



import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List

from ..utils import logging
from . import BaseTransformersCLICommand


try:
	from cookiecutter.main import cookiecutter

	_lowerCAmelCase	:   int    =   True
except ImportError:
	_lowerCAmelCase	:   Any    =   False

_lowerCAmelCase	:   Dict    =   logging.get_logger(__name__)  # pylint: disable=invalid-name







def     UpperCAmelCase_		(					snake_case__					)	->     Optional[Any]:



				"""simple docstring"""





				return AddNewModelCommand(args.testing    ,			args.testing_file    ,			path=args.path					)


class 	__snake_case   ( SCREAMING_SNAKE_CASE ):
		@staticmethod
		def 						SCREAMING_SNAKE_CASE_					(							a_						):







						"""simple docstring"""
						lowerCAmelCase__		  =  parser.add_parser('add-new-model'						)
						add_new_model_parser.add_argument('--testing'    ,action='store_true'    ,help='If in testing mode.'						)
						add_new_model_parser.add_argument('--testing_file'    ,type=a_    ,help='Configuration file on which to run.'						)
						add_new_model_parser.add_argument(
						    '--path'    ,type=a_    ,help='Path to cookiecutter. Should only be used for testing purposes.'						)
						add_new_model_parser.set_defaults(func=a_						)
		def __init__(							self    ,a_    ,a_    ,a_=None    ,*a_						):







						"""simple docstring"""
						lowerCAmelCase__		  =  testing
						lowerCAmelCase__		  =  testing_file
						lowerCAmelCase__		  =  path



		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						warnings.warn(
						    'The command `transformers-cli add-new-model` is deprecated and will be removed in v5 of Transformers. '
						    'It is not actively maintained anymore, so might give a result that won\'t pass all tests and quality '
						    'checks, you should use `transformers-cli add-new-model-like` instead.'						)
						if not _has_cookiecutter:
										raise ImportError(
										    'Model creation dependencies are required to use the `add_new_model` command. Install them by running '
										    'the following at the root of your `transformers` clone:\n\n\t$ pip install -e .[modelcreation]\n'						)
						# Ensure that there is no other `cookiecutter-template-xxx` directory in the current working directory
						lowerCAmelCase__		  =  [directory for directory in os.listdir() if 'cookiecutter-template-' == directory[:22]]
						if len(a_						) > 0:
										raise ValueError(
										    'Several directories starting with `cookiecutter-template-` in current working directory. '
										    'Please clean your directory by removing all folders starting with `cookiecutter-template-` or '
										    'change your working directory.'						)

						lowerCAmelCase__		  =  (
						    Path(a_						).parent.parent.parent.parent if self._path is None else Path(self._path						).parent.parent
						)
						lowerCAmelCase__		  =  path_to_transformer_root / 'templates' / 'adding_a_new_model'

						# Execute cookiecutter
						if not self._testing:
										cookiecutter(str(a_						)						)
						else:
										with open(self._testing_file    ,'r'						) as configuration_file:
														lowerCAmelCase__		  =  json.load(a_						)

										cookiecutter(
										    str(path_to_cookiecutter if self._path is None else self._path						)    ,no_input=a_    ,extra_context=a_    ,)

						lowerCAmelCase__		  =  [directory for directory in os.listdir() if 'cookiecutter-template-' in directory[:22]][0]

						# Retrieve configuration
						with open(directory + '/configuration.json'    ,'r'						) as configuration_file:
										lowerCAmelCase__		  =  json.load(a_						)

						lowerCAmelCase__		  =  configuration['lowercase_modelname']
						lowerCAmelCase__		  =  configuration['generate_tensorflow_pytorch_and_flax']
						os.remove(f'{directory}/configuration.json'						)

						lowerCAmelCase__		  =  'PyTorch' in generate_tensorflow_pytorch_and_flax
						lowerCAmelCase__		  =  'TensorFlow' in generate_tensorflow_pytorch_and_flax
						lowerCAmelCase__		  =  'Flax' in generate_tensorflow_pytorch_and_flax

						lowerCAmelCase__		  =  f'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
						os.makedirs(a_    ,exist_ok=a_						)
						os.makedirs(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}'    ,exist_ok=a_						)

						# Tests require submodules as they have parent imports
						with open(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/__init__.py'    ,'w'						):
										pass

						shutil.move(
						    f'{directory}/__init__.py'    ,f'{model_dir}/__init__.py'    ,)
						shutil.move(
						    f'{directory}/configuration_{lowercase_model_name}.py'    ,f'{model_dir}/configuration_{lowercase_model_name}.py'    ,)

						def remove_copy_lines(a_						):
										with open(a_    ,'r'						) as f:
														lowerCAmelCase__		  =  f.readlines()
										with open(a_    ,'w'						) as f:
														for line in lines:
																		if "# Copied from transformers." not in line:
																						f.write(a_						)

						if output_pytorch:
										if not self._testing:
														remove_copy_lines(f'{directory}/modeling_{lowercase_model_name}.py'						)

										shutil.move(
										    f'{directory}/modeling_{lowercase_model_name}.py'    ,f'{model_dir}/modeling_{lowercase_model_name}.py'    ,)

										shutil.move(
										    f'{directory}/test_modeling_{lowercase_model_name}.py'    ,f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_{lowercase_model_name}.py'    ,)
						else:
										os.remove(f'{directory}/modeling_{lowercase_model_name}.py'						)
										os.remove(f'{directory}/test_modeling_{lowercase_model_name}.py'						)

						if output_tensorflow:
										if not self._testing:
														remove_copy_lines(f'{directory}/modeling_tf_{lowercase_model_name}.py'						)

										shutil.move(
										    f'{directory}/modeling_tf_{lowercase_model_name}.py'    ,f'{model_dir}/modeling_tf_{lowercase_model_name}.py'    ,)

										shutil.move(
										    f'{directory}/test_modeling_tf_{lowercase_model_name}.py'    ,f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_tf_{lowercase_model_name}.py'    ,)
						else:
										os.remove(f'{directory}/modeling_tf_{lowercase_model_name}.py'						)
										os.remove(f'{directory}/test_modeling_tf_{lowercase_model_name}.py'						)

						if output_flax:
										if not self._testing:
														remove_copy_lines(f'{directory}/modeling_flax_{lowercase_model_name}.py'						)

										shutil.move(
										    f'{directory}/modeling_flax_{lowercase_model_name}.py'    ,f'{model_dir}/modeling_flax_{lowercase_model_name}.py'    ,)

										shutil.move(
										    f'{directory}/test_modeling_flax_{lowercase_model_name}.py'    ,f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_flax_{lowercase_model_name}.py'    ,)
						else:
										os.remove(f'{directory}/modeling_flax_{lowercase_model_name}.py'						)
										os.remove(f'{directory}/test_modeling_flax_{lowercase_model_name}.py'						)

						shutil.move(
						    f'{directory}/{lowercase_model_name}.md'    ,f'{path_to_transformer_root}/docs/source/en/model_doc/{lowercase_model_name}.md'    ,)

						shutil.move(
						    f'{directory}/tokenization_{lowercase_model_name}.py'    ,f'{model_dir}/tokenization_{lowercase_model_name}.py'    ,)

						shutil.move(
						    f'{directory}/tokenization_fast_{lowercase_model_name}.py'    ,f'{model_dir}/tokenization_{lowercase_model_name}_fast.py'    ,)

						from os import fdopen, remove
						from shutil import copymode, move
						from tempfile import mkstemp

						def replace(a_    ,a_    ,a_						):
										# Create temp file
										lowerCAmelCase__  ,   lowerCAmelCase__		  =  mkstemp()
										lowerCAmelCase__		  =  False
										with fdopen(a_    ,'w'						) as new_file:
														with open(a_						) as old_file:
																		for line in old_file:
																						new_file.write(a_						)
																						if line_to_copy_below in line:
																										lowerCAmelCase__		  =  True
																										for line_to_copy in lines_to_copy:
																														new_file.write(a_						)

										if not line_found:
														raise ValueError(f'Line {line_to_copy_below} was not found in file.'						)

										# Copy the file permissions from the old file to the new file
										copymode(a_    ,a_						)
										# Remove original file
										remove(a_						)
										# Move new file
										move(a_    ,a_						)

						def skip_units(a_						):
										return (
										    ("generating PyTorch" in line and not output_pytorch)
										    or ("generating TensorFlow" in line and not output_tensorflow)
										    or ("generating Flax" in line and not output_flax)
										)

						def replace_in_files(a_						):
										with open(a_						) as datafile:
														lowerCAmelCase__		  =  []
														lowerCAmelCase__		  =  False
														lowerCAmelCase__		  =  False
														for line in datafile:
																		if "# To replace in: " in line and "##" not in line:
																						lowerCAmelCase__		  =  line.split('"'						)[1]
																						lowerCAmelCase__		  =  skip_units(a_						)
																		elif "# Below: " in line and "##" not in line:
																						lowerCAmelCase__		  =  line.split('"'						)[1]
																						lowerCAmelCase__		  =  skip_units(a_						)
																		elif "# End." in line and "##" not in line:
																						if not skip_file and not skip_snippet:
																										replace(a_    ,a_    ,a_						)

																						lowerCAmelCase__		  =  []
																		elif "# Replace with" in line and "##" not in line:
																						lowerCAmelCase__		  =  []
																		elif "##" not in line:
																						lines_to_copy.append(a_						)

										remove(a_						)

						replace_in_files(f'{directory}/to_replace_{lowercase_model_name}.py'						)
						os.rmdir(a_						)





import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device


_lowerCAmelCase	:   Any    =   False


class 	__snake_case   ( unittest.TestCase ):
		pass



@nightly
@require_torch_gpu
class 	__snake_case   ( unittest.TestCase ):
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						# clean up the VRAM after each test
						super().tearDown()
						gc.collect()
						torch.cuda.empty_cache()
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  VersatileDiffusionPipeline.from_pretrained('shi-labs/versatile-diffusion'    ,torch_dtype=torch.floataa						)
						pipe.to(a_						)
						pipe.set_progress_bar_config(disable=a_						)

						lowerCAmelCase__		  =  load_image(
						    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'						)

						lowerCAmelCase__		  =  torch.manual_seed(0						)
						lowerCAmelCase__		  =  pipe.dual_guided(
						    prompt='first prompt'    ,image=a_    ,text_to_image_strength=0.75    ,generator=a_    ,guidance_scale=7.5    ,num_inference_steps=2    ,output_type='numpy'    ,).images

						with tempfile.TemporaryDirectory() as tmpdirname:
										pipe.save_pretrained(a_						)
										lowerCAmelCase__		  =  VersatileDiffusionPipeline.from_pretrained(a_    ,torch_dtype=torch.floataa						)
						pipe.to(a_						)
						pipe.set_progress_bar_config(disable=a_						)

						lowerCAmelCase__		  =  generator.manual_seed(0						)
						lowerCAmelCase__		  =  pipe.dual_guided(
						    prompt='first prompt'    ,image=a_    ,text_to_image_strength=0.75    ,generator=a_    ,guidance_scale=7.5    ,num_inference_steps=2    ,output_type='numpy'    ,).images

						assert np.abs(image - new_image						).sum() < 1e-5, "Models don't have the same forward pass"



		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  VersatileDiffusionPipeline.from_pretrained('shi-labs/versatile-diffusion'    ,torch_dtype=torch.floataa						)
						pipe.to(a_						)
						pipe.set_progress_bar_config(disable=a_						)

						lowerCAmelCase__		  =  'cyberpunk 2077'
						lowerCAmelCase__		  =  load_image(
						    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'						)
						lowerCAmelCase__		  =  torch.manual_seed(0						)
						lowerCAmelCase__		  =  pipe.dual_guided(
						    prompt=a_    ,image=a_    ,text_to_image_strength=0.75    ,generator=a_    ,guidance_scale=7.5    ,num_inference_steps=50    ,output_type='numpy'    ,).images

						lowerCAmelCase__		  =  image[0, 253:256, 253:256, -1]

						assert image.shape == (1, 512, 512, 3)
						lowerCAmelCase__		  =  np.array([0.1448, 0.1619, 0.1741, 0.1086, 0.1147, 0.1128, 0.1199, 0.1165, 0.1001]						)

						assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1

						lowerCAmelCase__		  =  'A painting of a squirrel eating a burger '
						lowerCAmelCase__		  =  torch.manual_seed(0						)
						lowerCAmelCase__		  =  pipe.text_to_image(
						    prompt=a_    ,generator=a_    ,guidance_scale=7.5    ,num_inference_steps=50    ,output_type='numpy'						).images

						lowerCAmelCase__		  =  image[0, 253:256, 253:256, -1]

						assert image.shape == (1, 512, 512, 3)
						lowerCAmelCase__		  =  np.array([0.3367, 0.3169, 0.2656, 0.3870, 0.4790, 0.3796, 0.4009, 0.4878, 0.4778]						)

						assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1

						lowerCAmelCase__		  =  pipe.image_variation(a_    ,generator=a_    ,output_type='numpy'						).images

						lowerCAmelCase__		  =  image[0, 253:256, 253:256, -1]

						assert image.shape == (1, 512, 512, 3)
						lowerCAmelCase__		  =  np.array([0.3076, 0.3123, 0.3284, 0.3782, 0.3770, 0.3894, 0.4297, 0.4331, 0.4456]						)

						assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1
