

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase			:				List[Any]   =     {
    "configuration_rembert": ["REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RemBertConfig", "RemBertOnnxConfig"]
}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase			:				int   =     ["RemBertTokenizer"]

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase			:				str   =     ["RemBertTokenizerFast"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase			:				Dict   =     [
		    "REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "RemBertForCausalLM",
		    "RemBertForMaskedLM",
		    "RemBertForMultipleChoice",
		    "RemBertForQuestionAnswering",
		    "RemBertForSequenceClassification",
		    "RemBertForTokenClassification",
		    "RemBertLayer",
		    "RemBertModel",
		    "RemBertPreTrainedModel",
		    "load_tf_weights_in_rembert",
		]


try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase			:				str   =     [
		    "TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "TFRemBertForCausalLM",
		    "TFRemBertForMaskedLM",
		    "TFRemBertForMultipleChoice",
		    "TFRemBertForQuestionAnswering",
		    "TFRemBertForSequenceClassification",
		    "TFRemBertForTokenClassification",
		    "TFRemBertLayer",
		    "TFRemBertModel",
		    "TFRemBertPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_rembert import REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RemBertConfig, RemBertOnnxConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_rembert import RemBertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_rembert_fast import RemBertTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_rembert import (
				    REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RemBertForCausalLM,
				    RemBertForMaskedLM,
				    RemBertForMultipleChoice,
				    RemBertForQuestionAnswering,
				    RemBertForSequenceClassification,
				    RemBertForTokenClassification,
				    RemBertLayer,
				    RemBertModel,
				    RemBertPreTrainedModel,
				    load_tf_weights_in_rembert,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_rembert import (
				    TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFRemBertForCausalLM,
				    TFRemBertForMaskedLM,
				    TFRemBertForMultipleChoice,
				    TFRemBertForQuestionAnswering,
				    TFRemBertForSequenceClassification,
				    TFRemBertForTokenClassification,
				    TFRemBertLayer,
				    TFRemBertModel,
				    TFRemBertPreTrainedModel,
				)


else:
		import sys

		lowercase			:				Dict   =     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)











"""simple docstring"""




from manim import *






class       UpperCAmelCase_    (							_UpperCamelCase		):



      def 		snake_case_   (	self	:      Tuple		):
           _UpperCAmelCase     :      str														=       Rectangle(height=0.5	,      width=0.5		)
           _UpperCAmelCase     :      List[Any]														=       Rectangle(height=0.25	,      width=0.25		)
           _UpperCAmelCase     :      Tuple														=       Rectangle(height=0.46	,      width=0.46		).set_stroke(width=0		)

           _UpperCAmelCase     :      List[Any]														=       [mem.copy() for i in range(6		)]
           _UpperCAmelCase     :      List[str]														=       [mem.copy() for i in range(6		)]
           _UpperCAmelCase     :      int														=       VGroup(*A		).arrange(A	,      buff=0		)
           _UpperCAmelCase     :      Dict														=       VGroup(*A		).arrange(A	,      buff=0		)
           _UpperCAmelCase     :      int														=       VGroup(A	,      A		).arrange(A	,      buff=0		)
           _UpperCAmelCase     :      str														=       Text("CPU"	,      font_size=2_4		)
           _UpperCAmelCase     :      Union[str, Any]														=       Group(A	,      A		).arrange(A	,      buff=0.5	,      aligned_edge=A		)
           cpu.move_to([-2.5, -0.5, 0]		)
           self.add(A		)

           _UpperCAmelCase     :      Union[str, Any]														=       [mem.copy() for i in range(4		)]
           _UpperCAmelCase     :      Optional[int]														=       VGroup(*A		).arrange(A	,      buff=0		)
           _UpperCAmelCase     :      Any														=       Text("GPU"	,      font_size=2_4		)
           _UpperCAmelCase     :      Dict														=       Group(A	,      A		).arrange(A	,      buff=0.5	,      aligned_edge=A		)
           gpu.move_to([-1, -1, 0]		)
           self.add(A		)

           _UpperCAmelCase     :      Tuple														=       [mem.copy() for i in range(6		)]
           _UpperCAmelCase     :      str														=       VGroup(*A		).arrange(A	,      buff=0		)

           _UpperCAmelCase     :      Any														=       Text("Model"	,      font_size=2_4		)
           _UpperCAmelCase     :      Any														=       Group(A	,      A		).arrange(A	,      buff=0.5	,      aligned_edge=A		)
           model.move_to([3, -1.0, 0]		)
           self.add(A		)

           _UpperCAmelCase     :      List[str]														=       []
           _UpperCAmelCase     :      Optional[int]														=       []
           _UpperCAmelCase     :      str														=       []

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

                _UpperCAmelCase     :      Dict														=       Rectangle(height=0.46 / 4	,      width=0.46 / 3		).set_stroke(width=0.0		).set_fill(A	,      opacity=0.7		)

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

           self.add(*A	,      *A	,      *A		)

           _UpperCAmelCase     :      Dict														=       [mem.copy() for i in range(6		)]
           _UpperCAmelCase     :      List[str]														=       VGroup(*A		).arrange(A	,      buff=0		)

           _UpperCAmelCase     :      List[str]														=       Text("Loaded Checkpoint"	,      font_size=2_4		)
           _UpperCAmelCase     :      Optional[int]														=       Group(A	,      A		).arrange(A	,      buff=0.5	,      aligned_edge=A		)
           checkpoint.move_to([3, 0.5, 0]		)

           self.add(A		)

           _UpperCAmelCase     :      Union[str, Any]														=       []
           _UpperCAmelCase     :      Union[str, Any]														=       []

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

                _UpperCAmelCase     :      Dict														=       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(A		)
           self.add(*A	,      *A		)

           _UpperCAmelCase     :      List[str]														=       Square(side_length=2.2		)
           key.move_to([-5, 2, 0]		)

           _UpperCAmelCase     :      List[Any]														=       MarkupText(
               f'<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model'	,      font_size=1_8	,      )

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

           self.add(A	,      A		)

           _UpperCAmelCase     :      Tuple														=       MarkupText(
               f'<span fgcolor=\'{BLUE}\'>●</span> Checkpoint'	,      font_size=1_8	,      )

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

           _UpperCAmelCase     :      Any														=       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=2_4	,      )
           step_a.move_to([2, 2, 0]		)

           _UpperCAmelCase     :      int														=       [meta_mem.copy() for i in range(6		)]
           _UpperCAmelCase     :      Optional[int]														=       [meta_mem.copy() for i in range(6		)]
           _UpperCAmelCase     :      List[str]														=       VGroup(*A		).arrange(A	,      buff=0		)
           _UpperCAmelCase     :      Optional[int]														=       VGroup(*A		).arrange(A	,      buff=0		)
           _UpperCAmelCase     :      List[Any]														=       VGroup(A	,      A		).arrange(A	,      buff=0		)
           _UpperCAmelCase     :      Union[str, Any]														=       Text("Disk"	,      font_size=2_4		)
           _UpperCAmelCase     :      int														=       Group(A	,      A		).arrange(A	,      buff=0.5	,      aligned_edge=A		)
           disk.move_to([-4.0, -1.25, 0]		)
           self.play(Write(A	,      run_time=3		)	,      Write(A	,      run_time=1		)	,      Create(A	,      run_time=1		)		)

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

           self.play(FadeOut(A		)		)

           _UpperCAmelCase     :      int														=       MarkupText(f'Then, the checkpoint is removed from memory\nthrough garbage collection.'	,      font_size=2_4		)
           step_a.move_to([2, 2, 0]		)

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

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

           self.wait()
