from manim import *





class      lowerCAmelCase						(					_a			):



     def 			a__  (					self       ):
            _A=	Rectangle(height=0.5				,      width=0.5       )
            _A=	Rectangle(height=0.25				,      width=0.25       )
            _A=	Rectangle(height=0.46				,      width=0.46       ).set_stroke(width=0       )

            _A=	[mem.copy() for i in range(6       )]
            _A=	[mem.copy() for i in range(6       )]
            _A=	VGroup(*lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )
            _A=	VGroup(*lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )
            _A=	VGroup(lowerCAmelCase__				,      lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )
            _A=	Text('CPU'				,      font_size=24       )
            _A=	Group(lowerCAmelCase__				,      lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0.5				,      aligned_edge=lowerCAmelCase__       )
            cpu.move_to([-2.5, -0.5, 0]       )
            self.add(lowerCAmelCase__       )

            _A=	[mem.copy() for i in range(4       )]
            _A=	VGroup(*lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )
            _A=	Text('GPU'				,      font_size=24       )
            _A=	Group(lowerCAmelCase__				,      lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0.5				,      aligned_edge=lowerCAmelCase__       )
            gpu.move_to([-1, -1, 0]       )
            self.add(lowerCAmelCase__       )

            _A=	[mem.copy() for i in range(6       )]
            _A=	VGroup(*lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )

            _A=	Text('Model'				,      font_size=24       )
            _A=	Group(lowerCAmelCase__				,      lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0.5				,      aligned_edge=lowerCAmelCase__       )
            model.move_to([3, -1.0, 0]       )
            self.add(lowerCAmelCase__       )

            _A=	[]
            _A=	[]
            _A=	[]

            for i, rect in enumerate(lowerCAmelCase__       ):
                   rect.set_stroke(lowerCAmelCase__       )

                   _A=	Rectangle(height=0.46 / 4				,      width=0.46 / 3       ).set_stroke(width=0.0       ).set_fill(lowerCAmelCase__				,      opacity=0.7       )

                   if i == 0:
                          cpu_target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT       )				,      buff=0.02				,      direction=lowerCAmelCase__       )
                          cpu_target.set_x(cpu_target.get_x() + 0.1       )
                   elif i == 3:
                          cpu_target.next_to(model_cpu_arr[0]				,      direction=lowerCAmelCase__				,      buff=0.0       )
                   else:
                          cpu_target.next_to(model_cpu_arr[i - 1]				,      direction=lowerCAmelCase__				,      buff=0.0       )
                   self.add(lowerCAmelCase__       )
                   model_cpu_arr.append(lowerCAmelCase__       )

            self.add(*lowerCAmelCase__				,      *lowerCAmelCase__				,      *lowerCAmelCase__       )

            _A=	[mem.copy() for i in range(6       )]
            _A=	VGroup(*lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )

            _A=	Text('Loaded Checkpoint'				,      font_size=24       )
            _A=	Group(lowerCAmelCase__				,      lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0.5				,      aligned_edge=lowerCAmelCase__       )
            checkpoint.move_to([3, 0.5, 0]       )

            self.add(lowerCAmelCase__       )

            _A=	[]
            _A=	[]

            for i, rect in enumerate(lowerCAmelCase__       ):
                   _A=	fill.copy().set_fill(lowerCAmelCase__				,      opacity=0.7       )
                   target.move_to(lowerCAmelCase__       )
                   ckpt_arr.append(lowerCAmelCase__       )

                   _A=	target.copy()
                   if i < 5:
                          cpu_target.move_to(cpu_left_col_base[i + 1]       )
                   else:
                          cpu_target.move_to(cpu_right_col_base[i - 5]       )
                   ckpt_cpu_arr.append(lowerCAmelCase__       )
            self.add(*lowerCAmelCase__				,      *lowerCAmelCase__       )

            _A=	Square(side_length=2.2       )
            key.move_to([-5, 2, 0]       )

            _A=	MarkupText(
                f"<b>Key:</b>\n\n<span fgcolor='{YELLOW}'>●</span> Empty Model"				,      font_size=18				,      )

            key_text.move_to([-5, 2.4, 0]       )

            self.add(lowerCAmelCase__				,      lowerCAmelCase__       )

            _A=	MarkupText(
                f"<span fgcolor='{BLUE}'>●</span> Checkpoint"				,      font_size=18				,      )

            blue_text.next_to(lowerCAmelCase__				,      DOWN * 2.4				,      aligned_edge=key_text.get_left()       )
            self.add(lowerCAmelCase__       )

            _A=	MarkupText(
                f"Based on the passed in configuration, weights are stored in\na variety of np.memmaps on disk or to a particular device."				,      font_size=24				,      )
            step_a.move_to([2, 2, 0]       )

            _A=	[meta_mem.copy() for i in range(6       )]
            _A=	[meta_mem.copy() for i in range(6       )]
            _A=	VGroup(*lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )
            _A=	VGroup(*lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )
            _A=	VGroup(lowerCAmelCase__				,      lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0       )
            _A=	Text('Disk'				,      font_size=24       )
            _A=	Group(lowerCAmelCase__				,      lowerCAmelCase__       ).arrange(lowerCAmelCase__				,      buff=0.5				,      aligned_edge=lowerCAmelCase__       )
            disk.move_to([-4.0, -1.25, 0]       )
            self.play(Write(lowerCAmelCase__				,      run_time=3       )				,      Write(lowerCAmelCase__				,      run_time=1       )				,      Create(lowerCAmelCase__				,      run_time=1       )       )

            _A=	[]
            for i, rect in enumerate(lowerCAmelCase__       ):
                   _A=	rect.copy()
                   target.generate_target()
                   target.target.move_to(disk_left_col_base[i]       ).scale(0.5       )
                   animations.append(MoveToTarget(lowerCAmelCase__				,      run_time=1.5       )       )
            self.play(*lowerCAmelCase__       )

            self.play(FadeOut(lowerCAmelCase__       )       )

            _A=	MarkupText(f"Then, the checkpoint is removed from memory\nthrough garbage collection."				,      font_size=24       )
            step_a.move_to([2, 2, 0]       )

            self.play(Write(lowerCAmelCase__				,      run_time=3       )       )

            self.play(
                FadeOut(lowerCAmelCase__				,      lowerCAmelCase__				,      *lowerCAmelCase__				,      *lowerCAmelCase__       )				,      )

            self.wait()
import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
      import jax

      from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
      from transformers.models.bert.modeling_flax_bert import FlaxBertModel
      from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel





@require_flax
class      lowerCAmelCase						(					unittest.TestCase			):



     @slow
     def 			a__  (					self       ):
            for model_name in ["bert-base-cased", "bert-large-uncased"]:
                   with self.subTest(lowerCAmelCase__       ):
                          _A=	AutoConfig.from_pretrained(lowerCAmelCase__       )
                          self.assertIsNotNone(lowerCAmelCase__       )
                          self.assertIsInstance(lowerCAmelCase__				,      lowerCAmelCase__       )

                          _A=	FlaxAutoModel.from_pretrained(lowerCAmelCase__       )
                          self.assertIsNotNone(lowerCAmelCase__       )
                          self.assertIsInstance(lowerCAmelCase__				,      lowerCAmelCase__       )



     @slow
     def 			a__  (					self       ):
            for model_name in ["roberta-base", "roberta-large"]:
                   with self.subTest(lowerCAmelCase__       ):
                          _A=	AutoConfig.from_pretrained(lowerCAmelCase__       )
                          self.assertIsNotNone(lowerCAmelCase__       )
                          self.assertIsInstance(lowerCAmelCase__				,      lowerCAmelCase__       )

                          _A=	FlaxAutoModel.from_pretrained(lowerCAmelCase__       )
                          self.assertIsNotNone(lowerCAmelCase__       )
                          self.assertIsInstance(lowerCAmelCase__				,      lowerCAmelCase__       )



     @slow
     def 			a__  (					self       ):
            for model_name in ["bert-base-cased", "bert-large-uncased"]:
                   _A=	AutoTokenizer.from_pretrained(lowerCAmelCase__       )
                   _A=	FlaxBertModel.from_pretrained(lowerCAmelCase__       )
                   _A=	tokenizer('Do you support jax jitted function?'				,      return_tensors=TensorType.JAX       )

                   @jax.jit
                   def eval(**lowerCAmelCase__       ):
                          return model(**lowerCAmelCase__       )

                   eval(**lowerCAmelCase__       ).block_until_ready()



     @slow
     def 			a__  (					self       ):
            for model_name in ["roberta-base", "roberta-large"]:
                   _A=	AutoTokenizer.from_pretrained(lowerCAmelCase__       )
                   _A=	FlaxRobertaModel.from_pretrained(lowerCAmelCase__       )
                   _A=	tokenizer('Do you support jax jitted function?'				,      return_tensors=TensorType.JAX       )

                   @jax.jit
                   def eval(**lowerCAmelCase__       ):
                          return model(**lowerCAmelCase__       )

                   eval(**lowerCAmelCase__       ).block_until_ready()



     def 			a__  (					self       ):
            with self.assertRaisesRegex(
                lowerCAmelCase__				,      'bert-base is not a local folder and is not a valid model identifier'       ):
                   _A=	FlaxAutoModel.from_pretrained('bert-base'       )



     def 			a__  (					self       ):
            with self.assertRaisesRegex(
                lowerCAmelCase__				,      r'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'       ):
                   _A=	FlaxAutoModel.from_pretrained(lowerCAmelCase__				,      revision='aaaaaa'       )



     def 			a__  (					self       ):
            with self.assertRaisesRegex(
                lowerCAmelCase__				,      'hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'				,      ):
                   _A=	FlaxAutoModel.from_pretrained('hf-internal-testing/config-no-model'       )





     def 			a__  (					self       ):
            with self.assertRaisesRegex(lowerCAmelCase__				,      'Use `from_pt=True` to load this model'       ):
                   _A=	FlaxAutoModel.from_pretrained('hf-internal-testing/tiny-bert-pt-only'       )