






"""simple docstring"""







import collections
import tempfile
import unittest

import numpy as np

from transformers.testing_utils import (
    is_pt_flax_cross_test,
    require_flax,
    require_torch,
    require_vision,
    slow,
    torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_vision_available

from ...test_modeling_flax_common import floats_tensor, ids_tensor, random_attention_mask
from ..bert.test_modeling_flax_bert import FlaxBertModelTester
from ..clip.test_modeling_flax_clip import FlaxCLIPVisionModelTester
from ..vit.test_modeling_flax_vit import FlaxViTModelTester


if is_flax_available():
			from transformers import (
			    FlaxBertModel,
			    FlaxCLIPVisionModel,
			    FlaxVisionTextDualEncoderModel,
			    FlaxViTModel,
			    VisionTextDualEncoderConfig,
			    VisionTextDualEncoderProcessor,
			)
			from transformers.modeling_flax_pytorch_utils import (
			    convert_pytorch_state_dict_to_flax,
			    load_flax_weights_in_pytorch_model,
			)


if is_torch_available():
			import torch

			from transformers import VisionTextDualEncoderModel

if is_vision_available():
			from PIL import Image





def 						lowercase__(A						)    ->Dict:




						"""simple docstring"""



						if isinstance(A ,		collections.abc.Iterable						):
												return x
						return (x, x)


@require_flax
class    __UpperCAmelCase:




						"""simple docstring"""




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												pass




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												pass




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												pass




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				Optional[Any]=	np.abs((a - b)      ).max()
												self.assertLessEqual(snake_case__	,  snake_case__	,  F'''Difference between torch and flax is {diff} (>= {tol}).'''      )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__	,  snake_case__	,  snake_case__=None	,  **snake_case__      ):
												'''simple docstring'''
												lowercase__    :				int=	VisionTextDualEncoderConfig.from_vision_text_configs(snake_case__	,  snake_case__      )

												lowercase__    :				Any=	FlaxVisionTextDualEncoderModel(snake_case__      )

												lowercase__    :				Optional[int]=	model(input_ids=snake_case__	,  pixel_values=snake_case__	,  attention_mask=snake_case__      )

												self.assertEqual(output["text_embeds"].shape	,  (input_ids.shape[0], config.projection_dim)      )
												self.assertEqual(output["image_embeds"].shape	,  (pixel_values.shape[0], config.projection_dim)      )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__	,  snake_case__	,  snake_case__=None	,  **snake_case__      ):
												'''simple docstring'''
												lowercase__,     lowercase__    :				List[str]=	self.get_vision_text_model(snake_case__	,  snake_case__      )
												lowercase__    :				str=	{"vision_model": vision_model, "text_model": text_model}
												lowercase__    :				Dict=	FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(**snake_case__      )

												lowercase__    :				Union[str, Any]=	model(input_ids=snake_case__	,  pixel_values=snake_case__	,  attention_mask=snake_case__      )

												self.assertEqual(output["text_embeds"].shape	,  (input_ids.shape[0], model.config.projection_dim)      )
												self.assertEqual(output["image_embeds"].shape	,  (pixel_values.shape[0], model.config.projection_dim)      )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__	,  snake_case__	,  snake_case__=None	,  **snake_case__      ):
												'''simple docstring'''
												lowercase__,     lowercase__    :				Optional[Any]=	self.get_vision_text_model(snake_case__	,  snake_case__      )
												lowercase__    :				int=	{"vision_model": vision_model, "text_model": text_model}
												lowercase__    :				int=	FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(**snake_case__      )

												lowercase__    :				List[str]=	model(input_ids=snake_case__	,  pixel_values=snake_case__	,  attention_mask=snake_case__      )
												lowercase__    :				int=	output[0]

												with tempfile.TemporaryDirectory() as tmpdirname:
																		model.save_pretrained(snake_case__      )
																		lowercase__    :				Optional[Any]=	FlaxVisionTextDualEncoderModel.from_pretrained(snake_case__      )

																		lowercase__    :				Optional[int]=	model(input_ids=snake_case__	,  pixel_values=snake_case__	,  attention_mask=snake_case__      )
																		lowercase__    :				List[str]=	after_output[0]
																		lowercase__    :				Optional[Any]=	np.amax(np.abs(out_a - out_a      )      )
																		self.assertLessEqual(snake_case__	,  1e-3      )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__	,  snake_case__	,  snake_case__=None	,  **snake_case__      ):
												'''simple docstring'''
												lowercase__,     lowercase__    :				Optional[Any]=	self.get_vision_text_model(snake_case__	,  snake_case__      )
												lowercase__    :				Any=	{"vision_model": vision_model, "text_model": text_model}
												lowercase__    :				List[Any]=	FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(**snake_case__      )

												lowercase__    :				int=	model(
												    input_ids=snake_case__	,  pixel_values=snake_case__	,  attention_mask=snake_case__	,  output_attentions=snake_case__      )

												lowercase__    :				int=	output.vision_model_output.attentions
												self.assertEqual(len(snake_case__      )	,  vision_config.num_hidden_layers      )

												# in ViT, the seq_len equals the number of patches + 1 (we add 1 for the [CLS] token)
												lowercase__    :				Any=	to_atuple(vision_model.config.image_size      )
												lowercase__    :				str=	to_atuple(vision_model.config.patch_size      )
												lowercase__    :				List[Any]=	(image_size[1] // patch_size[1]) * (image_size[0] // patch_size[0])
												lowercase__    :				int=	num_patches + 1
												self.assertEqual(vision_attentions[0].shape[-3:]	,  (vision_config.num_attention_heads, seq_len, seq_len)      )

												lowercase__    :				Tuple=	output.text_model_output.attentions
												self.assertEqual(len(snake_case__      )	,  text_config.num_hidden_layers      )

												self.assertEqual(
												    text_attentions[0].shape[-3:]	,  (text_config.num_attention_heads, input_ids.shape[-1], input_ids.shape[-1])	,  )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												pt_model.to(snake_case__      )
												pt_model.eval()

												# prepare inputs
												lowercase__    :				Union[str, Any]=	inputs_dict
												lowercase__    :				Any=	{k: torch.tensor(v.tolist()      ) for k, v in flax_inputs.items()}

												with torch.no_grad():
																		lowercase__    :				Dict=	pt_model(**snake_case__      ).to_tuple()

												lowercase__    :				Dict=	fx_model(**snake_case__      ).to_tuple()
												self.assertEqual(len(snake_case__      )	,  len(snake_case__      )	,  "Output lengths differ between Flax and PyTorch"      )
												for fx_output, pt_output in zip(fx_outputs[:4]	,  pt_outputs[:4]      ):
																		self.assert_almost_equals(snake_case__	,  pt_output.numpy()	,  4e-2      )

												# PT -> Flax
												with tempfile.TemporaryDirectory() as tmpdirname:
																		pt_model.save_pretrained(snake_case__      )
																		lowercase__    :				Tuple=	FlaxVisionTextDualEncoderModel.from_pretrained(snake_case__	,  from_pt=snake_case__      )

												lowercase__    :				str=	fx_model_loaded(**snake_case__      ).to_tuple()
												self.assertEqual(len(snake_case__      )	,  len(snake_case__      )	,  "Output lengths differ between Flax and PyTorch"      )
												for fx_output_loaded, pt_output in zip(fx_outputs_loaded[:4]	,  pt_outputs[:4]      ):
																		self.assert_almost_equals(snake_case__	,  pt_output.numpy()	,  4e-2      )

												# Flax -> PT
												with tempfile.TemporaryDirectory() as tmpdirname:
																		fx_model.save_pretrained(snake_case__      )
																		lowercase__    :				Optional[int]=	VisionTextDualEncoderModel.from_pretrained(snake_case__	,  from_flax=snake_case__      )

												pt_model_loaded.to(snake_case__      )
												pt_model_loaded.eval()

												with torch.no_grad():
																		lowercase__    :				int=	pt_model_loaded(**snake_case__      ).to_tuple()

												self.assertEqual(len(snake_case__      )	,  len(snake_case__      )	,  "Output lengths differ between Flax and PyTorch"      )
												for fx_output, pt_output_loaded in zip(fx_outputs[:4]	,  pt_outputs_loaded[:4]      ):
																		self.assert_almost_equals(snake_case__	,  pt_output_loaded.numpy()	,  4e-2      )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				int=	VisionTextDualEncoderConfig.from_vision_text_configs(snake_case__	,  snake_case__      )

												lowercase__    :				Optional[int]=	VisionTextDualEncoderModel(snake_case__      )
												lowercase__    :				int=	FlaxVisionTextDualEncoderModel(snake_case__      )

												lowercase__    :				str=	convert_pytorch_state_dict_to_flax(pt_model.state_dict()	,  snake_case__      )
												lowercase__    :				str=	fx_state

												self.check_pt_flax_equivalence(snake_case__	,  snake_case__	,  snake_case__      )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				Any=	VisionTextDualEncoderConfig.from_vision_text_configs(snake_case__	,  snake_case__      )

												lowercase__    :				List[str]=	VisionTextDualEncoderModel(snake_case__      )
												lowercase__    :				Optional[int]=	FlaxVisionTextDualEncoderModel(snake_case__      )

												lowercase__    :				Union[str, Any]=	load_flax_weights_in_pytorch_model(snake_case__	,  fx_model.params      )

												self.check_pt_flax_equivalence(snake_case__	,  snake_case__	,  snake_case__      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Optional[Any]=	self.prepare_config_and_inputs()
												self.check_model_from_pretrained_configs(**snake_case__      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Dict=	self.prepare_config_and_inputs()
												self.check_vision_text_dual_encoder_from_pretrained(**snake_case__      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Union[str, Any]=	self.prepare_config_and_inputs()
												self.check_save_load(**snake_case__      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Optional[int]=	self.prepare_config_and_inputs()
												self.check_vision_text_output_attention(**snake_case__      )




						@is_pt_flax_cross_test
						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				int=	self.prepare_config_and_inputs()
												lowercase__    :				Optional[int]=	config_inputs_dict.pop("vision_config"      )
												lowercase__    :				Dict=	config_inputs_dict.pop("text_config"      )

												lowercase__    :				str=	config_inputs_dict

												self.check_equivalence_pt_to_flax(snake_case__	,  snake_case__	,  snake_case__      )
												self.check_equivalence_flax_to_pt(snake_case__	,  snake_case__	,  snake_case__      )




						@slow
						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__,     lowercase__    :				str=	self.get_pretrained_model_and_inputs()

												lowercase__    :				List[Any]=	model_a(**snake_case__      )
												lowercase__    :				Dict=	outputs[0]

												with tempfile.TemporaryDirectory() as tmp_dirname:
																		model_a.save_pretrained(snake_case__      )
																		lowercase__    :				Union[str, Any]=	FlaxVisionTextDualEncoderModel.from_pretrained(snake_case__      )

																		lowercase__    :				Union[str, Any]=	model_a(**snake_case__      )
																		lowercase__    :				Dict=	after_outputs[0]
																		lowercase__    :				List[str]=	np.amax(np.abs(out_a - out_a      )      )
																		self.assertLessEqual(snake_case__	,  1e-5      )


@require_flax
class    __UpperCAmelCase(       SCREAMING_SNAKE_CASE__  ,  unittest.TestCase							):




						"""simple docstring"""




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Union[str, Any]=	FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(
												    "hf-internal-testing/tiny-random-vit"	,  "hf-internal-testing/tiny-bert"	,  vision_from_pt=snake_case__	,  text_from_pt=snake_case__	,  )
												lowercase__    :				Union[str, Any]=	13
												lowercase__    :				Dict=	floats_tensor(
												    [
												        batch_size,
												        model.config.vision_config.num_channels,
												        model.config.vision_config.image_size,
												        model.config.vision_config.image_size,
												    ]      )
												lowercase__    :				Dict=	ids_tensor([batch_size, 4]	,  model.config.text_config.vocab_size      )
												lowercase__    :				List[Any]=	random_attention_mask([batch_size, 4]      )
												lowercase__    :				List[Any]=	{"pixel_values": pixel_values, "input_ids": input_ids, "attention_mask": attention_mask}

												return model, inputs




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				str=	FlaxViTModel(snake_case__      )
												lowercase__    :				Optional[int]=	FlaxBertModel(snake_case__      )
												return vision_model, text_model




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				List[str]=	FlaxViTModelTester(self      )
												lowercase__    :				Tuple=	FlaxBertModelTester(self      )
												lowercase__    :				Tuple=	vit_model_tester.prepare_config_and_inputs()
												lowercase__    :				List[str]=	bert_model_tester.prepare_config_and_inputs()

												lowercase__,     lowercase__    :				Union[str, Any]=	vision_config_and_inputs

												lowercase__,     lowercase__,     lowercase__,     lowercase__    :				List[Any]=	text_config_and_inputs

												# make sure that cross attention layers are added
												return {
												    "text_config": text_config,
												    "vision_config": vision_config,
												    "pixel_values": pixel_values,
												    "attention_mask": attention_mask,
												    "input_ids": input_ids,
												    "token_type_ids": token_type_ids,
												}


@require_torch
class    __UpperCAmelCase(       SCREAMING_SNAKE_CASE__  ,  unittest.TestCase							):




						"""simple docstring"""




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Any=	FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(
												    "hf-internal-testing/tiny-random-clip"	,  "hf-internal-testing/tiny-bert"	,  vision_from_pt=snake_case__	,  text_from_pt=snake_case__	,  )
												lowercase__    :				Dict=	13
												lowercase__    :				int=	floats_tensor(
												    [
												        batch_size,
												        model.config.vision_config.num_channels,
												        model.config.vision_config.image_size,
												        model.config.vision_config.image_size,
												    ]      )
												lowercase__    :				List[Any]=	ids_tensor([batch_size, 4]	,  model.config.text_config.vocab_size      )
												lowercase__    :				List[Any]=	random_attention_mask([batch_size, 4]      )
												lowercase__    :				Optional[Any]=	{"pixel_values": pixel_values, "input_ids": input_ids, "attention_mask": attention_mask}

												return model, inputs




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				Dict=	FlaxCLIPVisionModel(snake_case__      )
												lowercase__    :				Union[str, Any]=	FlaxBertModel(snake_case__      )
												return vision_model, text_model




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Any=	FlaxCLIPVisionModelTester(self      )
												lowercase__    :				Tuple=	FlaxBertModelTester(self      )
												lowercase__    :				int=	clip_model_tester.prepare_config_and_inputs()
												lowercase__    :				str=	bert_model_tester.prepare_config_and_inputs()

												lowercase__,     lowercase__    :				str=	vision_config_and_inputs

												lowercase__,     lowercase__,     lowercase__,     lowercase__    :				List[Any]=	text_config_and_inputs

												# make sure that cross attention layers are added
												return {
												    "text_config": text_config,
												    "vision_config": vision_config,
												    "pixel_values": pixel_values,
												    "attention_mask": attention_mask,
												    "input_ids": input_ids,
												    "token_type_ids": token_type_ids,
												}


@require_flax
@require_vision
class    __UpperCAmelCase(       unittest.TestCase							):




						"""simple docstring"""




						@slow
						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				List[str]=	FlaxVisionTextDualEncoderModel.from_pretrained("clip-italian/clip-italian"	,  logit_scale_init_value=1.0      )
												lowercase__    :				Any=	VisionTextDualEncoderProcessor.from_pretrained("clip-italian/clip-italian"      )

												lowercase__    :				Optional[Any]=	Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"      )
												lowercase__    :				Dict=	processor(
												    text=["una foto di un gatto", "una foto di un cane"]	,  images=snake_case__	,  padding=snake_case__	,  return_tensors="np"      )

												lowercase__    :				List[str]=	model(**snake_case__      )

												# verify the logits
												self.assertEqual(outputs.logits_per_image.shape	,  (inputs.pixel_values.shape[0], inputs.input_ids.shape[0])      )
												self.assertEqual(
												    outputs.logits_per_text.shape	,  (inputs.input_ids.shape[0], inputs.pixel_values.shape[0])	,  )

												lowercase__    :				Dict=	np.array([[1.2_28_47_27, 0.3_10_41_22]]      )

												self.assertTrue(np.allclose(outputs.logits_per_image	,  snake_case__	,  atol=1e-3      )      )














"""simple docstring"""







from __future__ import annotations


class    __UpperCAmelCase:




						"""simple docstring"""




						def __init__(       self	,  snake_case__=None      ):
												'''simple docstring'''
												lowercase__    :				Union[str, Any]=	data
												lowercase__    :				Optional[Any]=	None




						def __repr__(       self      ):
												'''simple docstring'''
												lowercase__    :				str=	[]
												lowercase__    :				Tuple=	self
												while temp:
																		string_rep.append(F'''{temp.data}'''      )
																		lowercase__    :				Optional[int]=	temp.next
												return "->".join(snake_case__      )





def 						lowercase__(A						)    ->Dict:




						"""simple docstring"""



						if not elements_list:
												raise Exception("The Elements List is empty"						)

						lowercase__    :				Optional[int]=	Node(elements_list[0]						)
						for i in range(1 ,		len(A						)						):
												lowercase__    :				Optional[Any]=	Node(elements_list[i]						)
												lowercase__    :				str=	current.next
						return head





def 						lowercase__(A						)    ->None:




						"""simple docstring"""



						if head_node is not None and isinstance(A ,		A						):
												print_reverse(head_node.next						)
												print(head_node.data						)





def 						lowercase__()    ->str:




						"""simple docstring"""



						from doctest import testmod

						testmod()

						lowercase__    :				Optional[int]=	make_linked_list([14, 52, 14, 12, 43]						)
						print("Linked List:"						)
						print(A						)
						print("Elements in Reverse:"						)
						print_reverse(A						)


if __name__ == "__main__":
			main()






