




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_UpperCAmelCase	:						Any			=     {
    "configuration_mask2former": [
        "MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Mask2FormerConfig",
    ],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase	:						Union[str, Any]			=     ["Mask2FormerImageProcessor"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase	:						Union[str, Any]			=     [
         "MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
         "Mask2FormerForUniversalSegmentation",
         "Mask2FormerModel",
         "Mask2FormerPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_maskaformer import MaskaFormerImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_maskaformer import (
              MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              MaskaFormerForUniversalSegmentation,
              MaskaFormerModel,
              MaskaFormerPreTrainedModel,
          )


else:
     import sys

     _UpperCAmelCase	:						List[Any]			=     _LazyModule(__name__, globals()["__file__"], _import_structure)









import json
import os
import tempfile
from unittest.mock import patch

import torch
from torch.utils.data import DataLoader, TensorDataset

from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, PartialState
from accelerate.test_utils import require_bnb, require_multi_gpu, slow
from accelerate.test_utils.testing import AccelerateTestCase, require_cuda
from accelerate.utils import patch_environment



def       UpperCAmelCase__  (     ):
  lowercase    :List[str]      	=						torch.nn.Linear(2,			4   )
  lowercase    :List[Any]      	=						torch.optim.AdamW(model.parameters(),			lr=1.0   )
  lowercase    :int      	=						torch.optim.lr_scheduler.OneCycleLR(lowerCamelCase,			max_lr=0.01,			steps_per_epoch=2,			epochs=1   )
  lowercase    :Optional[int]      	=						DataLoader(TensorDataset(torch.tensor([1, 2, 3]   )   )   )
  lowercase    :List[str]      	=						DataLoader(TensorDataset(torch.tensor([4, 5, 6]   )   )   )

  return model, optimizer, scheduler, train_dl, valid_dl



def       UpperCAmelCase__  (     lowerCamelCase   ):
  return (model.weight.abs().sum() + model.bias.abs().sum()).item()



def       UpperCAmelCase__  (     lowerCamelCase   ):
  lowercase    :Dict      	=						torch.nn.Linear(*tuple(model.weight.T.shape   )   ).state_dict()
  model.load_state_dict(lowerCamelCase   )







class    __lowerCAmelCase       (							lowerCAmelCase):






       @require_cuda
       def 					SCREAMING_SNAKE_CASE    (   self:					str				):
         lowercase    :List[str]      	=						Accelerator()
         assert PartialState._shared_state["_cpu"] is False
         assert PartialState._shared_state["device"].type == "cuda"
         with self.assertRaises(_lowerCAmelCase				):
           lowercase    :Any      	=						Accelerator(cpu=_lowerCAmelCase				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Tuple				):
         lowercase    :Any      	=						Accelerator()
         lowercase    :Dict      	=						GradientState()
         assert state.num_steps == 1
         lowercase    :Tuple      	=						4
         assert state.num_steps == 4

         assert state.sync_gradients is True
         lowercase    :List[Any]      	=						False
         assert state.sync_gradients is False
         GradientState._reset_state()






       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         lowercase    :str      	=						Accelerator()
         lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase    :Any      	=						create_components()

         (
             (
             lowercase
         )	,    (
             lowercase
         )	,    (
             lowercase
         )	,    (
             lowercase
         )	,    (
             lowercase
         )	,    
         )    :Tuple      	=						accelerator.prepare(_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase				)

         self.assertTrue(prepared_model in accelerator._models				)
         self.assertTrue(prepared_optimizer in accelerator._optimizers				)
         self.assertTrue(prepared_scheduler in accelerator._schedulers				)
         self.assertTrue(prepared_train_dl in accelerator._dataloaders				)
         self.assertTrue(prepared_valid_dl in accelerator._dataloaders				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Any				):
         lowercase    :Dict      	=						Accelerator()
         lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase    :List[str]      	=						create_components()
         accelerator.prepare(_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase				)
         accelerator.free_memory()

         self.assertTrue(len(accelerator._models				) == 0				)
         self.assertTrue(len(accelerator._optimizers				) == 0				)
         self.assertTrue(len(accelerator._schedulers				) == 0				)
         self.assertTrue(len(accelerator._dataloaders				) == 0				)






       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         PartialState._reset_state()

         # Mock torch.cuda.set_device to avoid an exception as the device doesn't exist
         def noop(*_lowerCAmelCase:					List[str]       ,					**_lowerCAmelCase:					Optional[int]				):
           pass

         with patch("torch.cuda.set_device"       ,					_lowerCAmelCase				), patch_environment(ACCELERATE_TORCH_DEVICE="cuda:64"				):
           lowercase    :List[Any]      	=						Accelerator()
           self.assertEqual(str(accelerator.state.device				)       ,					"cuda:64"				)






       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         lowercase    :Tuple      	=						Accelerator()
         lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase    :Optional[Any]      	=						create_components()
         accelerator.prepare(_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase				)

         lowercase    :Tuple      	=						get_signature(_lowerCAmelCase				)

         with tempfile.TemporaryDirectory() as tmpdirname:
           accelerator.save_state(_lowerCAmelCase				)

           # make sure random weights don't match
           load_random_weights(_lowerCAmelCase				)
           self.assertTrue(abs(model_signature - get_signature(_lowerCAmelCase				)				) > 1e-3				)

           # make sure loaded weights match
           accelerator.load_state(_lowerCAmelCase				)
           self.assertTrue(abs(model_signature - get_signature(_lowerCAmelCase				)				) < 1e-3				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[int]				):
         lowercase    :Dict      	=						Accelerator()
         lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase    :int      	=						create_components()
         accelerator.prepare(_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase				)

         lowercase    :int      	=						get_signature(_lowerCAmelCase				)

         # saving hook
         def save_config(_lowerCAmelCase:					Union[str, Any]       ,					_lowerCAmelCase:					str       ,					_lowerCAmelCase:					List[Any]				):
           lowercase    :Dict      	=						{"class_name": models[0].__class__.__name__}

           with open(os.path.join(_lowerCAmelCase       ,					"data.json"				)       ,					"w"				) as f:
             json.dump(_lowerCAmelCase       ,					_lowerCAmelCase				)

        # loading hook
         def load_config(_lowerCAmelCase:					Union[str, Any]       ,					_lowerCAmelCase:					Union[str, Any]				):
           with open(os.path.join(_lowerCAmelCase       ,					"data.json"				)       ,					"r"				) as f:
             lowercase    :int      	=						json.load(_lowerCAmelCase				)

           lowercase    :Optional[int]      	=						config["class_name"]

         lowercase    :Optional[Any]      	=						accelerator.register_save_state_pre_hook(_lowerCAmelCase				)
         lowercase    :Tuple      	=						accelerator.register_load_state_pre_hook(_lowerCAmelCase				)

         with tempfile.TemporaryDirectory() as tmpdirname:
           accelerator.save_state(_lowerCAmelCase				)

           # make sure random weights don't match with hooks
           load_random_weights(_lowerCAmelCase				)
           self.assertTrue(abs(model_signature - get_signature(_lowerCAmelCase				)				) > 1e-3				)

           # random class name to verify correct one is loaded
           lowercase    :Optional[int]      	=						"random"

           # make sure loaded weights match with hooks
           accelerator.load_state(_lowerCAmelCase				)
           self.assertTrue(abs(model_signature - get_signature(_lowerCAmelCase				)				) < 1e-3				)

           # mode.class_name is loaded from config
           self.assertTrue(model.class_name == model.__class__.__name__				)

         # remove hooks
         save_hook.remove()
         load_hook.remove()

         with tempfile.TemporaryDirectory() as tmpdirname:
           accelerator.save_state(_lowerCAmelCase				)

           # make sure random weights don't match with hooks removed
           load_random_weights(_lowerCAmelCase				)
           self.assertTrue(abs(model_signature - get_signature(_lowerCAmelCase				)				) > 1e-3				)

           # random class name to verify correct one is loaded
           lowercase    :str      	=						"random"

           # make sure loaded weights match with hooks removed
           accelerator.load_state(_lowerCAmelCase				)
           self.assertTrue(abs(model_signature - get_signature(_lowerCAmelCase				)				) < 1e-3				)

           # mode.class_name is NOT loaded from config
           self.assertTrue(model.class_name != model.__class__.__name__				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[int]				):
         lowercase    :List[str]      	=						Accelerator()
         lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase    :List[Any]      	=						create_components()
         lowercase    :List[str]      	=						None

         # This should work
         lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase    :str      	=						accelerator.prepare(
             _lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase				)
         self.assertTrue(dummy_obj is None				)






       def 					SCREAMING_SNAKE_CASE    (   self:					List[str]				):
         lowercase    :Union[str, Any]      	=						Accelerator()
         lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase    :Union[str, Any]      	=						create_components()
         lowercase    :Union[str, Any]      	=						[1, 2, 3]

         # This should work
         lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase	,    lowercase    :List[str]      	=						accelerator.prepare(
             _lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase				)
         self.assertEqual(
             getattr(_lowerCAmelCase       ,					"_is_accelerate_prepared"       ,					_lowerCAmelCase				)       ,					_lowerCAmelCase       ,					"Dummy object should have `_is_accelerate_prepared` set to `True`"       ,					)
         self.assertEqual(
             getattr(_lowerCAmelCase       ,					"_is_accelerate_prepared"       ,					_lowerCAmelCase				)       ,					_lowerCAmelCase       ,					"Model is missing `_is_accelerator_prepared` or is set to `False`"       ,					)
         self.assertEqual(
             getattr(_lowerCAmelCase       ,					"_is_accelerate_prepared"       ,					_lowerCAmelCase				)       ,					_lowerCAmelCase       ,					"Optimizer is missing `_is_accelerator_prepared` or is set to `False`"       ,					)
         self.assertEqual(
             getattr(_lowerCAmelCase       ,					"_is_accelerate_prepared"       ,					_lowerCAmelCase				)       ,					_lowerCAmelCase       ,					"Scheduler is missing `_is_accelerator_prepared` or is set to `False`"       ,					)
         self.assertEqual(
             getattr(_lowerCAmelCase       ,					"_is_accelerate_prepared"       ,					_lowerCAmelCase				)       ,					_lowerCAmelCase       ,					"Train Dataloader is missing `_is_accelerator_prepared` or is set to `False`"       ,					)
         self.assertEqual(
             getattr(_lowerCAmelCase       ,					"_is_accelerate_prepared"       ,					_lowerCAmelCase				)       ,					_lowerCAmelCase       ,					"Valid Dataloader is missing `_is_accelerator_prepared` or is set to `False`"       ,					)






       @slow
       @require_bnb
       def 					SCREAMING_SNAKE_CASE    (   self:					Union[str, Any]				):
         from transformers import AutoModelForCausalLM

         lowercase    :Any      	=						AutoModelForCausalLM.from_pretrained(
             "EleutherAI/gpt-neo-125m"       ,					load_in_abit=_lowerCAmelCase       ,					device_map={"": 0}       ,					)
         lowercase    :int      	=						Accelerator()

         # This should work
         lowercase    :Optional[int]      	=						accelerator.prepare(_lowerCAmelCase				)






       @slow
       @require_bnb
       def 					SCREAMING_SNAKE_CASE    (   self:					List[str]				):
         from transformers import AutoModelForCausalLM

         lowercase    :Optional[Any]      	=						Accelerator()

         with init_empty_weights():
           lowercase    :Any      	=						AutoModelForCausalLM.from_pretrained(
               "EleutherAI/gpt-neo-125m"       ,					)
           model.tie_weights()
           lowercase    :Dict      	=						infer_auto_device_map(_lowerCAmelCase				)
           lowercase    :int      	=						"cpu"

         lowercase    :str      	=						AutoModelForCausalLM.from_pretrained(
             "EleutherAI/gpt-neo-125m"       ,					device_map=_lowerCAmelCase       ,					load_in_abit=_lowerCAmelCase       ,					llm_inta_enable_fpaa_cpu_offload=_lowerCAmelCase				)

         # This should not work and get value error
         with self.assertRaises(_lowerCAmelCase				):
           lowercase    :Dict      	=						accelerator.prepare(_lowerCAmelCase				)






       @slow
       @require_bnb
       @require_multi_gpu
       def 					SCREAMING_SNAKE_CASE    (   self:					Any				):
         from transformers import AutoModelForCausalLM

         lowercase    :List[str]      	=						{"distributed_type": DistributedType.MULTI_GPU}

         with init_empty_weights():
           lowercase    :str      	=						AutoModelForCausalLM.from_pretrained(
               "EleutherAI/gpt-neo-125m"       ,					)
           model.tie_weights()
           lowercase    :Optional[Any]      	=						infer_auto_device_map(_lowerCAmelCase				)
           lowercase    :Any      	=						1

         lowercase    :str      	=						AutoModelForCausalLM.from_pretrained(
             "EleutherAI/gpt-neo-125m"       ,					load_in_abit=_lowerCAmelCase       ,					device_map=_lowerCAmelCase       ,					)
         lowercase    :List[str]      	=						Accelerator()

         # This should not work and get value error
         with self.assertRaises(_lowerCAmelCase				):
           lowercase    :Optional[Any]      	=						accelerator.prepare(_lowerCAmelCase				)

         PartialState._reset_state()






       @slow
       @require_bnb
       @require_multi_gpu
       def 					SCREAMING_SNAKE_CASE    (   self:					List[Any]				):
         from transformers import AutoModelForCausalLM

         with init_empty_weights():
           lowercase    :List[str]      	=						AutoModelForCausalLM.from_pretrained(
               "EleutherAI/gpt-neo-125m"       ,					)
           lowercase    :List[Any]      	=						infer_auto_device_map(_lowerCAmelCase				)
           lowercase    :Optional[int]      	=						1

         lowercase    :Union[str, Any]      	=						AutoModelForCausalLM.from_pretrained(
             "EleutherAI/gpt-neo-125m"       ,					load_in_abit=_lowerCAmelCase       ,					device_map=_lowerCAmelCase       ,					)
         lowercase    :Union[str, Any]      	=						Accelerator()

         # This should work
         lowercase    :List[Any]      	=						accelerator.prepare(_lowerCAmelCase				)






       @require_cuda
       def 					SCREAMING_SNAKE_CASE    (   self:					Any				):
         lowercase    :Optional[int]      	=						torch.nn.Linear(10       ,					10				)
         lowercase    :Optional[int]      	=						torch.optim.SGD(model.parameters()       ,					lr=0.01				)
         lowercase    :List[Any]      	=						Accelerator(cpu=_lowerCAmelCase				)
         lowercase    :List[str]      	=						accelerator.prepare(_lowerCAmelCase				)



