




"""simple docstring"""





from manim import *



class      a__				(	__magic_name__   ):


			def       a_     (      self      :    str):


						"""simple docstring"""




						__UpperCAmelCase	: List[str]		=					Rectangle(height=0.5      ,  width=0.5)
						__UpperCAmelCase	: List[str]		=					Rectangle(height=0.25      ,  width=0.25)
						__UpperCAmelCase	: Dict		=					Rectangle(height=0.46      ,  width=0.46).set_stroke(width=0)

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

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

						__UpperCAmelCase	: Any		=					[mem.copy() for i in range(6)]
						__UpperCAmelCase	: int		=					VGroup(*UpperCamelCase_).arrange(UpperCamelCase_      ,  buff=0)

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

						__UpperCAmelCase	: str		=					[]
						__UpperCAmelCase	: Tuple		=					[]
						__UpperCAmelCase	: Any		=					[]

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

									__UpperCAmelCase	: Optional[int]		=					Rectangle(height=0.46 / 4      ,  width=0.46 / 3).set_stroke(width=0.0).set_fill(UpperCamelCase_      ,  opacity=0.7)

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

						self.add(*UpperCamelCase_      ,  *UpperCamelCase_      ,  *UpperCamelCase_)

						__UpperCAmelCase	: Optional[int]		=					[mem.copy() for i in range(6)]
						__UpperCAmelCase	: Dict		=					VGroup(*UpperCamelCase_).arrange(UpperCamelCase_      ,  buff=0)

						__UpperCAmelCase	: Tuple		=					Text("Loaded Checkpoint"      ,  font_size=24)
						__UpperCAmelCase	: Any		=					Group(UpperCamelCase_      ,  UpperCamelCase_).arrange(UpperCamelCase_      ,  buff=0.5      ,  aligned_edge=UpperCamelCase_)
						checkpoint.move_to([3, 0.5, 0])

						self.add(UpperCamelCase_)

						__UpperCAmelCase	: Optional[int]		=					[]
						__UpperCAmelCase	: int		=					[]

						for i, rect in enumerate(UpperCamelCase_):
									__UpperCAmelCase	: Optional[Any]		=					fill.copy().set_fill(UpperCamelCase_      ,  opacity=0.7)
									target.move_to(UpperCamelCase_)
									ckpt_arr.append(UpperCamelCase_)

									__UpperCAmelCase	: Optional[Any]		=					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(UpperCamelCase_)
						self.add(*UpperCamelCase_      ,  *UpperCamelCase_)

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

						__UpperCAmelCase	: int		=					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(UpperCamelCase_      ,  UpperCamelCase_)

						__UpperCAmelCase	: Optional[Any]		=					MarkupText(
						    F"<span fgcolor='{BLUE}'>●</span> Checkpoint"      ,  font_size=18      ,  )

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

						__UpperCAmelCase	: Dict		=					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])

						__UpperCAmelCase	: List[Any]		=					[meta_mem.copy() for i in range(6)]
						__UpperCAmelCase	: Optional[int]		=					[meta_mem.copy() for i in range(6)]
						__UpperCAmelCase	: int		=					VGroup(*UpperCamelCase_).arrange(UpperCamelCase_      ,  buff=0)
						__UpperCAmelCase	: Union[str, Any]		=					VGroup(*UpperCamelCase_).arrange(UpperCamelCase_      ,  buff=0)
						__UpperCAmelCase	: Tuple		=					VGroup(UpperCamelCase_      ,  UpperCamelCase_).arrange(UpperCamelCase_      ,  buff=0)
						__UpperCAmelCase	: Optional[int]		=					Text("Disk"      ,  font_size=24)
						__UpperCAmelCase	: str		=					Group(UpperCamelCase_      ,  UpperCamelCase_).arrange(UpperCamelCase_      ,  buff=0.5      ,  aligned_edge=UpperCamelCase_)
						disk.move_to([-4.0, -1.25, 0])
						self.play(Write(UpperCamelCase_      ,  run_time=3)      ,  Write(UpperCamelCase_      ,  run_time=1)      ,  Create(UpperCamelCase_      ,  run_time=1))

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

						self.play(FadeOut(UpperCamelCase_))

						__UpperCAmelCase	: Union[str, Any]		=					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(UpperCamelCase_      ,  run_time=3))

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

						self.wait()








"""simple docstring"""





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


A   =       logging.get_logger(__name__)

A   =       {
    """bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",
}



class      a__				(	__magic_name__   ):
			lowercase_    =	"gpt_bigcode"
			lowercase_    =	["past_key_values"]
			lowercase_    =	{
			    "hidden_size": "n_embd",
			    "max_position_embeddings": "n_positions",
			    "num_attention_heads": "n_head",
			    "num_hidden_layers": "n_layer",
			}


			def __init__(      self      :    Any      ,  UpperCamelCase_      :    Tuple=50257      ,  UpperCamelCase_      :    Dict=1024      ,  UpperCamelCase_      :    Optional[Any]=768      ,  UpperCamelCase_      :    Optional[Any]=12      ,  UpperCamelCase_      :    Any=12      ,  UpperCamelCase_      :    Optional[int]=None      ,  UpperCamelCase_      :    List[Any]="gelu_pytorch_tanh"      ,  UpperCamelCase_      :    Optional[Any]=0.1      ,  UpperCamelCase_      :    Union[str, Any]=0.1      ,  UpperCamelCase_      :    Tuple=0.1      ,  UpperCamelCase_      :    Tuple=1e-5      ,  UpperCamelCase_      :    List[str]=0.02      ,  UpperCamelCase_      :    Dict=True      ,  UpperCamelCase_      :    Optional[int]=True      ,  UpperCamelCase_      :    str=50256      ,  UpperCamelCase_      :    Union[str, Any]=50256      ,  UpperCamelCase_      :    Dict=True      ,  UpperCamelCase_      :    List[str]=True      ,  UpperCamelCase_      :    Union[str, Any]=True      ,  **UpperCamelCase_      :    Union[str, Any]      ,  ):


						"""simple docstring"""




						__UpperCAmelCase	: Tuple		=					vocab_size
						__UpperCAmelCase	: Optional[int]		=					n_positions
						__UpperCAmelCase	: Tuple		=					n_embd
						__UpperCAmelCase	: str		=					n_layer
						__UpperCAmelCase	: Dict		=					n_head
						__UpperCAmelCase	: Optional[Any]		=					n_inner
						__UpperCAmelCase	: Optional[Any]		=					activation_function
						__UpperCAmelCase	: List[str]		=					resid_pdrop
						__UpperCAmelCase	: List[Any]		=					embd_pdrop
						__UpperCAmelCase	: Optional[Any]		=					attn_pdrop
						__UpperCAmelCase	: Dict		=					layer_norm_epsilon
						__UpperCAmelCase	: List[str]		=					initializer_range
						__UpperCAmelCase	: int		=					scale_attn_weights
						__UpperCAmelCase	: Tuple		=					use_cache
						__UpperCAmelCase	: List[Any]		=					attention_softmax_in_fpaa
						__UpperCAmelCase	: Any		=					scale_attention_softmax_in_fpaa
						__UpperCAmelCase	: str		=					multi_query

						__UpperCAmelCase	: int		=					bos_token_id
						__UpperCAmelCase	: str		=					eos_token_id

						super().__init__(bos_token_id=UpperCamelCase_      ,  eos_token_id=UpperCamelCase_      ,  **UpperCamelCase_)


