






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__magic_name__:					Optional[int]							=     logging.get_logger(__name__)

__magic_name__:					Optional[Any]							=     {
    "google/realm-cc-news-pretrained-embedder": (
        "https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-encoder": (
        "https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-scorer": (
        "https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-openqa": (
        "https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"
    ),
    "google/realm-orqa-nq-openqa": "https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json",
    "google/realm-orqa-nq-reader": "https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json",
    "google/realm-orqa-wq-openqa": "https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json",
    "google/realm-orqa-wq-reader": "https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json",
    # See all REALM models at https://huggingface.co/models?filter=realm
}





class 	snake_case__ (							_lowerCAmelCase				):
	lowercase__						:					Optional[Any]											=   '''realm'''
	def __init__(    self      ,       lowerCAmelCase__=3_05_22      ,       lowerCAmelCase__=7_68      ,       lowerCAmelCase__=1_28      ,       lowerCAmelCase__=12      ,       lowerCAmelCase__=12      ,       lowerCAmelCase__=8      ,       lowerCAmelCase__=30_72      ,       lowerCAmelCase__="gelu_new"      ,       lowerCAmelCase__=0.1      ,       lowerCAmelCase__=0.1      ,       lowerCAmelCase__=5_12      ,       lowerCAmelCase__=2      ,       lowerCAmelCase__=0.0_2      ,       lowerCAmelCase__=1e-1_2      ,       lowerCAmelCase__=2_56      ,       lowerCAmelCase__=10      ,       lowerCAmelCase__=1e-3      ,       lowerCAmelCase__=5      ,       lowerCAmelCase__=3_20      ,       lowerCAmelCase__=13_35_37_18      ,       lowerCAmelCase__=50_00      ,       lowerCAmelCase__=1      ,       lowerCAmelCase__=0      ,       lowerCAmelCase__=2      ,       **lowerCAmelCase__      ,       )							->				Optional[Any]:
							super().__init__(pad_token_id=lowerCAmelCase__      ,       bos_token_id=lowerCAmelCase__      ,       eos_token_id=lowerCAmelCase__      ,       **lowerCAmelCase__			)

							# Common config
							__magic_name__      :       Optional[int]       						= vocab_size
							__magic_name__      :       List[Any]       						= max_position_embeddings
							__magic_name__      :       List[Any]       						= hidden_size
							__magic_name__      :       Union[str, Any]       						= retriever_proj_size
							__magic_name__      :       str       						= num_hidden_layers
							__magic_name__      :       List[Any]       						= num_attention_heads
							__magic_name__      :       Union[str, Any]       						= num_candidates
							__magic_name__      :       Dict       						= intermediate_size
							__magic_name__      :       Any       						= hidden_act
							__magic_name__      :       Optional[int]       						= hidden_dropout_prob
							__magic_name__      :       Optional[int]       						= attention_probs_dropout_prob
							__magic_name__      :       Dict       						= initializer_range
							__magic_name__      :       List[str]       						= type_vocab_size
							__magic_name__      :       List[Any]       						= layer_norm_eps

							# Reader config
							__magic_name__      :       Tuple       						= span_hidden_size
							__magic_name__      :       Dict       						= max_span_width
							__magic_name__      :       Optional[int]       						= reader_layer_norm_eps
							__magic_name__      :       Optional[int]       						= reader_beam_size
							__magic_name__      :       Union[str, Any]       						= reader_seq_len

							# Retrieval config
							__magic_name__      :       List[Any]       						= num_block_records
							__magic_name__      :       int       						= searcher_beam_size








from manim import *





class 	snake_case__ (							_lowerCAmelCase				):
	def       __magic_name__    (    self			)							->				Dict:
							__magic_name__      :       int       						= Rectangle(height=0.5      ,       width=0.5			)
							__magic_name__      :       Optional[int]       						= Rectangle(height=0.2_5      ,       width=0.2_5			)
							__magic_name__      :       str       						= Rectangle(height=0.4_6      ,       width=0.4_6			).set_stroke(width=0			)

							__magic_name__      :       List[Any]       						= [mem.copy() for i in range(6			)]
							__magic_name__      :       int       						= [mem.copy() for i in range(6			)]
							__magic_name__      :       Tuple       						= VGroup(*lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0			)
							__magic_name__      :       List[str]       						= VGroup(*lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0			)
							__magic_name__      :       str       						= VGroup(lowerCAmelCase__      ,       lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0			)
							__magic_name__      :       Union[str, Any]       						= Text("""CPU"""      ,       font_size=24			)
							__magic_name__      :       Tuple       						= Group(lowerCAmelCase__      ,       lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0.5      ,       aligned_edge=lowerCAmelCase__			)
							cpu.move_to([-2.5, -0.5, 0]			)
							self.add(lowerCAmelCase__			)

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

							__magic_name__      :       Union[str, Any]       						= [mem.copy() for i in range(6			)]
							__magic_name__      :       Union[str, Any]       						= VGroup(*lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0			)

							__magic_name__      :       str       						= Text("""Model"""      ,       font_size=24			)
							__magic_name__      :       Optional[int]       						= Group(lowerCAmelCase__      ,       lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0.5      ,       aligned_edge=lowerCAmelCase__			)
							model.move_to([3, -1.0, 0]			)
							self.add(lowerCAmelCase__			)

							__magic_name__      :       str       						= []
							__magic_name__      :       Tuple       						= []
							__magic_name__      :       Union[str, Any]       						= []

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

													__magic_name__      :       Optional[Any]       						= Rectangle(height=0.4_6 / 4      ,       width=0.4_6 / 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=0.0_2      ,       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__			)

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

							__magic_name__      :       Any       						= Text("""Loaded Checkpoint"""      ,       font_size=24			)
							__magic_name__      :       Optional[int]       						= Group(lowerCAmelCase__      ,       lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0.5      ,       aligned_edge=lowerCAmelCase__			)
							checkpoint.move_to([3, 0.5, 0]			)

							self.add(lowerCAmelCase__			)

							__magic_name__      :       Optional[int]       						= []
							__magic_name__      :       Tuple       						= []

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

													__magic_name__      :       int       						= 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__			)

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

							__magic_name__      :       str       						= 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__			)

							__magic_name__      :       Any       						= 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__			)

							__magic_name__      :       Optional[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=24      ,       )
							step_a.move_to([2, 2, 0]			)

							__magic_name__      :       int       						= [meta_mem.copy() for i in range(6			)]
							__magic_name__      :       Union[str, Any]       						= [meta_mem.copy() for i in range(6			)]
							__magic_name__      :       Any       						= VGroup(*lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0			)
							__magic_name__      :       str       						= VGroup(*lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0			)
							__magic_name__      :       Tuple       						= VGroup(lowerCAmelCase__      ,       lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0			)
							__magic_name__      :       int       						= Text("""Disk"""      ,       font_size=24			)
							__magic_name__      :       Union[str, Any]       						= Group(lowerCAmelCase__      ,       lowerCAmelCase__			).arrange(lowerCAmelCase__      ,       buff=0.5      ,       aligned_edge=lowerCAmelCase__			)
							disk.move_to([-4.0, -1.2_5, 0]			)
							self.play(Write(lowerCAmelCase__      ,       run_time=3			)      ,       Write(lowerCAmelCase__      ,       run_time=1			)      ,       Create(lowerCAmelCase__      ,       run_time=1			)			)

							__magic_name__      :       List[Any]       						= []
							for i, rect in enumerate(lowerCAmelCase__			):
													__magic_name__      :       Dict       						= 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__			)			)

							__magic_name__      :       str       						= 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()
