



import doctest
from collections import deque

import numpy as np



class     _UpperCAmelCase			:




     def __init__(				self):
         A__		 =					[2, 1, 2, -1]
         A__		 =					[1, 2, 3, 4]




     def 		snake_case_		(				self):
         A__		 =					len(self.first_signal)
         A__		 =					len(self.second_signal)

         A__		 =					max(a__ ,						a__)

         # create a zero matrix of max_length x max_length
         A__		 =					[[0] * max_length for i in range(a__)]

         # fills the smaller signal with zeros to make both signals of same length
         if length_first_signal < length_second_signal:
             self.first_signal += [0] * (max_length - length_first_signal)
         elif length_first_signal > length_second_signal:
             self.second_signal += [0] * (max_length - length_second_signal)
         for i in range(a__):
             A__		 =					deque(self.second_signal)
             rotated_signal.rotate(a__)
             for j, item in enumerate(a__):
                 matrix[i][j] += item

        # multiply the matrix with the first signal
         A__		 =					np.matmul(np.transpose(a__) ,						np.transpose(self.first_signal))

         # rounding-off to two decimal places
         return [round(a__ ,						2) for i in final_signal]


if __name__ == "__main__":
   doctest.testmod()





# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_lowercase						  =		{
    "configuration_cpmant": ["CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP", "CpmAntConfig"],
    "tokenization_cpmant": ["CpmAntTokenizer"],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowercase						  =		[
       "CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "CpmAntForCausalLM",
       "CpmAntModel",
       "CpmAntPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
   from .tokenization_cpmant import CpmAntTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_cpmant import (
          CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
          CpmAntForCausalLM,
          CpmAntModel,
          CpmAntPreTrainedModel,
      )


else:
   import sys

   _lowercase						  =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
