

"""simple docstring"""

from manim import *


class       _snake_case  (    UpperCamelCase							):







						def 							_UpperCamelCase     (self				)      ->    str:
											__lowercase        =      Rectangle(height=0.5  ,				width=0.5				)
											__lowercase        =      Rectangle(height=0.4_6  ,				width=0.4_6				).set_stroke(width=0				)
											__lowercase        =      Rectangle(height=0.2_5  ,				width=0.2_5				)

											__lowercase        =      [mem.copy() for i in range(6				)]
											__lowercase        =      [mem.copy() for i in range(6				)]
											__lowercase        =      VGroup(*UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0				)
											__lowercase        =      VGroup(*UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0				)
											__lowercase        =      VGroup(UpperCAmelCase_  ,				UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0				)
											__lowercase        =      Text('''CPU'''  ,				font_size=2_4				)
											__lowercase        =      Group(UpperCAmelCase_  ,				UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0.5  ,				aligned_edge=UpperCAmelCase_				)
											cpu.move_to([-2.5, -0.5, 0]				)
											self.add(UpperCAmelCase_				)

											__lowercase        =      [mem.copy() for i in range(4				)]
											__lowercase        =      VGroup(*UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0				)
											__lowercase        =      Text('''GPU'''  ,				font_size=2_4				)
											__lowercase        =      Group(UpperCAmelCase_  ,				UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0.5  ,				aligned_edge=UpperCAmelCase_				)
											gpu.move_to([-1, -1, 0]				)
											self.add(UpperCAmelCase_				)

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

											__lowercase        =      Text('''Model'''  ,				font_size=2_4				)
											__lowercase        =      Group(UpperCAmelCase_  ,				UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0.5  ,				aligned_edge=UpperCAmelCase_				)
											model.move_to([3, -1.0, 0]				)
											self.add(UpperCAmelCase_				)

											__lowercase        =      []
											__lowercase        =      []

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

																__lowercase        =      Rectangle(height=0.4_6 / 4  ,				width=0.4_6 / 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=0.0_2  ,				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_				)

											__lowercase        =      [meta_mem.copy() for i in range(6				)]
											__lowercase        =      [meta_mem.copy() for i in range(6				)]
											__lowercase        =      VGroup(*UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0				)
											__lowercase        =      VGroup(*UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0				)
											__lowercase        =      VGroup(UpperCAmelCase_  ,				UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0				)
											__lowercase        =      Text('''Disk'''  ,				font_size=2_4				)
											__lowercase        =      Group(UpperCAmelCase_  ,				UpperCAmelCase_				).arrange(UpperCAmelCase_  ,				buff=0.5  ,				aligned_edge=UpperCAmelCase_				)
											disk.move_to([-4.0, -1.2_5, 0]				)
											self.add(UpperCAmelCase_  ,				UpperCAmelCase_				)

											__lowercase        =      []

											for i in range(6				):
																__lowercase        =      fill.copy().set_fill(UpperCAmelCase_  ,				opacity=0.8				)
																target.move_to(disk_left_col_base[i]				).scale(0.5				)
																cpu_disk_arr.append(UpperCAmelCase_				)

											self.add(*UpperCAmelCase_				)

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

											__lowercase        =      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(UpperCAmelCase_  ,				UpperCAmelCase_				)

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

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

											__lowercase        =      MarkupText(f'''The offloaded weights are all sent to the CPU.'''  ,				font_size=2_4				)
											step_a.move_to([2, 2, 0]				)

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

											for i in range(6				):
																__lowercase        =      cpu_disk_arr[i]
																__lowercase        =      rect.copy().set_fill(UpperCAmelCase_  ,				opacity=0.8				).scale(2.0				)
																cpa.generate_target()
																cpa.target.move_to(model_base[i]				)

																if i == 0:
																					rect.set_fill(UpperCAmelCase_  ,				opacity=0.8				)
																					rect.generate_target()
																					rect.target.move_to(cpu_left_col_base[0]				).scale(2.0				)

																					self.remove(
																					    *UpperCAmelCase_  ,				*UpperCAmelCase_  ,				)

																else:
																					rect.generate_target()
																					rect.target.move_to(cpu_left_col_base[i]				).scale(2.0				)
																self.play(MoveToTarget(UpperCAmelCase_				)  ,				MoveToTarget(UpperCAmelCase_				)  ,				model_base[i].animate.set_stroke(UpperCAmelCase_				)				)
											self.play(FadeOut(UpperCAmelCase_				)				)

											__lowercase        =      MarkupText(
											    f'''Finally, hooks are added to each weight in the model\nto transfer the weights from CPU to GPU\n\t\tand back when needed.'''  ,				font_size=2_4  ,				)
											step_a.move_to([2, 2, 0]				)

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

											__lowercase        =      []
											__lowercase        =      []
											for i in range(6				):
																__lowercase        =      Arrow(start=UpperCAmelCase_  ,				end=UpperCAmelCase_  ,				color=UpperCAmelCase_  ,				buff=0.5				)
																a.next_to(model_base[i].get_left()  ,				UpperCAmelCase_  ,				buff=0.2				)
																arrows.append(UpperCAmelCase_				)
																animations.append(Write(UpperCAmelCase_				)				)
											self.play(*UpperCAmelCase_				)
											self.wait()





"""simple docstring"""

from typing import Mapping

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


a__			:						Dict							=			logging.get_logger(__name__)

a__			:						Any							=			{
    """google/long-t5-local-base""": """https://huggingface.co/google/long-t5-local-base/blob/main/config.json""",
    """google/long-t5-local-large""": """https://huggingface.co/google/long-t5-local-large/blob/main/config.json""",
    """google/long-t5-tglobal-base""": """https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json""",
    """google/long-t5-tglobal-large""": """https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json""",
}


class       _snake_case  (    UpperCamelCase							):
						__snake_case			      =  'longt5'
						__snake_case			      =  ['past_key_values']
						__snake_case			      =  {'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}







						def __init__(self  ,				UpperCAmelCase_=3_2_1_2_8  ,				UpperCAmelCase_=5_1_2  ,				UpperCAmelCase_=6_4  ,				UpperCAmelCase_=2_0_4_8  ,				UpperCAmelCase_=6  ,				UpperCAmelCase_=None  ,				UpperCAmelCase_=8  ,				UpperCAmelCase_=1_2_7  ,				UpperCAmelCase_=1_6  ,				UpperCAmelCase_=3_2  ,				UpperCAmelCase_=1_2_8  ,				UpperCAmelCase_=0.1  ,				UpperCAmelCase_=1e-6  ,				UpperCAmelCase_=1.0  ,				UpperCAmelCase_="relu"  ,				UpperCAmelCase_=True  ,				UpperCAmelCase_="local"  ,				UpperCAmelCase_=True  ,				UpperCAmelCase_=0  ,				UpperCAmelCase_=1  ,				**UpperCAmelCase_  ,				)      ->    int:
											__lowercase        =      vocab_size
											__lowercase        =      d_model
											__lowercase        =      d_kv
											__lowercase        =      d_ff
											__lowercase        =      num_layers
											# default = symmetry
											__lowercase        =      num_decoder_layers if num_decoder_layers is not None else self.num_layers
											__lowercase        =      num_heads
											__lowercase        =      local_radius
											__lowercase        =      global_block_size
											__lowercase        =      relative_attention_num_buckets
											__lowercase        =      relative_attention_max_distance
											__lowercase        =      dropout_rate
											__lowercase        =      layer_norm_epsilon
											__lowercase        =      initializer_factor
											__lowercase        =      feed_forward_proj
											__lowercase        =      encoder_attention_type
											__lowercase        =      use_cache

											__lowercase        =      self.feed_forward_proj.split('''-'''				)
											__lowercase        =      act_info[-1]
											__lowercase        =      act_info[0] == '''gated'''

											if len(UpperCAmelCase_				) > 1 and act_info[0] != "gated" or len(UpperCAmelCase_				) > 2:
																raise ValueError(
																    f'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
																    '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
																    '''\'gated-gelu\' or \'relu\''''				)

											# for backwards compatibility
											if feed_forward_proj == "gated-gelu":
																__lowercase        =      '''gelu_new'''

											super().__init__(
											    pad_token_id=UpperCAmelCase_  ,				eos_token_id=UpperCAmelCase_  ,				is_encoder_decoder=UpperCAmelCase_  ,				**UpperCAmelCase_  ,				)



class       _snake_case  (    UpperCamelCase							):







						@property
						def 							_UpperCamelCase     (self				)      ->    Mapping[str, Mapping[int, str]]:
											__lowercase        =      {
											    '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
											    '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
											}
											if self.use_past:
																__lowercase        =      '''past_encoder_sequence + sequence'''
																__lowercase        =      {0: '''batch'''}
																__lowercase        =      {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
											else:
																__lowercase        =      {0: '''batch''', 1: '''decoder_sequence'''}
																__lowercase        =      {0: '''batch''', 1: '''decoder_sequence'''}

											if self.use_past:
																self.fill_with_past_key_values_(UpperCAmelCase_  ,				direction='''inputs'''				)

											return common_inputs







						@property
						def 							_UpperCamelCase     (self				)      ->    int:
											return 1_3


