
"""simple docstring"""




import json
import logging
import os
import sys
from pathlib import Path

import finetune_rag

from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
    TestCasePlus,
    execute_subprocess_async,
    require_ray,
    require_torch_gpu,
    require_torch_multi_gpu,
)


logging.basicConfig(level=logging.DEBUG)
UpperCAmelCase__   :					Union[str, Any]												=				logging.getLogger()

UpperCAmelCase__   :					Any												=				logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)



class 			lowerCAmelCase_		(a__						):


				"""simple docstring"""



				def 			__magic_name__					(self     , SCREAMING_SNAKE_CASE__					)      ->	Dict:



											"""simple docstring"""




											os.makedirs(SCREAMING_SNAKE_CASE__     , exist_ok=SCREAMING_SNAKE_CASE__					)
											SCREAMING_SNAKE_CASE__		: Tuple     =     {"""source""": """What is love ?""", """target""": """life"""}
											SCREAMING_SNAKE_CASE__		: str     =     {"""train""": 12, """val""": 2, """test""": 2}
											for split in ["train", "test", "val"]:
																		for field in ["source", "target"]:
																									SCREAMING_SNAKE_CASE__		: List[str]     =     """\n""".join([contents[field]] * n_lines[split]					)
																									with open(os.path.join(SCREAMING_SNAKE_CASE__     , F'''{split}.{field}'''					)     , """w"""					) as f:
																																f.write(SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self     , SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__ = "pytorch"					)      ->	List[str]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: List[Any]     =     self.get_auto_remove_tmp_dir()
											SCREAMING_SNAKE_CASE__		: int     =     os.path.join(SCREAMING_SNAKE_CASE__     , """output"""					)
											SCREAMING_SNAKE_CASE__		: Dict     =     os.path.join(SCREAMING_SNAKE_CASE__     , """data"""					)
											self._create_dummy_data(data_dir=SCREAMING_SNAKE_CASE__					)

											SCREAMING_SNAKE_CASE__		: Any     =     F'''
                --data_dir {data_dir} \
                --output_dir {output_dir} \
                --model_name_or_path facebook/rag-sequence-base \
                --model_type rag_sequence \
                --do_train \
                --do_predict \
                --n_val -1 \
                --val_check_interval 1.0 \
                --train_batch_size 2 \
                --eval_batch_size 1 \
                --max_source_length 25 \
                --max_target_length 25 \
                --val_max_target_length 25 \
                --test_max_target_length 25 \
                --label_smoothing 0.1 \
                --dropout 0.1 \
                --attention_dropout 0.1 \
                --weight_decay 0.001 \
                --adam_epsilon 1e-08 \
                --max_grad_norm 0.1 \
                --lr_scheduler polynomial \
                --learning_rate 3e-04 \
                --num_train_epochs 1 \
                --warmup_steps 4 \
                --gradient_accumulation_steps 1 \
                --distributed-port 8787 \
                --use_dummy_dataset 1 \
                --distributed_retriever {distributed_retriever} \
            '''.split()

											if gpus > 0:
																		testargs.append(F'''--gpus={gpus}'''					)
																		if is_apex_available():
																									testargs.append("""--fp16"""					)
											else:
																		testargs.append("""--gpus=0"""					)
																		testargs.append("""--distributed_backend=ddp_cpu"""					)
																		testargs.append("""--num_processes=2"""					)

											SCREAMING_SNAKE_CASE__		: Dict     =     [sys.executable, str(Path(finetune_rag.__file__					).resolve()					)] + testargs
											execute_subprocess_async(SCREAMING_SNAKE_CASE__     , env=self.get_env()					)

											SCREAMING_SNAKE_CASE__		: Dict     =     os.path.join(SCREAMING_SNAKE_CASE__     , """metrics.json"""					)
											with open(SCREAMING_SNAKE_CASE__					) as f:
																		SCREAMING_SNAKE_CASE__		: Tuple     =     json.load(SCREAMING_SNAKE_CASE__					)
											return result



				@require_torch_gpu
				def 			__magic_name__					(self					)      ->	Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: str     =     self._run_finetune(gpus=1					)
											self.assertGreaterEqual(result["""test"""][0]["""test_avg_em"""]     , 0.2					)



				@require_torch_multi_gpu
				def 			__magic_name__					(self					)      ->	Tuple:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Tuple     =     self._run_finetune(gpus=2					)
											self.assertGreaterEqual(result["""test"""][0]["""test_avg_em"""]     , 0.2					)



				@require_torch_gpu
				@require_ray
				def 			__magic_name__					(self					)      ->	Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Dict     =     self._run_finetune(gpus=1     , distributed_retriever="""ray"""					)
											self.assertGreaterEqual(result["""test"""][0]["""test_avg_em"""]     , 0.2					)



				@require_torch_multi_gpu
				@require_ray
				def 			__magic_name__					(self					)      ->	str:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Optional[int]     =     self._run_finetune(gpus=1     , distributed_retriever="""ray"""					)
											self.assertGreaterEqual(result["""test"""][0]["""test_avg_em"""]     , 0.2					)






"""simple docstring"""




from manim import *



class 			lowerCAmelCase_		(a__						):


				"""simple docstring"""



				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Dict     =     Rectangle(height=0.5     , width=0.5					)
											SCREAMING_SNAKE_CASE__		: Dict     =     Rectangle(height=0.46     , width=0.46					).set_stroke(width=0					)

											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     Rectangle(height=0.25     , width=0.25					)

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

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

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

											SCREAMING_SNAKE_CASE__		: Tuple     =     Text("""Model"""     , font_size=24					)
											SCREAMING_SNAKE_CASE__		: Dict     =     Group(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					).arrange(SCREAMING_SNAKE_CASE__     , buff=0.5     , aligned_edge=SCREAMING_SNAKE_CASE__					)
											model.move_to([3, -1.0, 0]					)
											self.add(SCREAMING_SNAKE_CASE__					)

											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     []
											SCREAMING_SNAKE_CASE__		: Any     =     []

											for i, rect in enumerate(SCREAMING_SNAKE_CASE__					):
																		SCREAMING_SNAKE_CASE__		: List[str]     =     fill.copy().set_fill(SCREAMING_SNAKE_CASE__     , opacity=0.8					)
																		target.move_to(SCREAMING_SNAKE_CASE__					)
																		model_arr.append(SCREAMING_SNAKE_CASE__					)

																		SCREAMING_SNAKE_CASE__		: List[str]     =     Rectangle(height=0.46     , width=0.46					).set_stroke(width=0.0					).set_fill(SCREAMING_SNAKE_CASE__     , opacity=0.8					)
																		cpu_target.move_to(cpu_left_col_base[i]					)
																		model_cpu_arr.append(SCREAMING_SNAKE_CASE__					)

											self.add(*SCREAMING_SNAKE_CASE__     , *SCREAMING_SNAKE_CASE__					)

											SCREAMING_SNAKE_CASE__		: Tuple     =     [meta_mem.copy() for i in range(6					)]
											SCREAMING_SNAKE_CASE__		: List[str]     =     [meta_mem.copy() for i in range(6					)]
											SCREAMING_SNAKE_CASE__		: Any     =     VGroup(*SCREAMING_SNAKE_CASE__					).arrange(SCREAMING_SNAKE_CASE__     , buff=0					)
											SCREAMING_SNAKE_CASE__		: int     =     VGroup(*SCREAMING_SNAKE_CASE__					).arrange(SCREAMING_SNAKE_CASE__     , buff=0					)
											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     VGroup(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					).arrange(SCREAMING_SNAKE_CASE__     , buff=0					)
											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     Text("""Disk"""     , font_size=24					)
											SCREAMING_SNAKE_CASE__		: Any     =     Group(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					).arrange(SCREAMING_SNAKE_CASE__     , buff=0.5     , aligned_edge=SCREAMING_SNAKE_CASE__					)
											disk.move_to([-4, -1.25, 0]					)
											self.add(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)

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

											SCREAMING_SNAKE_CASE__		: List[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(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)

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

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

											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     MarkupText(
											    F'''Now watch as an input is passed through the model\nand how the memory is utilized and handled.'''     , font_size=24     , )
											step_a.move_to([2, 2, 0]					)

											self.play(Write(SCREAMING_SNAKE_CASE__					)					)

											SCREAMING_SNAKE_CASE__		: Dict     =     Square(0.3					)
											input.set_fill(SCREAMING_SNAKE_CASE__     , opacity=1.0					)
											input.set_stroke(width=0.0					)
											input.next_to(model_base[0]     , SCREAMING_SNAKE_CASE__     , buff=0.5					)

											self.play(Write(SCREAMING_SNAKE_CASE__					)					)

											input.generate_target()
											input.target.next_to(model_arr[0]     , direction=SCREAMING_SNAKE_CASE__     , buff=0.02					)
											self.play(MoveToTarget(SCREAMING_SNAKE_CASE__					)					)

											self.play(FadeOut(SCREAMING_SNAKE_CASE__					)					)

											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     Arrow(start=SCREAMING_SNAKE_CASE__     , end=SCREAMING_SNAKE_CASE__     , color=SCREAMING_SNAKE_CASE__     , buff=0.5					)
											a.next_to(model_arr[0].get_left()     , SCREAMING_SNAKE_CASE__     , buff=0.2					)

											model_cpu_arr[0].generate_target()
											model_cpu_arr[0].target.move_to(gpu_rect[0]					)

											SCREAMING_SNAKE_CASE__		: Tuple     =     MarkupText(
											    F'''As the input reaches a layer, the hook triggers\nand weights are moved from the CPU\nto the GPU and back.'''     , font_size=24     , )
											step_a.move_to([2, 2, 0]					)

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

											SCREAMING_SNAKE_CASE__		: Tuple     =     {"""run_time""": 1, """fade_in""": True, """fade_out""": True, """buff""": 0.02}

											self.play(
											    Write(SCREAMING_SNAKE_CASE__					)     , Circumscribe(model_arr[0]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , Circumscribe(model_cpu_arr[0]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , Circumscribe(gpu_rect[0]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , )
											self.play(MoveToTarget(model_cpu_arr[0]					)					)

											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     a.copy()
											for i in range(6					):
																		a_c.next_to(model_arr[i].get_right() + 0.02     , SCREAMING_SNAKE_CASE__     , buff=0.2					)

																		input.generate_target()
																		input.target.move_to(model_arr[i].get_right() + 0.02					)

																		SCREAMING_SNAKE_CASE__		: Optional[Any]     =     AnimationGroup(
																		    FadeOut(SCREAMING_SNAKE_CASE__     , run_time=0.5					)     , MoveToTarget(SCREAMING_SNAKE_CASE__     , run_time=0.5					)     , FadeIn(SCREAMING_SNAKE_CASE__     , run_time=0.5					)     , lag_ratio=0.2					)

																		self.play(SCREAMING_SNAKE_CASE__					)

																		model_cpu_arr[i].generate_target()
																		model_cpu_arr[i].target.move_to(cpu_left_col_base[i]					)

																		if i < 5:
																									model_cpu_arr[i + 1].generate_target()
																									model_cpu_arr[i + 1].target.move_to(gpu_rect[0]					)
																									if i >= 1:
																																SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     0.7

																									self.play(
																									    Circumscribe(model_arr[i]     , **SCREAMING_SNAKE_CASE__					)     , Circumscribe(cpu_left_col_base[i]     , **SCREAMING_SNAKE_CASE__					)     , Circumscribe(cpu_left_col_base[i + 1]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , Circumscribe(gpu_rect[0]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , Circumscribe(model_arr[i + 1]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , )
																									if i < 1:
																																self.play(
																																    MoveToTarget(model_cpu_arr[i]					)     , MoveToTarget(model_cpu_arr[i + 1]					)     , )
																									else:
																																self.play(
																																    MoveToTarget(model_cpu_arr[i]     , run_time=0.7					)     , MoveToTarget(model_cpu_arr[i + 1]     , run_time=0.7					)     , )
																		else:
																									model_cpu_arr[i].generate_target()
																									model_cpu_arr[i].target.move_to(cpu_left_col_base[-1]					)
																									input.generate_target()
																									input.target.next_to(model_arr[-1].get_right()     , RIGHT + 0.02     , buff=0.2					)

																									self.play(
																									    Circumscribe(model_arr[-1]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , Circumscribe(cpu_left_col_base[-1]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , Circumscribe(gpu_rect[0]     , color=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)     , )

																									self.play(MoveToTarget(model_cpu_arr[i]					)					)

																		SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     a_c
																		SCREAMING_SNAKE_CASE__		: Optional[Any]     =     a_c.copy()

											input.generate_target()
											input.target.next_to(model_base[-1]     , RIGHT + 0.02     , buff=0.5					)
											self.play(
											    FadeOut(SCREAMING_SNAKE_CASE__					)     , FadeOut(SCREAMING_SNAKE_CASE__     , run_time=0.5					)     , )

											SCREAMING_SNAKE_CASE__		: Dict     =     MarkupText(F'''Inference on a model too large for GPU memory\nis successfully completed.'''     , font_size=24					)
											step_a.move_to([2, 2, 0]					)

											self.play(Write(SCREAMING_SNAKE_CASE__     , run_time=3					)     , MoveToTarget(SCREAMING_SNAKE_CASE__					)					)

											self.wait()




