import os
import sys
import unittest


A     :  str					     =       os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
A     :  Tuple					     =       os.path.join(git_repo_path, "src", "diffusers")


class   lowerCamelCase					(unittest.TestCase					):
  """simple docstring"""







  def    __A     (							self :       Optional[Any]   )  ->	Union[str, Any]:
        SCREAMING_SNAKE_CASE_          =  find_backend("    if not is_torch_available():"   )
        self.assertEqual(__magic_name__  ,     "torch"   )

        # backend_with_underscore = find_backend("    if not is_tensorflow_text_available():")
        # self.assertEqual(backend_with_underscore, "tensorflow_text")

        SCREAMING_SNAKE_CASE_          =  find_backend("    if not (is_torch_available() and is_transformers_available()):"   )
        self.assertEqual(__magic_name__  ,     "torch_and_transformers"   )

        # double_backend_with_underscore = find_backend(
        #    "    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"
        # )
        # self.assertEqual(double_backend_with_underscore, "sentencepiece_and_tensorflow_text")

        SCREAMING_SNAKE_CASE_          =  find_backend(
            "    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):"   )
        self.assertEqual(__magic_name__  ,     "torch_and_transformers_and_onnx"   )







  def    __A     (							self :       Dict   )  ->	str:
        SCREAMING_SNAKE_CASE_          =  read_init()
        # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
        self.assertIn("torch"  ,     __magic_name__   )
        self.assertIn("torch_and_transformers"  ,     __magic_name__   )
        self.assertIn("flax_and_transformers"  ,     __magic_name__   )
        self.assertIn("torch_and_transformers_and_onnx"  ,     __magic_name__   )

        # Likewise, we can't assert on the exact content of a key
        self.assertIn("UNet2DModel"  ,     objects["torch"]   )
        self.assertIn("FlaxUNet2DConditionModel"  ,     objects["flax"]   )
        self.assertIn("StableDiffusionPipeline"  ,     objects["torch_and_transformers"]   )
        self.assertIn("FlaxStableDiffusionPipeline"  ,     objects["flax_and_transformers"]   )
        self.assertIn("LMSDiscreteScheduler"  ,     objects["torch_and_scipy"]   )
        self.assertIn("OnnxStableDiffusionPipeline"  ,     objects["torch_and_transformers_and_onnx"]   )







  def    __A     (							self :       int   )  ->	Any:
        SCREAMING_SNAKE_CASE_          =  create_dummy_object("CONSTANT"  ,     "'torch'"   )
        self.assertEqual(__magic_name__  ,     "\nCONSTANT = None\n"   )

        SCREAMING_SNAKE_CASE_          =  create_dummy_object("function"  ,     "'torch'"   )
        self.assertEqual(
            __magic_name__  ,     "\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"   )

        SCREAMING_SNAKE_CASE_          =  "\nclass FakeClass(metaclass=DummyObject):\n    _backends = 'torch'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, 'torch')\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, 'torch')\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, 'torch')\n"
        SCREAMING_SNAKE_CASE_          =  create_dummy_object("FakeClass"  ,     "'torch'"   )
        self.assertEqual(__magic_name__  ,     __magic_name__   )







  def    __A     (							self :       Any   )  ->	List[Any]:
        SCREAMING_SNAKE_CASE_          =  "# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, [\"torch\"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = [\"torch\"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, [\"torch\"])\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, [\"torch\"])\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, [\"torch\"])\n"
        SCREAMING_SNAKE_CASE_          =  create_dummy_files({"torch": ["CONSTANT", "function", "FakeClass"]}   )
        self.assertEqual(dummy_files["torch"]  ,     __magic_name__   )



# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

A     :  Dict					     =       TypeVar("T")


class   lowerCamelCase					(Generic[T]					):
  """simple docstring"""







  def __init__(							self :       Optional[int]  ,     __magic_name__ :       bool = True   )  ->	None:
        SCREAMING_SNAKE_CASE_          =  {}  # dictionary of lists
        SCREAMING_SNAKE_CASE_          =  directed







  def    __A     (							self :       Dict  ,     __magic_name__ :       T  ,     __magic_name__ :       T   )  ->	GraphAdjacencyList[T]:

        if not self.directed:  # For undirected graphs
              # if both source vertex and destination vertex are both present in the
              # adjacency list, add destination vertex to source vertex list of adjacent
              # vertices and add source vertex to destination vertex list of adjacent
              # vertices.
              if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                    self.adj_list[source_vertex].append(__magic_name__   )
                    self.adj_list[destination_vertex].append(__magic_name__   )
              # if only source vertex is present in adjacency list, add destination vertex
              # to source vertex list of adjacent vertices, then create a new vertex with
              # destination vertex as key and assign a list containing the source vertex
              # as it's first adjacent vertex.
              elif source_vertex in self.adj_list:
                    self.adj_list[source_vertex].append(__magic_name__   )
                    SCREAMING_SNAKE_CASE_          =  [source_vertex]
              # if only destination vertex is present in adjacency list, add source vertex
              # to destination vertex list of adjacent vertices, then create a new vertex
              # with source vertex as key and assign a list containing the source vertex
              # as it's first adjacent vertex.
              elif destination_vertex in self.adj_list:
                    self.adj_list[destination_vertex].append(__magic_name__   )
                    SCREAMING_SNAKE_CASE_          =  [destination_vertex]
              # if both source vertex and destination vertex are not present in adjacency
              # list, create a new vertex with source vertex as key and assign a list
              # containing the destination vertex as it's first adjacent vertex also
              # create a new vertex with destination vertex as key and assign a list
              # containing the source vertex as it's first adjacent vertex.
              else:
                    SCREAMING_SNAKE_CASE_          =  [destination_vertex]
                    SCREAMING_SNAKE_CASE_          =  [source_vertex]
        else:  # For directed graphs
              # if both source vertex and destination vertex are present in adjacency
              # list, add destination vertex to source vertex list of adjacent vertices.
              if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                    self.adj_list[source_vertex].append(__magic_name__   )
              # if only source vertex is present in adjacency list, add destination
              # vertex to source vertex list of adjacent vertices and create a new vertex
              # with destination vertex as key, which has no adjacent vertex
              elif source_vertex in self.adj_list:
                    self.adj_list[source_vertex].append(__magic_name__   )
                    SCREAMING_SNAKE_CASE_          =  []
              # if only destination vertex is present in adjacency list, create a new
              # vertex with source vertex as key and assign a list containing destination
              # vertex as first adjacent vertex
              elif destination_vertex in self.adj_list:
                    SCREAMING_SNAKE_CASE_          =  [destination_vertex]
              # if both source vertex and destination vertex are not present in adjacency
              # list, create a new vertex with source vertex as key and a list containing
              # destination vertex as it's first adjacent vertex. Then create a new vertex
              # with destination vertex as key, which has no adjacent vertex
              else:
                    SCREAMING_SNAKE_CASE_          =  [destination_vertex]
                    SCREAMING_SNAKE_CASE_          =  []

        return self







  def __repr__(							self :       int   )  ->	str:
        return pformat(self.adj_list   )


