}},
					        {"""score""": 0.2_77, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_2, """xmax""": 1_7_7, """ymax""": 1_1_5}},
					        {"""score""": 0.25_37, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 5_5, """xmax""": 3_1_5, """ymax""": 4_7_2}},
					        {"""score""": 0.14_74, """label""": """remote""", """box""": {"""xmin""": 3_3_5, """ymin""": 7_4, """xmax""": 3_7_1, """ymax""": 1_8_7}},
					        {"""score""": 0.12_08, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 6_4_2, """ymax""": 4_7_6}},
					    ]							,     )

					__SCREAMING_SNAKE_CASE       :		Dict           =		object_detector(
					    [
					        {
					            """image""": """http://images.cocodataset.org/val2017/000000039769.jpg""",
					            """candidate_labels""": ["""cat""", """remote""", """couch"""],
					        },
					        {
					            """image""": """http://images.cocodataset.org/val2017/000000039769.jpg""",
					            """candidate_labels""": ["""cat""", """remote""", """couch"""],
					        },
					    ]							,     )
					self.assertEqual(
					    nested_simplify(lowerCAmelCase__							,     decimals=4						)							,     [
					        [
					            {"""score""": 0.28_68, """label""": """cat""", """box""": {"""xmin""": 3_2_4, """ymin""": 2_0, """xmax""": 6_4_0, """ymax""": 3_7_3}},
					            {"""score""": 0.2_77, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_2, """xmax""": 1_7_7, """ymax""": 1_1_5}},
					            {"""score""": 0.25_37, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 5_5, """xmax""": 3_1_5, """ymax""": 4_7_2}},
					            {"""score""": 0.14_74, """label""": """remote""", """box""": {"""xmin""": 3_3_5, """ymin""": 7_4, """xmax""": 3_7_1, """ymax""": 1_8_7}},
					            {"""score""": 0.12_08, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 6_4_2, """ymax""": 4_7_6}},
					        ],
					        [
					            {"""score""": 0.28_68, """label""": """cat""", """box""": {"""xmin""": 3_2_4, """ymin""": 2_0, """xmax""": 6_4_0, """ymax""": 3_7_3}},
					            {"""score""": 0.2_77, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_2, """xmax""": 1_7_7, """ymax""": 1_1_5}},
					            {"""score""": 0.25_37, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 5_5, """xmax""": 3_1_5, """ymax""": 4_7_2}},
					            {"""score""": 0.14_74, """label""": """remote""", """box""": {"""xmin""": 3_3_5, """ymin""": 7_4, """xmax""": 3_7_1, """ymax""": 1_8_7}},
					            {"""score""": 0.12_08, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 6_4_2, """ymax""": 4_7_6}},
					        ],
					    ]							,     )

			@require_tf
			@unittest.skip("""Zero Shot Object Detection not implemented in TF"""						)
			def UpperCamelCase__					(							self     : Any						):





					"""simple docstring"""






					pass

			@require_torch
			@slow
			def UpperCamelCase__					(							self     : List[str]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Dict           =		0.2
					__SCREAMING_SNAKE_CASE       :		Dict           =		pipeline("""zero-shot-object-detection"""						)

					__SCREAMING_SNAKE_CASE       :		Any           =		object_detector(
					    """http://images.cocodataset.org/val2017/000000039769.jpg"""							,     candidate_labels=["""cat""", """remote""", """couch"""]							,     threshold=lowerCAmelCase__							,     )
					self.assertEqual(
					    nested_simplify(lowerCAmelCase__							,     decimals=4						)							,     [
					        {"""score""": 0.28_68, """label""": """cat""", """box""": {"""xmin""": 3_2_4, """ymin""": 2_0, """xmax""": 6_4_0, """ymax""": 3_7_3}},
					        {"""score""": 0.2_77, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_2, """xmax""": 1_7_7, """ymax""": 1_1_5}},
					        {"""score""": 0.25_37, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 5_5, """xmax""": 3_1_5, """ymax""": 4_7_2}},
					    ]							,     )



			@require_torch
			@slow
			def UpperCamelCase__					(							self     : int						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		str           =		2
					__SCREAMING_SNAKE_CASE       :		int           =		pipeline("""zero-shot-object-detection"""						)

					__SCREAMING_SNAKE_CASE       :		int           =		object_detector(
					    """http://images.cocodataset.org/val2017/000000039769.jpg"""							,     candidate_labels=["""cat""", """remote""", """couch"""]							,     top_k=lowerCAmelCase__							,     )
					self.assertEqual(
					    nested_simplify(lowerCAmelCase__							,     decimals=4						)							,     [
					        {"""score""": 0.28_68, """label""": """cat""", """box""": {"""xmin""": 3_2_4, """ymin""": 2_0, """xmax""": 6_4_0, """ymax""": 3_7_3}},
					        {"""score""": 0.2_77, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_2, """xmax""": 1_7_7, """ymax""": 1_1_5}},
					    ]							,     )