

from manim import *







class 			lowercase    (	lowercase_      ):




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

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

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

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

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

											snake_case_          =   []
											snake_case_          =   []
											snake_case_          =   []

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

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

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

											self.add(*snake_case				,       *snake_case				,       *snake_case	)

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

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

											self.add(snake_case	)

											snake_case_          =   []
											snake_case_          =   []

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

																		snake_case_          =   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(snake_case	)
											self.add(*snake_case				,       *snake_case	)

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

											snake_case_          =   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(snake_case				,       snake_case	)

											snake_case_          =   MarkupText(
											    F'''<span fgcolor=\'{BLUE}\'>●</span> Checkpoint'''				,       font_size=18				,       )

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

											snake_case_          =   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]	)

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

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

											self.play(FadeOut(snake_case	)	)

											snake_case_          =   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(snake_case				,       run_time=3	)	)

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

											self.wait()







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_UpperCAmelCase		:       int						    =	logging.get_logger(__name__)

_UpperCAmelCase		:       Optional[Any]						    =	{
    """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json""",
    """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json""",
    """junnyu/roformer_chinese_char_small""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json"""
    ),
    """junnyu/roformer_chinese_char_base""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_discriminator""": (
        """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_generator""": (
        """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json"""
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}







class 			lowercase    (	lowercase_      ):
				__SCREAMING_SNAKE_CASE :			List[Any]	      =      '''roformer'''




				def __init__( self				,       snake_case=5_0000				,       snake_case=None				,       snake_case=768				,       snake_case=12				,       snake_case=12				,       snake_case=3072				,       snake_case="gelu"				,       snake_case=0.1				,       snake_case=0.1				,       snake_case=1536				,       snake_case=2				,       snake_case=0.02				,       snake_case=1e-1_2				,       snake_case=0				,       snake_case=False				,       snake_case=True				,       **snake_case				,       ):
											super().__init__(pad_token_id=snake_case				,       **snake_case	)

											snake_case_          =   vocab_size
											snake_case_          =   hidden_size if embedding_size is None else embedding_size
											snake_case_          =   hidden_size
											snake_case_          =   num_hidden_layers
											snake_case_          =   num_attention_heads
											snake_case_          =   hidden_act
											snake_case_          =   intermediate_size
											snake_case_          =   hidden_dropout_prob
											snake_case_          =   attention_probs_dropout_prob
											snake_case_          =   max_position_embeddings
											snake_case_          =   type_vocab_size
											snake_case_          =   initializer_range
											snake_case_          =   layer_norm_eps
											snake_case_          =   rotary_value
											snake_case_          =   use_cache







class 			lowercase    (	lowercase_      ):




				@property
				def    a							( self	):
											if self.task == "multiple-choice":
																		snake_case_          =   {0: 'batch', 1: 'choice', 2: 'sequence'}
											else:
																		snake_case_          =   {0: 'batch', 1: 'sequence'}
											snake_case_          =   {0: 'batch', 1: 'sequence'}
											return OrderedDict(
											    [
											        ('input_ids', dynamic_axis),
											        ('attention_mask', dynamic_axis),
											        ('token_type_ids', dynamic_axis),
											    ]	)




