



import tempfile
import unittest

import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax


if is_flax_available():
	import os

	from flax.core.frozen_dict import unfreeze
	from flax.traverse_util import flatten_dict

	from transformers import FlaxBertModel

	_lowerCAmelCase	:   List[Any]    =   "0.12"  # assumed parallelism: 8


@require_flax
@is_staging_test
class 	__snake_case   ( unittest.TestCase ):
		@classmethod
		def 						SCREAMING_SNAKE_CASE_					(							cls						):







						"""simple docstring"""
						lowerCAmelCase__		  =  TOKEN
						HfFolder.save_token(a_						)
		@classmethod
		def 						SCREAMING_SNAKE_CASE_					(							cls						):







						"""simple docstring"""
						try:
										delete_repo(token=cls._token    ,repo_id='test-model-flax'						)
						except HTTPError:
										pass

						try:
										delete_repo(token=cls._token    ,repo_id='valid_org/test-model-flax-org'						)
						except HTTPError:
										pass
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  BertConfig(
						    vocab_size=99    ,hidden_size=32    ,num_hidden_layers=5    ,num_attention_heads=4    ,intermediate_size=37						)
						lowerCAmelCase__		  =  FlaxBertModel(a_						)
						model.push_to_hub('test-model-flax'    ,use_auth_token=self._token						)

						lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(f'{USER}/test-model-flax'						)

						lowerCAmelCase__		  =  flatten_dict(unfreeze(model.params						)						)
						lowerCAmelCase__		  =  flatten_dict(unfreeze(new_model.params						)						)

						for key in base_params.keys():
										lowerCAmelCase__		  =  (base_params[key] - new_params[key]).sum().item()
										self.assertLessEqual(a_    ,1e-3    ,msg=f'{key} not identical'						)

						# Reset repo
						delete_repo(token=self._token    ,repo_id='test-model-flax'						)

						# Push to hub via save_pretrained
						with tempfile.TemporaryDirectory() as tmp_dir:
										model.save_pretrained(a_    ,repo_id='test-model-flax'    ,push_to_hub=a_    ,use_auth_token=self._token						)

						lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(f'{USER}/test-model-flax'						)

						lowerCAmelCase__		  =  flatten_dict(unfreeze(model.params						)						)
						lowerCAmelCase__		  =  flatten_dict(unfreeze(new_model.params						)						)

						for key in base_params.keys():
										lowerCAmelCase__		  =  (base_params[key] - new_params[key]).sum().item()
										self.assertLessEqual(a_    ,1e-3    ,msg=f'{key} not identical'						)



		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  BertConfig(
						    vocab_size=99    ,hidden_size=32    ,num_hidden_layers=5    ,num_attention_heads=4    ,intermediate_size=37						)
						lowerCAmelCase__		  =  FlaxBertModel(a_						)
						model.push_to_hub('valid_org/test-model-flax-org'    ,use_auth_token=self._token						)

						lowerCAmelCase__		  =  FlaxBertModel.from_pretrained('valid_org/test-model-flax-org'						)

						lowerCAmelCase__		  =  flatten_dict(unfreeze(model.params						)						)
						lowerCAmelCase__		  =  flatten_dict(unfreeze(new_model.params						)						)

						for key in base_params.keys():
										lowerCAmelCase__		  =  (base_params[key] - new_params[key]).sum().item()
										self.assertLessEqual(a_    ,1e-3    ,msg=f'{key} not identical'						)

						# Reset repo
						delete_repo(token=self._token    ,repo_id='valid_org/test-model-flax-org'						)

						# Push to hub via save_pretrained
						with tempfile.TemporaryDirectory() as tmp_dir:
										model.save_pretrained(
										    a_    ,repo_id='valid_org/test-model-flax-org'    ,push_to_hub=a_    ,use_auth_token=self._token						)

						lowerCAmelCase__		  =  FlaxBertModel.from_pretrained('valid_org/test-model-flax-org'						)

						lowerCAmelCase__		  =  flatten_dict(unfreeze(model.params						)						)
						lowerCAmelCase__		  =  flatten_dict(unfreeze(new_model.params						)						)

						for key in base_params.keys():
										lowerCAmelCase__		  =  (base_params[key] - new_params[key]).sum().item()
										self.assertLessEqual(a_    ,1e-3    ,msg=f'{key} not identical'						)







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__					)	->     Union[str, Any]:



				"""simple docstring"""





				lowerCAmelCase__		  =  True
				lowerCAmelCase__		  =  flatten_dict(modela.params					)
				lowerCAmelCase__		  =  flatten_dict(modela.params					)
				for key in flat_params_a.keys():
								if np.sum(np.abs(flat_params_a[key] - flat_params_a[key]					)					) > 1E-4:
												lowerCAmelCase__		  =  False

				return models_are_equal


@require_flax
class 	__snake_case   ( unittest.TestCase ):
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  BertConfig.from_pretrained('hf-internal-testing/tiny-bert-flax-only'						)
						lowerCAmelCase__		  =  FlaxBertModel(a_						)

						lowerCAmelCase__		  =  'bert'
						with tempfile.TemporaryDirectory() as tmp_dir:
										model.save_pretrained(os.path.join(a_    ,a_						)						)

										with self.assertRaises(a_						):
														lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(a_						)

										lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(a_    ,subfolder=a_						)

						self.assertTrue(check_models_equal(a_    ,a_						)						)
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  BertConfig.from_pretrained('hf-internal-testing/tiny-bert-flax-only'						)
						lowerCAmelCase__		  =  FlaxBertModel(a_						)

						lowerCAmelCase__		  =  'bert'
						with tempfile.TemporaryDirectory() as tmp_dir:
										model.save_pretrained(os.path.join(a_    ,a_						)    ,max_shard_size='10KB'						)

										with self.assertRaises(a_						):
														lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(a_						)

										lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(a_    ,subfolder=a_						)

						self.assertTrue(check_models_equal(a_    ,a_						)						)
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  'bert'
						lowerCAmelCase__		  =  'hf-internal-testing/tiny-random-bert-subfolder'

						with self.assertRaises(a_						):
										lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(a_						)

						lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(a_    ,subfolder=a_						)

						self.assertIsNotNone(a_						)



		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  'bert'
						lowerCAmelCase__		  =  'hf-internal-testing/tiny-random-bert-sharded-subfolder'
						with self.assertRaises(a_						):
										lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(a_						)

						lowerCAmelCase__		  =  FlaxBertModel.from_pretrained(a_    ,subfolder=a_						)

						self.assertIsNotNone(a_						)





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowerCAmelCase	:   Any    =   {
    "configuration_chinese_clip": [
        "CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ChineseCLIPConfig",
        "ChineseCLIPOnnxConfig",
        "ChineseCLIPTextConfig",
        "ChineseCLIPVisionConfig",
    ],
    "processing_chinese_clip": ["ChineseCLIPProcessor"],
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCAmelCase	:   str    =   ["ChineseCLIPFeatureExtractor"]
	_lowerCAmelCase	:   Any    =   ["ChineseCLIPImageProcessor"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCAmelCase	:   Optional[int]    =   [
	    "CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "ChineseCLIPModel",
	    "ChineseCLIPPreTrainedModel",
	    "ChineseCLIPTextModel",
	    "ChineseCLIPVisionModel",
	]

if TYPE_CHECKING:
	from .configuration_chinese_clip import (
	    CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    ChineseCLIPConfig,
	    ChineseCLIPOnnxConfig,
	    ChineseCLIPTextConfig,
	    ChineseCLIPVisionConfig,
	)
	from .processing_chinese_clip import ChineseCLIPProcessor

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_chinese_clip import (
		    CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ChineseCLIPModel,
		    ChineseCLIPPreTrainedModel,
		    ChineseCLIPTextModel,
		    ChineseCLIPVisionModel,
		)

else:
	import sys

	_lowerCAmelCase	:   Any    =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
