



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

     SCREAMING_SNAKE_CASE_:int					=						"""0.12"""  # assumed parallelism: 8






@require_flax
@is_staging_test
class SCREAMING_SNAKE_CASE__					(		unittest.TestCase   ):




    '''simple docstring'''






    @classmethod
    def       _lowerCAmelCase (	cls		):
        A			:	Union[str, Any]										=       TOKEN
        HfFolder.save_token(lowerCamelCase__		)






    @classmethod
    def       _lowerCAmelCase (	cls		):
        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       _lowerCAmelCase (	self		):
        A			:	Optional[int]										=       BertConfig(
            vocab_size=99,		hidden_size=32,		num_hidden_layers=5,		num_attention_heads=4,		intermediate_size=37		)
        A			:	Tuple										=       FlaxBertModel(lowerCamelCase__		)
        model.push_to_hub("""test-model-flax""",		use_auth_token=self._token		)

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

        A			:	Dict										=       flatten_dict(unfreeze(model.params		)		)
        A			:	Any										=       flatten_dict(unfreeze(new_model.params		)		)

        for key in base_params.keys():
            A			:	Optional[Any]										=       (base_params[key] - new_params[key]).sum().item()
            self.assertLessEqual(lowerCamelCase__,		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(lowerCamelCase__,		repo_id="""test-model-flax""",		push_to_hub=lowerCamelCase__,		use_auth_token=self._token		)

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

        A			:	Tuple										=       flatten_dict(unfreeze(model.params		)		)
        A			:	Any										=       flatten_dict(unfreeze(new_model.params		)		)

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






    def       _lowerCAmelCase (	self		):
        A			:	Optional[Any]										=       BertConfig(
            vocab_size=99,		hidden_size=32,		num_hidden_layers=5,		num_attention_heads=4,		intermediate_size=37		)
        A			:	int										=       FlaxBertModel(lowerCamelCase__		)
        model.push_to_hub("""valid_org/test-model-flax-org""",		use_auth_token=self._token		)

        A			:	Optional[int]										=       FlaxBertModel.from_pretrained("""valid_org/test-model-flax-org"""		)

        A			:	Tuple										=       flatten_dict(unfreeze(model.params		)		)
        A			:	List[Any]										=       flatten_dict(unfreeze(new_model.params		)		)

        for key in base_params.keys():
            A			:	List[str]										=       (base_params[key] - new_params[key]).sum().item()
            self.assertLessEqual(lowerCamelCase__,		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(
                lowerCamelCase__,		repo_id="""valid_org/test-model-flax-org""",		push_to_hub=lowerCamelCase__,		use_auth_token=self._token		)

        A			:	Any										=       FlaxBertModel.from_pretrained("""valid_org/test-model-flax-org"""		)

        A			:	Optional[Any]										=       flatten_dict(unfreeze(model.params		)		)
        A			:	Union[str, Any]										=       flatten_dict(unfreeze(new_model.params		)		)

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




def      __UpperCamelCase     (  _lowerCAmelCase				,					_lowerCAmelCase		)	->  List[str]:



    """simple docstring"""






    A			:	Any										=       True
    A			:	Optional[Any]										=       flatten_dict(modela.params		)
    A			:	Optional[int]										=       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:
            A			:	List[Any]										=       False

    return models_are_equal






@require_flax
class SCREAMING_SNAKE_CASE__					(		unittest.TestCase   ):




    '''simple docstring'''






    def       _lowerCAmelCase (	self		):
        A			:	Optional[int]										=       BertConfig.from_pretrained("""hf-internal-testing/tiny-bert-flax-only"""		)
        A			:	int										=       FlaxBertModel(lowerCamelCase__		)

        A			:	List[str]										=       """bert"""
        with tempfile.TemporaryDirectory() as tmp_dir:
            model.save_pretrained(os.path.join(lowerCamelCase__,		lowerCamelCase__		)		)

            with self.assertRaises(lowerCamelCase__		):
                A			:	Optional[int]										=       FlaxBertModel.from_pretrained(lowerCamelCase__		)

            A			:	Any										=       FlaxBertModel.from_pretrained(lowerCamelCase__,		subfolder=lowerCamelCase__		)

        self.assertTrue(check_models_equal(lowerCamelCase__,		lowerCamelCase__		)		)






    def       _lowerCAmelCase (	self		):
        A			:	Optional[Any]										=       BertConfig.from_pretrained("""hf-internal-testing/tiny-bert-flax-only"""		)
        A			:	Any										=       FlaxBertModel(lowerCamelCase__		)

        A			:	int										=       """bert"""
        with tempfile.TemporaryDirectory() as tmp_dir:
            model.save_pretrained(os.path.join(lowerCamelCase__,		lowerCamelCase__		),		max_shard_size="""10KB"""		)

            with self.assertRaises(lowerCamelCase__		):
                A			:	str										=       FlaxBertModel.from_pretrained(lowerCamelCase__		)

            A			:	Any										=       FlaxBertModel.from_pretrained(lowerCamelCase__,		subfolder=lowerCamelCase__		)

        self.assertTrue(check_models_equal(lowerCamelCase__,		lowerCamelCase__		)		)






    def       _lowerCAmelCase (	self		):
        A			:	Optional[int]										=       """bert"""
        A			:	Optional[Any]										=       """hf-internal-testing/tiny-random-bert-subfolder"""

        with self.assertRaises(lowerCamelCase__		):
            A			:	str										=       FlaxBertModel.from_pretrained(lowerCamelCase__		)

        A			:	Optional[Any]										=       FlaxBertModel.from_pretrained(lowerCamelCase__,		subfolder=lowerCamelCase__		)

        self.assertIsNotNone(lowerCamelCase__		)






    def       _lowerCAmelCase (	self		):
        A			:	Optional[int]										=       """bert"""
        A			:	int										=       """hf-internal-testing/tiny-random-bert-sharded-subfolder"""
        with self.assertRaises(lowerCamelCase__		):
            A			:	Optional[int]										=       FlaxBertModel.from_pretrained(lowerCamelCase__		)

        A			:	List[Any]										=       FlaxBertModel.from_pretrained(lowerCamelCase__,		subfolder=lowerCamelCase__		)

        self.assertIsNotNone(lowerCamelCase__		)







import os
from pathlib import Path




def      __UpperCamelCase     (  )	->  Any:



    """simple docstring"""






    from torch.utils.cpp_extension import load

    A			:	Any										=       Path(_lowerCAmelCase		).resolve().parent.parent.parent / """kernels""" / """deformable_detr"""
    A			:	int										=       [
        root / filename
        for filename in [
            """vision.cpp""",
            os.path.join("""cpu"""				,					"""ms_deform_attn_cpu.cpp"""		),
            os.path.join("""cuda"""				,					"""ms_deform_attn_cuda.cu"""		),
        ]
    ]

    load(
        """MultiScaleDeformableAttention"""				,					_lowerCAmelCase				,					with_cuda=_lowerCAmelCase				,					extra_include_paths=[str(_lowerCAmelCase		)]				,					extra_cflags=["""-DWITH_CUDA=1"""]				,					extra_cuda_cflags=[
            """-DCUDA_HAS_FP16=1""",
            """-D__CUDA_NO_HALF_OPERATORS__""",
            """-D__CUDA_NO_HALF_CONVERSIONS__""",
            """-D__CUDA_NO_HALF2_OPERATORS__""",
        ]				,					)

    import MultiScaleDeformableAttention as MSDA

    return MSDA


