


import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from requests.exceptions import HTTPError

from transformers.utils import (
    CONFIG_NAME,
    FLAX_WEIGHTS_NAME,
    TF2_WEIGHTS_NAME,
    TRANSFORMERS_CACHE,
    WEIGHTS_NAME,
    cached_file,
    get_file_from_repo,
    has_file,
)


a					  =     'hf-internal-testing/tiny-random-bert'
a					  =     os.path.join(TRANSFORMERS_CACHE, 'models--hf-internal-testing--tiny-random-bert')
a					  =     '9b8c223d42b2188cb49d29af482996f9d0f3e5a6'







class        UpperCamelCase__   (	unittest.TestCase   ):

					def   UpperCAmelCase__       (     self       :   Optional[Any]       ):






										'''simple docstring'''






										lowercase_  							=			cached_file(UpperCAmelCase_							,					UpperCAmelCase_       )
										# Should have downloaded the file in here
										self.assertTrue(os.path.isdir(UpperCAmelCase_       )       )
										# Cache should contain at least those three subfolders:
										for subfolder in ["blobs", "refs", "snapshots"]:
															self.assertTrue(os.path.isdir(os.path.join(UpperCAmelCase_							,					UpperCAmelCase_       )       )       )
										with open(os.path.join(UpperCAmelCase_							,					"""refs"""							,					"""main"""       )       ) as f:
															lowercase_  							=			f.read()
										self.assertEqual(UpperCAmelCase_							,					os.path.join(UpperCAmelCase_							,					"""snapshots"""							,					UpperCAmelCase_							,					UpperCAmelCase_       )       )
										self.assertTrue(os.path.isfile(UpperCAmelCase_       )       )

										# File is cached at the same place the second time.
										lowercase_  							=			cached_file(UpperCAmelCase_							,					UpperCAmelCase_       )
										self.assertEqual(UpperCAmelCase_							,					UpperCAmelCase_       )

										# Using a specific revision to test the full commit hash.
										lowercase_  							=			cached_file(UpperCAmelCase_							,					UpperCAmelCase_							,					revision="""9b8c223"""       )
										self.assertEqual(UpperCAmelCase_							,					os.path.join(UpperCAmelCase_							,					"""snapshots"""							,					UpperCAmelCase_							,					UpperCAmelCase_       )       )

					def   UpperCAmelCase__       (     self       :   Any       ):






										'''simple docstring'''






										with self.assertRaisesRegex(UpperCAmelCase_							,					"""is not a valid model identifier"""       ):
															lowercase_  							=			cached_file("""tiny-random-bert"""							,					UpperCAmelCase_       )

										with self.assertRaisesRegex(UpperCAmelCase_							,					"""is not a valid git identifier"""       ):
															lowercase_  							=			cached_file(UpperCAmelCase_							,					UpperCAmelCase_							,					revision="""aaaa"""       )

										with self.assertRaisesRegex(UpperCAmelCase_							,					"""does not appear to have a file named"""       ):
															lowercase_  							=			cached_file(UpperCAmelCase_							,					"""conf"""       )

					def   UpperCAmelCase__       (     self       :   str       ):






										'''simple docstring'''






										with self.assertRaisesRegex(UpperCAmelCase_							,					"""does not appear to have a file named"""       ):
															lowercase_  							=			cached_file(UpperCAmelCase_							,					"""conf"""       )

										with open(os.path.join(UpperCAmelCase_							,					"""refs"""							,					"""main"""       )       ) as f:
															lowercase_  							=			f.read()
										self.assertTrue(os.path.isfile(os.path.join(UpperCAmelCase_							,					""".no_exist"""							,					UpperCAmelCase_							,					"""conf"""       )       )       )

										lowercase_  							=			cached_file(UpperCAmelCase_							,					"""conf"""							,					_raise_exceptions_for_missing_entries=UpperCAmelCase_       )
										self.assertIsNone(UpperCAmelCase_       )

										lowercase_  							=			cached_file(UpperCAmelCase_							,					"""conf"""							,					local_files_only=UpperCAmelCase_							,					_raise_exceptions_for_missing_entries=UpperCAmelCase_       )
										self.assertIsNone(UpperCAmelCase_       )

										lowercase_  							=			mock.Mock()
										lowercase_  							=			500
										lowercase_  							=			{}
										lowercase_  							=			HTTPError
										lowercase_  							=			{}

										# Under the mock environment we get a 500 error when trying to reach the tokenizer.
										with mock.patch("""requests.Session.request"""							,					return_value=UpperCAmelCase_       ) as mock_head:
															lowercase_  							=			cached_file(UpperCAmelCase_							,					"""conf"""							,					_raise_exceptions_for_connection_errors=UpperCAmelCase_       )
															self.assertIsNone(UpperCAmelCase_       )
															# This check we did call the fake head request
															mock_head.assert_called()

					def   UpperCAmelCase__       (     self       :   Any       ):






										'''simple docstring'''






										self.assertTrue(has_file("""hf-internal-testing/tiny-bert-pt-only"""							,					UpperCAmelCase_       )       )
										self.assertFalse(has_file("""hf-internal-testing/tiny-bert-pt-only"""							,					UpperCAmelCase_       )       )
										self.assertFalse(has_file("""hf-internal-testing/tiny-bert-pt-only"""							,					UpperCAmelCase_       )       )

					def   UpperCAmelCase__       (     self       :   Optional[Any]       ):






										'''simple docstring'''






										self.assertIsNone(get_file_from_repo("""bert-base-cased"""							,					"""ahah.txt"""       )       )

										# The function raises if the repository does not exist.
										with self.assertRaisesRegex(UpperCAmelCase_							,					"""is not a valid model identifier"""       ):
															get_file_from_repo("""bert-base-case"""							,					UpperCAmelCase_       )

										# The function raises if the revision does not exist.
										with self.assertRaisesRegex(UpperCAmelCase_							,					"""is not a valid git identifier"""       ):
															get_file_from_repo("""bert-base-cased"""							,					UpperCAmelCase_							,					revision="""ahaha"""       )

										lowercase_  							=			get_file_from_repo("""bert-base-cased"""							,					UpperCAmelCase_       )
										# The name is the cached name which is not very easy to test, so instead we load the content.
										lowercase_  							=			json.loads(open(UpperCAmelCase_							,					"""r"""       ).read()       )
										self.assertEqual(config["""hidden_size"""]							,					768       )







					def   UpperCAmelCase__       (     self       :   int       ):






										'''simple docstring'''






										with tempfile.TemporaryDirectory() as tmp_dir:
															lowercase_  							=			Path(UpperCAmelCase_       ) / """a.txt"""
															filename.touch()
															self.assertEqual(get_file_from_repo(UpperCAmelCase_							,					"""a.txt"""       )							,					str(UpperCAmelCase_       )       )

															self.assertIsNone(get_file_from_repo(UpperCAmelCase_							,					"""b.txt"""       )       )






import torch

from diffusers import UnCLIPScheduler

from .test_schedulers import SchedulerCommonTest







class        UpperCamelCase__   (	__magic_name__   ):
					__SCREAMING_SNAKE_CASE       :  str						=   (UnCLIPScheduler,)

					def   UpperCAmelCase__       (     self       :   int							,					**UpperCamelCase__       :   int       ):






										'''simple docstring'''






										lowercase_  							=			{
										    """num_train_timesteps""": 1_000,
										    """variance_type""": """fixed_small_log""",
										    """clip_sample""": True,
										    """clip_sample_range""": 1.0,
										    """prediction_type""": """epsilon""",
										}

										config.update(**UpperCamelCase__       )
										return config

					def   UpperCAmelCase__       (     self       :   Tuple       ):






										'''simple docstring'''






										for timesteps in [1, 5, 100, 1_000]:
															self.check_over_configs(num_train_timesteps=UpperCamelCase__       )

					def   UpperCAmelCase__       (     self       :   Optional[Any]       ):






										'''simple docstring'''






										for variance in ["fixed_small_log", "learned_range"]:
															self.check_over_configs(variance_type=UpperCamelCase__       )

					def   UpperCAmelCase__       (     self       :   List[str]       ):






										'''simple docstring'''






										for clip_sample in [True, False]:
															self.check_over_configs(clip_sample=UpperCamelCase__       )

					def   UpperCAmelCase__       (     self       :   Any       ):






										'''simple docstring'''






										for clip_sample_range in [1, 5, 10, 20]:
															self.check_over_configs(clip_sample_range=UpperCamelCase__       )

					def   UpperCAmelCase__       (     self       :   Tuple       ):






										'''simple docstring'''






										for prediction_type in ["epsilon", "sample"]:
															self.check_over_configs(prediction_type=UpperCamelCase__       )

					def   UpperCAmelCase__       (     self       :   Optional[int]       ):






										'''simple docstring'''






										for time_step in [0, 500, 999]:
															for prev_timestep in [None, 5, 100, 250, 500, 750]:
																				if prev_timestep is not None and prev_timestep >= time_step:
																									continue

																				self.check_over_forward(time_step=UpperCamelCase__							,					prev_timestep=UpperCamelCase__       )

					def   UpperCAmelCase__       (     self       :   Union[str, Any]       ):






										'''simple docstring'''






										lowercase_  							=			self.scheduler_classes[0]
										lowercase_  							=			self.get_scheduler_config(variance_type="""fixed_small_log"""       )
										lowercase_  							=			scheduler_class(**UpperCamelCase__       )

										assert torch.sum(torch.abs(scheduler._get_variance(0       ) - 1.0000e-10       )       ) < 1e-5
										assert torch.sum(torch.abs(scheduler._get_variance(487       ) - 0.0_549_625       )       ) < 1e-5
										assert torch.sum(torch.abs(scheduler._get_variance(999       ) - 0.9_994_987       )       ) < 1e-5

					def   UpperCAmelCase__       (     self       :   str       ):






										'''simple docstring'''






										lowercase_  							=			self.scheduler_classes[0]
										lowercase_  							=			self.get_scheduler_config(variance_type="""learned_range"""       )
										lowercase_  							=			scheduler_class(**UpperCamelCase__       )

										lowercase_  							=			0.5

										assert scheduler._get_variance(1							,					predicted_variance=UpperCamelCase__       ) - -10.1_712_790 < 1e-5
										assert scheduler._get_variance(487							,					predicted_variance=UpperCamelCase__       ) - -5.7_998_052 < 1e-5
										assert scheduler._get_variance(999							,					predicted_variance=UpperCamelCase__       ) - -0.0_010_011 < 1e-5

					def   UpperCAmelCase__       (     self       :   Optional[Any]       ):






										'''simple docstring'''






										lowercase_  							=			self.scheduler_classes[0]
										lowercase_  							=			self.get_scheduler_config()
										lowercase_  							=			scheduler_class(**UpperCamelCase__       )

										lowercase_  							=			scheduler.timesteps

										lowercase_  							=			self.dummy_model()
										lowercase_  							=			self.dummy_sample_deter
										lowercase_  							=			torch.manual_seed(0       )

										for i, t in enumerate(UpperCamelCase__       ):
															# 1. predict noise residual
															lowercase_  							=			model(UpperCamelCase__							,					UpperCamelCase__       )

															# 2. predict previous mean of sample x_t-1
															lowercase_  							=			scheduler.step(UpperCamelCase__							,					UpperCamelCase__							,					UpperCamelCase__							,					generator=UpperCamelCase__       ).prev_sample

															lowercase_  							=			pred_prev_sample

										lowercase_  							=			torch.sum(torch.abs(UpperCamelCase__       )       )
										lowercase_  							=			torch.mean(torch.abs(UpperCamelCase__       )       )

										assert abs(result_sum.item() - 252.2_682_495       ) < 1e-2
										assert abs(result_mean.item() - 0.3_284_743       ) < 1e-3

					def   UpperCAmelCase__       (     self       :   int       ):






										'''simple docstring'''






										lowercase_  							=			self.scheduler_classes[0]
										lowercase_  							=			self.get_scheduler_config()
										lowercase_  							=			scheduler_class(**UpperCamelCase__       )

										scheduler.set_timesteps(25       )

										lowercase_  							=			scheduler.timesteps

										lowercase_  							=			self.dummy_model()
										lowercase_  							=			self.dummy_sample_deter
										lowercase_  							=			torch.manual_seed(0       )

										for i, t in enumerate(UpperCamelCase__       ):
															# 1. predict noise residual
															lowercase_  							=			model(UpperCamelCase__							,					UpperCamelCase__       )

															if i + 1 == timesteps.shape[0]:
																				lowercase_  							=			None
															else:
																				lowercase_  							=			timesteps[i + 1]

															# 2. predict previous mean of sample x_t-1
															lowercase_  							=			scheduler.step(
															    UpperCamelCase__							,					UpperCamelCase__							,					UpperCamelCase__							,					prev_timestep=UpperCamelCase__							,					generator=UpperCamelCase__       ).prev_sample

															lowercase_  							=			pred_prev_sample

										lowercase_  							=			torch.sum(torch.abs(UpperCamelCase__       )       )
										lowercase_  							=			torch.mean(torch.abs(UpperCamelCase__       )       )

										assert abs(result_sum.item() - 258.2_044_983       ) < 1e-2
										assert abs(result_mean.item() - 0.3_362_038       ) < 1e-3

					def   UpperCAmelCase__       (     self       :   List[str]       ):






										'''simple docstring'''






										pass







					def   UpperCAmelCase__       (     self       :   int       ):






										'''simple docstring'''






										pass


