

'''simple docstring'''

import argparse
import glob
import inspect
import os
import re
import unittest

from get_test_info import get_test_classes

from tests.test_pipeline_mixin import pipeline_test_mapping


a       :      int  	=			{}
for task, _ in pipeline_test_mapping.items():
    a       :      List[Any]  	=			{"pt": None, "tf": None}


# DO **NOT** add item to this set (unless the reason is approved)
a       :      str  	=			{
    "tests/models/esm/test_modeling_esmfold.py",  # The pipeline test mapping is added to `test_modeling_esm.py`
}





def 				lowercase (					__magic_name__							):



     '''simple docstring'''







     if "ModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
          return "pt"
     elif "TFModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
          return "tf"
     elif "FlaxModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
          return "flax"
     else:
          return None





def 				lowercase (					__magic_name__			,   __magic_name__							):



     '''simple docstring'''







     if PIPELINE_TEST_MAPPING[task].get(snake_case__			,   snake_case__							) is not None:
          return PIPELINE_TEST_MAPPING[task][framework]

     UpperCAmelCase		:							List[Any]        =       pipeline_test_mapping[task]["test"]
     UpperCAmelCase		:							Tuple        =       None

     if framework == "pt":
          UpperCAmelCase		:							Dict        =       getattr(snake_case__			,   "model_mapping"			,   snake_case__							)
     elif framework == "tf":
          UpperCAmelCase		:							Tuple        =       getattr(snake_case__			,   "tf_model_mapping"			,   snake_case__							)

     if mapping is not None:
          UpperCAmelCase		:							int        =       dict(mapping.items()							)

     # cache the results
     UpperCAmelCase		:							int        =       mapping
     return mapping





def 				lowercase (					__magic_name__			,   __magic_name__							):



     '''simple docstring'''







     UpperCAmelCase		:							Any        =       get_framework(snake_case__							)
     if framework is None:
          return None
     UpperCAmelCase		:							Optional[Any]        =       get_mapping_for_task(snake_case__			,   snake_case__							)
     if mapping is None:
          return None

     UpperCAmelCase		:							List[str]        =       list({model_class.config_class for model_class in test_class.all_model_classes}							)
     if len(snake_case__							) != 1:
          raise ValueError("There should be exactly one configuration class from `test_class.all_model_classes`."							)

     # This could be a list/tuple of model classes, but it's rare.
     UpperCAmelCase		:							List[str]        =       mapping.get(config_classes[0]			,   snake_case__							)
     if isinstance(snake_case__			,   (tuple, list)							):
          UpperCAmelCase		:							List[str]        =       sorted(snake_case__			,   key=lambda __magic_name__							: x.__name__							)

     return model_class





def 				lowercase (					__magic_name__							):



     '''simple docstring'''







     UpperCAmelCase		:							Optional[Any]        =       [(task, get_model_for_pipeline_test(snake_case__			,   snake_case__							)) for task in pipeline_test_mapping]
     UpperCAmelCase		:							Dict        =       sorted([(task, model) for task, model in mapping if model is not None]			,   key=lambda __magic_name__							: x[0]							)

     return dict(snake_case__							)





def 				lowercase (					__magic_name__							):



     '''simple docstring'''







     UpperCAmelCase		:							Tuple        =       get_framework(snake_case__							)
     if framework == "pt":
          UpperCAmelCase		:							Optional[Any]        =       "torch"
     UpperCAmelCase		:							Dict        =       "{}"

     UpperCAmelCase		:							Optional[int]        =       get_pipeline_model_mapping(snake_case__							)
     if len(snake_case__							) == 0:
          return ""

     UpperCAmelCase		:							Optional[int]        =       []
     for task, model_classes in mapping.items():
          if isinstance(snake_case__			,   (tuple, list)							):
               # A list/tuple of model classes
               UpperCAmelCase		:							List[str]        =       "(" + ", ".join([x.__name__ for x in model_classes]							) + ")"
          else:
               # A single model class
               UpperCAmelCase		:							List[Any]        =       model_classes.__name__
          texts.append(F"\"{task}\": {value}"							)
     UpperCAmelCase		:							Optional[int]        =       "{" + ", ".join(snake_case__							) + "}"
     UpperCAmelCase		:							Dict        =       F"pipeline_model_mapping = {text} if is_{framework}_available() else {default_value}"

     return text





def 				lowercase (					__magic_name__							):



     '''simple docstring'''







     UpperCAmelCase		:							Union[str, Any]        =       {"ModelTesterMixin", "TFModelTesterMixin", "FlaxModelTesterMixin"}
     if not issubclass(snake_case__			,   unittest.TestCase							):
          return False
     return len(base_class_names.intersection([x.__name__ for x in test_class.__bases__]							)							) > 0





def 				lowercase (					__magic_name__							):



     '''simple docstring'''







     UpperCAmelCase		:							Optional[Any]        =       [x for x in get_test_classes(snake_case__							) if is_valid_test_class(snake_case__							)]

     UpperCAmelCase		:							Optional[int]        =       None
     for test_class in test_classes:
          # If a test class has defined `pipeline_model_mapping`, let's take it
          if getattr(snake_case__			,   "pipeline_model_mapping"			,   snake_case__							) is not None:
               UpperCAmelCase		:							Any        =       test_class
               break
    # Take the test class with the shortest name (just a heuristic)
     if target_test_class is None and len(snake_case__							) > 0:
          UpperCAmelCase		:							int        =       sorted(snake_case__			,   key=lambda __magic_name__							: (len(x.__name__							), x.__name__)							)[0]

     return target_test_class





def 				lowercase (					__magic_name__			,   __magic_name__			,   __magic_name__							):



     '''simple docstring'''







     UpperCAmelCase		:							Tuple        =       start_idx
     for idx, line in enumerate(lines[start_idx:]							):
          UpperCAmelCase		:							Union[str, Any]        =       len(snake_case__							) - len(line.lstrip()							)
          if idx == 0 or indent > indent_level or (indent == indent_level and line.strip() == ")"):
               UpperCAmelCase		:							Union[str, Any]        =       start_idx + idx
          elif idx > 0 and indent <= indent_level:
               # Outside the definition block of `pipeline_model_mapping`
               break

     return end_idx





def 				lowercase (					__magic_name__			,   __magic_name__=False							):



     '''simple docstring'''







     if getattr(snake_case__			,   "pipeline_model_mapping"			,   snake_case__							) is not None:
          if not overwrite:
               return "", -1

     UpperCAmelCase		:							Any        =       get_pipeline_model_mapping_string(snake_case__							)
     if len(snake_case__							) == 0:
          return "", -1
     UpperCAmelCase		:							Any        =       line_to_add + "\n"

     # The code defined the class `test_class`
     UpperCAmelCase ,			UpperCAmelCase		:							Union[str, Any]        =       inspect.getsourcelines(snake_case__							)
     # `inspect` gives the code for an object, including decorator(s) if any.
     # We (only) need the exact line of the class definition.
     for idx, line in enumerate(snake_case__							):
          if line.lstrip().startswith("class "							):
               UpperCAmelCase		:							List[str]        =       class_lines[idx:]
               class_start_line_no += idx
               break
     UpperCAmelCase		:							int        =       class_start_line_no + len(snake_case__							) - 1

     # The index in `class_lines` that starts the definition of `all_model_classes`, `all_generative_model_classes` or
     # `pipeline_model_mapping`. This assumes they are defined in such order, and we take the start index of the last
     # block that appears in a `test_class`.
     UpperCAmelCase		:							List[str]        =       None
     # The indent level of the line at `class_lines[start_idx]` (if defined)
     UpperCAmelCase		:							int        =       0
     # To record if `pipeline_model_mapping` is found in `test_class`.
     UpperCAmelCase		:							Optional[Any]        =       None
     for idx, line in enumerate(snake_case__							):
          if line.strip().startswith("all_model_classes = "							):
               UpperCAmelCase		:							str        =       len(snake_case__							) - len(line.lstrip()							)
               UpperCAmelCase		:							int        =       idx
          elif line.strip().startswith("all_generative_model_classes = "							):
               UpperCAmelCase		:							List[str]        =       len(snake_case__							) - len(line.lstrip()							)
               UpperCAmelCase		:							int        =       idx
          elif line.strip().startswith("pipeline_model_mapping = "							):
               UpperCAmelCase		:							Tuple        =       len(snake_case__							) - len(line.lstrip()							)
               UpperCAmelCase		:							Optional[int]        =       idx
               UpperCAmelCase		:							Optional[int]        =       line
               break

     if start_idx is None:
          return "", -1
     # Find the ending index (inclusive) of the above found block.
     UpperCAmelCase		:							int        =       find_block_ending(snake_case__			,   snake_case__			,   snake_case__							)

     # Extract `is_xxx_available()` from existing blocks: some models require specific libraries like `timm` and use
     # `is_timm_available()` instead of `is_torch_available()`.
     # Keep leading and trailing whitespaces
     UpperCAmelCase		:							Optional[int]        =       re.compile(R"\s(is_\S+?_available\(\))\s"							)
     for line in class_lines[start_idx : end_idx + 1]:
          UpperCAmelCase		:							Any        =       r.search(snake_case__							)
          if backend_condition is not None:
               # replace the leading and trailing whitespaces to the space character " ".
               UpperCAmelCase		:							Dict        =       " " + backend_condition[0][1:-1] + " "
               UpperCAmelCase		:							Optional[int]        =       r.sub(snake_case__			,   snake_case__							)
               break

     if def_line is None:
          # `pipeline_model_mapping` is not defined. The target index is set to the ending index (inclusive) of
          # `all_model_classes` or `all_generative_model_classes`.
          UpperCAmelCase		:							Union[str, Any]        =       end_idx
     else:
          # `pipeline_model_mapping` is defined. The target index is set to be one **BEFORE** its start index.
          UpperCAmelCase		:							List[Any]        =       start_idx - 1
          # mark the lines of the currently existing `pipeline_model_mapping` to be removed.
          for idx in range(snake_case__			,   end_idx + 1							):
               # These lines are going to be removed before writing to the test file.
               UpperCAmelCase		:							List[str]        =       None  # noqa

    # Make sure the test class is a subclass of `PipelineTesterMixin`.
     UpperCAmelCase		:							Any        =       [x.__name__ for x in test_class.__bases__]
     if "PipelineTesterMixin" not in parent_classes:
          # Put `PipelineTesterMixin` just before `unittest.TestCase`
          UpperCAmelCase		:							int        =       [x for x in parent_classes if x != "TestCase"] + ["PipelineTesterMixin"]
          if "TestCase" in parent_classes:
               # Here we **assume** the original string is always with `unittest.TestCase`.
               _parent_classes.append("unittest.TestCase"							)
          UpperCAmelCase		:							int        =       ", ".join(_parent_classes							)
          for idx, line in enumerate(snake_case__							):
               # Find the ending of the declaration of `test_class`
               if line.strip().endswith("):"							):
                    # mark the lines of the declaration of `test_class` to be removed
                    for _idx in range(idx + 1							):
                         UpperCAmelCase		:							int        =       None  # noqa
                    break
        # Add the new, one-line, class declaration for `test_class`
          UpperCAmelCase		:							Tuple        =       F"class {test_class.__name__}({parent_classes}):\n"

     # Add indentation
     UpperCAmelCase		:							Tuple        =       " " * indent_level + line_to_add
     # Insert `pipeline_model_mapping` to `class_lines`.
     # (The line at `target_idx` should be kept by definition!)
     UpperCAmelCase		:							Any        =       class_lines[: target_idx + 1] + [line_to_add] + class_lines[target_idx + 1 :]
     # Remove the lines that are marked to be removed
     UpperCAmelCase		:							Union[str, Any]        =       [x for x in class_lines if x is not None]

     # Move from test class to module (in order to write to the test file)
     UpperCAmelCase		:							Optional[int]        =       inspect.getsourcelines(inspect.getmodule(snake_case__							)							)[0]
     # Be careful with the 1-off between line numbers and array indices
     UpperCAmelCase		:							Optional[int]        =       module_lines[: class_start_line_no - 1] + class_lines + module_lines[class_end_line_no:]
     UpperCAmelCase		:							List[Any]        =       "".join(snake_case__							)

     UpperCAmelCase		:							Optional[int]        =       inspect.getsourcefile(snake_case__							)
     with open(snake_case__			,   "w"			,   encoding="UTF-8"			,   newline="\n"							) as fp:
          fp.write(snake_case__							)

     return line_to_add





def 				lowercase (					__magic_name__			,   __magic_name__=False							):



     '''simple docstring'''







     UpperCAmelCase		:							str        =       find_test_class(snake_case__							)
     if test_class:
          add_pipeline_model_mapping(snake_case__			,   overwrite=snake_case__							)


if __name__ == "__main__":
    a       :      Any  	=			argparse.ArgumentParser()
    parser.add_argument(
        "--test_file", type=str, help="A path to the test file, starting with the repository\'s `tests` directory."
    )
    parser.add_argument(
        "--all",
        action="store_true",
        help="If to check and modify all test files.",
    )
    parser.add_argument(
        "--overwrite",
        action="store_true",
        help="If to overwrite a test class if it has already defined `pipeline_model_mapping`.",
    )
    a       :      List[str]  	=			parser.parse_args()

    if not args.all and not args.test_file:
        raise ValueError("Please specify either `test_file` or pass `--all` to check/modify all test files.")
    elif args.all and args.test_file:
        raise ValueError("Only one of `--test_file` and `--all` could be specified.")

    a       :      Union[str, Any]  	=			[]
    if args.test_file:
        a       :      Dict  	=			[args.test_file]
    else:
        a       :      Any  	=			os.path.join("tests", "models", "**", "test_modeling_*.py")
        for test_file in glob.glob(pattern):
            # `Flax` is not concerned at this moment
            if not test_file.startswith("test_modeling_flax_"):
                test_files.append(test_file)

    for test_file in test_files:
        if test_file in TEST_FILE_TO_IGNORE:
            print(F'[SKIPPED] {test_file} is skipped as it is in `TEST_FILE_TO_IGNORE` in the file {__file__}.')
            continue
        add_pipeline_model_mapping_to_test_file(test_file, overwrite=args.overwrite)



'''simple docstring'''

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier

# Load iris file
a       :      List[Any]  	=			load_iris()
iris.keys()


print(F'Target names: \n {iris.target_names} ')
print(F'\n Features: \n {iris.feature_names}')

# Train set e Test set
a	,						a	,						a	,						a       :      List[Any]  	=			train_test_split(
    iris["data"], iris["target"], random_state=4
)

# KNN

a       :      Tuple  	=			KNeighborsClassifier(n_neighbors=1)
knn.fit(X_train, y_train)

# new array to test
a       :      Optional[int]  	=			[[1, 2, 1, 4], [2, 3, 4, 5]]

a       :      Tuple  	=			knn.predict(X_new)

print(
    F'\nNew array: \n {X_new}\n\nTarget Names Prediction: \n'
    F' {iris["target_names"][prediction]}'
)
