"""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      UpperCAmelCase__			(							lowerCAmelCase__	:Optional[Any]						)					->       str:
      '''simple docstring'''


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





@require_flax
class 					_A		:

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            pass

      def 							A__			(		self		):







            """simple docstring"""



            pass

      def 							A__			(		self		):







            """simple docstring"""



            pass

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      np.abs((a - b)		).max()
            self.assertLessEqual(__lowerCAmelCase						,			__lowerCAmelCase						,			f'Difference between torch and flax is {diff} (>= {tol}).'		)

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase=None						,			**__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      VisionTextDualEncoderConfig.from_vision_text_configs(__lowerCAmelCase						,			__lowerCAmelCase		)

            lowercase								=      FlaxVisionTextDualEncoderModel(__lowerCAmelCase		)

            lowercase								=      model(input_ids=__lowerCAmelCase						,			pixel_values=__lowerCAmelCase						,			attention_mask=__lowerCAmelCase		)

            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 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase=None						,			**__lowerCAmelCase		):







            """simple docstring"""



            lowercase				,				lowercase								=      self.get_vision_text_model(__lowerCAmelCase						,			__lowerCAmelCase		)
            lowercase								=      {"""vision_model""": vision_model, """text_model""": text_model}
            lowercase								=      FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(**__lowerCAmelCase		)

            lowercase								=      model(input_ids=__lowerCAmelCase						,			pixel_values=__lowerCAmelCase						,			attention_mask=__lowerCAmelCase		)

            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 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase=None						,			**__lowerCAmelCase		):







            """simple docstring"""



            lowercase				,				lowercase								=      self.get_vision_text_model(__lowerCAmelCase						,			__lowerCAmelCase		)
            lowercase								=      {"""vision_model""": vision_model, """text_model""": text_model}
            lowercase								=      FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(**__lowerCAmelCase		)

            lowercase								=      model(input_ids=__lowerCAmelCase						,			pixel_values=__lowerCAmelCase						,			attention_mask=__lowerCAmelCase		)
            lowercase								=      output[0]

            with tempfile.TemporaryDirectory() as tmpdirname:
                  model.save_pretrained(__lowerCAmelCase		)
                  lowercase								=      FlaxVisionTextDualEncoderModel.from_pretrained(__lowerCAmelCase		)

                  lowercase								=      model(input_ids=__lowerCAmelCase						,			pixel_values=__lowerCAmelCase						,			attention_mask=__lowerCAmelCase		)
                  lowercase								=      after_output[0]
                  lowercase								=      np.amax(np.abs(out_a - out_a		)		)
                  self.assertLessEqual(__lowerCAmelCase						,			1E-3		)

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase=None						,			**__lowerCAmelCase		):







            """simple docstring"""



            lowercase				,				lowercase								=      self.get_vision_text_model(__lowerCAmelCase						,			__lowerCAmelCase		)
            lowercase								=      {"""vision_model""": vision_model, """text_model""": text_model}
            lowercase								=      FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(**__lowerCAmelCase		)

            lowercase								=      model(
                input_ids=__lowerCAmelCase						,			pixel_values=__lowerCAmelCase						,			attention_mask=__lowerCAmelCase						,			output_attentions=__lowerCAmelCase		)

            lowercase								=      output.vision_model_output.attentions
            self.assertEqual(len(__lowerCAmelCase		)						,			vision_config.num_hidden_layers		)

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

            lowercase								=      output.text_model_output.attentions
            self.assertEqual(len(__lowerCAmelCase		)						,			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 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            pt_model.to(__lowerCAmelCase		)
            pt_model.eval()

            # prepare inputs
            lowercase								=      inputs_dict
            lowercase								=      {k: torch.tensor(v.tolist()		) for k, v in flax_inputs.items()}

            with torch.no_grad():
                  lowercase								=      pt_model(**__lowerCAmelCase		).to_tuple()

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

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

            lowercase								=      fx_model_loaded(**__lowerCAmelCase		).to_tuple()
            self.assertEqual(len(__lowerCAmelCase		)						,			len(__lowerCAmelCase		)						,			"""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(__lowerCAmelCase						,			pt_output.numpy()						,			4E-2		)

            # Flax -> PT
            with tempfile.TemporaryDirectory() as tmpdirname:
                  fx_model.save_pretrained(__lowerCAmelCase		)
                  lowercase								=      VisionTextDualEncoderModel.from_pretrained(__lowerCAmelCase						,			from_flax=__lowerCAmelCase		)

            pt_model_loaded.to(__lowerCAmelCase		)
            pt_model_loaded.eval()

            with torch.no_grad():
                  lowercase								=      pt_model_loaded(**__lowerCAmelCase		).to_tuple()

            self.assertEqual(len(__lowerCAmelCase		)						,			len(__lowerCAmelCase		)						,			"""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(__lowerCAmelCase						,			pt_output_loaded.numpy()						,			4E-2		)

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      VisionTextDualEncoderConfig.from_vision_text_configs(__lowerCAmelCase						,			__lowerCAmelCase		)

            lowercase								=      VisionTextDualEncoderModel(__lowerCAmelCase		)
            lowercase								=      FlaxVisionTextDualEncoderModel(__lowerCAmelCase		)

            lowercase								=      convert_pytorch_state_dict_to_flax(pt_model.state_dict()						,			__lowerCAmelCase		)
            lowercase								=      fx_state

            self.check_pt_flax_equivalence(__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      VisionTextDualEncoderConfig.from_vision_text_configs(__lowerCAmelCase						,			__lowerCAmelCase		)

            lowercase								=      VisionTextDualEncoderModel(__lowerCAmelCase		)
            lowercase								=      FlaxVisionTextDualEncoderModel(__lowerCAmelCase		)

            lowercase								=      load_flax_weights_in_pytorch_model(__lowerCAmelCase						,			fx_model.params		)

            self.check_pt_flax_equivalence(__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      self.prepare_config_and_inputs()
            self.check_model_from_pretrained_configs(**__lowerCAmelCase		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      self.prepare_config_and_inputs()
            self.check_vision_text_dual_encoder_from_pretrained(**__lowerCAmelCase		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      self.prepare_config_and_inputs()
            self.check_save_load(**__lowerCAmelCase		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      self.prepare_config_and_inputs()
            self.check_vision_text_output_attention(**__lowerCAmelCase		)

      @is_pt_flax_cross_test
      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      self.prepare_config_and_inputs()
            lowercase								=      config_inputs_dict.pop("""vision_config"""		)
            lowercase								=      config_inputs_dict.pop("""text_config"""		)

            lowercase								=      config_inputs_dict

            self.check_equivalence_pt_to_flax(__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		)
            self.check_equivalence_flax_to_pt(__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		)







      @slow
      def 							A__			(		self		):







            """simple docstring"""



            lowercase				,				lowercase								=      self.get_pretrained_model_and_inputs()

            lowercase								=      model_a(**__lowerCAmelCase		)
            lowercase								=      outputs[0]

            with tempfile.TemporaryDirectory() as tmp_dirname:
                  model_a.save_pretrained(__lowerCAmelCase		)
                  lowercase								=      FlaxVisionTextDualEncoderModel.from_pretrained(__lowerCAmelCase		)

                  lowercase								=      model_a(**__lowerCAmelCase		)
                  lowercase								=      after_outputs[0]
                  lowercase								=      np.amax(np.abs(out_a - out_a		)		)
                  self.assertLessEqual(__lowerCAmelCase						,			1E-5		)






@require_flax
class 					_A		(			lowerCAmelCase    ,       unittest.TestCase      ):

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(
                """hf-internal-testing/tiny-random-vit"""						,			"""hf-internal-testing/tiny-bert"""						,			vision_from_pt=__lowerCAmelCase						,			text_from_pt=__lowerCAmelCase						,			)
            lowercase								=      13
            lowercase								=      floats_tensor(
                [
                    batch_size,
                    model.config.vision_config.num_channels,
                    model.config.vision_config.image_size,
                    model.config.vision_config.image_size,
                ]		)
            lowercase								=      ids_tensor([batch_size, 4]						,			model.config.text_config.vocab_size		)
            lowercase								=      random_attention_mask([batch_size, 4]		)
            lowercase								=      {"""pixel_values""": pixel_values, """input_ids""": input_ids, """attention_mask""": attention_mask}

            return model, inputs

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      FlaxViTModel(__lowerCAmelCase		)
            lowercase								=      FlaxBertModel(__lowerCAmelCase		)
            return vision_model, text_model







      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      FlaxViTModelTester(self		)
            lowercase								=      FlaxBertModelTester(self		)
            lowercase								=      vit_model_tester.prepare_config_and_inputs()
            lowercase								=      bert_model_tester.prepare_config_and_inputs()

            lowercase				,				lowercase								=      vision_config_and_inputs

            lowercase				,				lowercase				,				lowercase				,				lowercase								=      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 					_A		(			lowerCAmelCase    ,       unittest.TestCase      ):

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      FlaxVisionTextDualEncoderModel.from_vision_text_pretrained(
                """hf-internal-testing/tiny-random-clip"""						,			"""hf-internal-testing/tiny-bert"""						,			vision_from_pt=__lowerCAmelCase						,			text_from_pt=__lowerCAmelCase						,			)
            lowercase								=      13
            lowercase								=      floats_tensor(
                [
                    batch_size,
                    model.config.vision_config.num_channels,
                    model.config.vision_config.image_size,
                    model.config.vision_config.image_size,
                ]		)
            lowercase								=      ids_tensor([batch_size, 4]						,			model.config.text_config.vocab_size		)
            lowercase								=      random_attention_mask([batch_size, 4]		)
            lowercase								=      {"""pixel_values""": pixel_values, """input_ids""": input_ids, """attention_mask""": attention_mask}

            return model, inputs

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      FlaxCLIPVisionModel(__lowerCAmelCase		)
            lowercase								=      FlaxBertModel(__lowerCAmelCase		)
            return vision_model, text_model







      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      FlaxCLIPVisionModelTester(self		)
            lowercase								=      FlaxBertModelTester(self		)
            lowercase								=      clip_model_tester.prepare_config_and_inputs()
            lowercase								=      bert_model_tester.prepare_config_and_inputs()

            lowercase				,				lowercase								=      vision_config_and_inputs

            lowercase				,				lowercase				,				lowercase				,				lowercase								=      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 					_A		(			unittest.TestCase      ):

      @slow
      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      FlaxVisionTextDualEncoderModel.from_pretrained("""clip-italian/clip-italian"""						,			logit_scale_init_value=1.0		)
            lowercase								=      VisionTextDualEncoderProcessor.from_pretrained("""clip-italian/clip-italian"""		)

            lowercase								=      Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""		)
            lowercase								=      processor(
                text=["""una foto di un gatto""", """una foto di un cane"""]						,			images=__lowerCAmelCase						,			padding=__lowerCAmelCase						,			return_tensors="""np"""		)

            lowercase								=      model(**__lowerCAmelCase		)

            # 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								=      np.array([[1.2_2_8_4_7_2_7, 0.3_1_0_4_1_2_2]]		)

            self.assertTrue(np.allclose(outputs.logits_per_image						,			__lowerCAmelCase						,			atol=1E-3		)		)




"""simple docstring"""






from __future__ import annotations


def      UpperCAmelCase__			(							lowerCAmelCase__	:dict   ,						lowerCAmelCase__	:str						)					->       set[str]:
      '''simple docstring'''


      lowercase				,				lowercase								=      set(lowerCAmelCase__						), [start]

      while stack:
            lowercase								=      stack.pop()
            explored.add(lowerCAmelCase__						)
            # Differences from BFS:
            # 1) pop last element instead of first one
            # 2) add adjacent elements to stack without exploring them
            for adj in reversed(graph[v]						):
                  if adj not in explored:
                        stack.append(lowerCAmelCase__						)
      return explored


__lowerCAmelCase       :			str   	={
    """A""": ["""B""", """C""", """D"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B""", """D"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E""", """G"""],
    """G""": ["""F"""],
}

if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(depth_first_search(G, """A"""))



