



'''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


lowercase											=      {}
for task, _ in pipeline_test_mapping.items():
  lowercase											=      {'''pt''': None, '''tf''': None}


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






def 			UpperCAmelCase_							(		lowercase__							):


     '''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 			UpperCAmelCase_							(		lowercase__							,						lowercase__							):


     '''simple docstring'''







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

     a_									=pipeline_test_mapping[task]["test"]
     a_									=None

     if framework == "pt":
          a_									=getattr(lowercase__							,						"model_mapping"							,						lowercase__							)
     elif framework == "tf":
          a_									=getattr(lowercase__							,						"tf_model_mapping"							,						lowercase__							)

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

     # cache the results
     a_									=mapping
     return mapping






def 			UpperCAmelCase_							(		lowercase__							,						lowercase__							):


     '''simple docstring'''







     a_									=get_framework(lowercase__							)
     if framework is None:
          return None
     a_									=get_mapping_for_task(lowercase__							,						lowercase__							)
     if mapping is None:
          return None

     a_									=list({model_class.config_class for model_class in test_class.all_model_classes}							)
     if len(lowercase__							) != 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.
     a_									=mapping.get(config_classes[0]							,						lowercase__							)
     if isinstance(lowercase__							,						(tuple, list)							):
          a_									=sorted(lowercase__							,						key=lambda lowercase__							: x.__name__							)

     return model_class






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







     a_									=[(task, get_model_for_pipeline_test(lowercase__							,						lowercase__							)) for task in pipeline_test_mapping]
     a_									=sorted([(task, model) for task, model in mapping if model is not None]							,						key=lambda lowercase__							: x[0]							)

     return dict(lowercase__							)






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







     a_									=get_framework(lowercase__							)
     if framework == "pt":
          a_									="torch"
     a_									="{}"

     a_									=get_pipeline_model_mapping(lowercase__							)
     if len(lowercase__							) == 0:
          return ""

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

     return text






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







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






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







     a_									=[x for x in get_test_classes(lowercase__							) if is_valid_test_class(lowercase__							)]

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

     return target_test_class






def 			UpperCAmelCase_							(		lowercase__							,						lowercase__							,						lowercase__							):


     '''simple docstring'''







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

     return end_idx






def 			UpperCAmelCase_							(		lowercase__							,						lowercase__=False							):


     '''simple docstring'''







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

     a_									=get_pipeline_model_mapping_string(lowercase__							)
     if len(lowercase__							) == 0:
          return "", -1
     a_									=line_to_add + "\n"

     # The code defined the class `test_class`
     a_		,    a_									=inspect.getsourcelines(lowercase__							)
     # `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(lowercase__							):
          if line.lstrip().startswith("class "							):
               a_									=class_lines[idx:]
               class_start_line_no += idx
               break
     a_									=class_start_line_no + len(lowercase__							) - 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`.
     a_									=None
     # The indent level of the line at `class_lines[start_idx]` (if defined)
     a_									=0
     # To record if `pipeline_model_mapping` is found in `test_class`.
     a_									=None
     for idx, line in enumerate(lowercase__							):
          if line.strip().startswith("all_model_classes = "							):
               a_									=len(lowercase__							) - len(line.lstrip()							)
               a_									=idx
          elif line.strip().startswith("all_generative_model_classes = "							):
               a_									=len(lowercase__							) - len(line.lstrip()							)
               a_									=idx
          elif line.strip().startswith("pipeline_model_mapping = "							):
               a_									=len(lowercase__							) - len(line.lstrip()							)
               a_									=idx
               a_									=line
               break

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

     # 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
     a_									=re.compile(r"\s(is_\S+?_available\(\))\s"							)
     for line in class_lines[start_idx : end_idx + 1]:
          a_									=r.search(lowercase__							)
          if backend_condition is not None:
               # replace the leading and trailing whitespaces to the space character " ".
               a_									=" " + backend_condition[0][1:-1] + " "
               a_									=r.sub(lowercase__							,						lowercase__							)
               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`.
          a_									=end_idx
     else:
          # `pipeline_model_mapping` is defined. The target index is set to be one **BEFORE** its start index.
          a_									=start_idx - 1
          # mark the lines of the currently existing `pipeline_model_mapping` to be removed.
          for idx in range(lowercase__							,						end_idx + 1							):
               # These lines are going to be removed before writing to the test file.
               a_									=None  # noqa

    # Make sure the test class is a subclass of `PipelineTesterMixin`.
     a_									=[x.__name__ for x in test_class.__bases__]
     if "PipelineTesterMixin" not in parent_classes:
          # Put `PipelineTesterMixin` just before `unittest.TestCase`
          a_									=[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"							)
          a_									=", ".join(_parent_classes							)
          for idx, line in enumerate(lowercase__							):
               # 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							):
                         a_									=None  # noqa
                    break
        # Add the new, one-line, class declaration for `test_class`
          a_									=F"""class {test_class.__name__}({parent_classes}):\n"""

     # Add indentation
     a_									=" " * indent_level + line_to_add
     # Insert `pipeline_model_mapping` to `class_lines`.
     # (The line at `target_idx` should be kept by definition!)
     a_									=class_lines[: target_idx + 1] + [line_to_add] + class_lines[target_idx + 1 :]
     # Remove the lines that are marked to be removed
     a_									=[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)
     a_									=inspect.getsourcelines(inspect.getmodule(lowercase__							)							)[0]
     # Be careful with the 1-off between line numbers and array indices
     a_									=module_lines[: class_start_line_no - 1] + class_lines + module_lines[class_end_line_no:]
     a_									="".join(lowercase__							)

     a_									=inspect.getsourcefile(lowercase__							)
     with open(lowercase__							,						"w"							,						encoding="UTF-8"							,						newline="\n"							) as fp:
          fp.write(lowercase__							)

     return line_to_add






def 			UpperCAmelCase_							(		lowercase__							,						lowercase__=False							):


     '''simple docstring'''







     a_									=find_test_class(lowercase__							)
     if test_class:
          add_pipeline_model_mapping(lowercase__							,						overwrite=lowercase__							)


if __name__ == "__main__":
  lowercase											=      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`.''',
  )
  lowercase											=      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.''')

  lowercase											=      []
  if args.test_file:
    lowercase											=      [args.test_file]
  else:
    lowercase											=      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'''


import argparse
import os

import torch
from emmental.modules import ThresholdBinarizer, TopKBinarizer






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







     a_									=args.serialization_dir
     a_									=args.pruning_method
     a_									=args.threshold

     a_									=torch.load(os.path.join(lowercase__							,						"pytorch_model.bin"							)							,						map_location="cpu"							)

     a_									=0  # Number of remaining (not pruned) params in the encoder
     a_									=0  # Number of params in the encoder

     print("name".ljust(6_0							,						" "							)							,						"Remaining Weights %"							,						"Remaining Weight"							)
     for name, param in st.items():
          if "encoder" not in name:
               continue

          if "mask_scores" in name:
               if pruning_method == "topK":
                    a_									=TopKBinarizer.apply(lowercase__							,						lowercase__							).sum().item()
               elif pruning_method == "sigmoied_threshold":
                    a_									=ThresholdBinarizer.apply(lowercase__							,						lowercase__							,						lowercase__							).sum().item()
               elif pruning_method == "l0":
                    a_		,    a_									=-0.1, 1.1
                    a_									=torch.sigmoid(lowercase__							)
                    a_									=s * (r - l) + l
                    a_									=s_bar.clamp(min=0.0							,						max=1.0							)
                    a_									=(mask > 0.0).sum().item()
               else:
                    raise ValueError("Unknown pruning method"							)
               remaining_count += mask_ones
               print(name.ljust(6_0							,						" "							)							,						str(round(1_0_0 * mask_ones / param.numel()							,						3							)							).ljust(2_0							,						" "							)							,						str(lowercase__							)							)
          else:
               encoder_count += param.numel()
               if "bias" in name or "LayerNorm" in name:
                    remaining_count += param.numel()

     print(""							)
     print("Remaining Weights (global) %: "							,						1_0_0 * remaining_count / encoder_count							)


if __name__ == "__main__":
  lowercase											=      argparse.ArgumentParser()

  parser.add_argument(
      '''--pruning_method''',
      choices=['''l0''', '''topK''', '''sigmoied_threshold'''],
      type=str,
      required=True,
      help=(
          '''Pruning Method (l0 = L0 regularization, topK = Movement pruning, sigmoied_threshold = Soft movement'''
          ''' pruning)'''
      ),
  )
  parser.add_argument(
      '''--threshold''',
      type=float,
      required=False,
      help=(
          '''For `topK`, it is the level of remaining weights (in %) in the fine-pruned model.'''
          '''For `sigmoied_threshold`, it is the threshold \tau against which the (sigmoied) scores are compared.'''
          '''Not needed for `l0`'''
      ),
  )
  parser.add_argument(
      '''--serialization_dir''',
      type=str,
      required=True,
      help='''Folder containing the model that was previously fine-pruned''',
  )

  lowercase											=      parser.parse_args()

  main(args)


