

import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase							:  List[str]            =						logging.get_logger(__name__)

lowerCAmelCase							:  int            =						{
    """BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json""",
    # See all AltCLIP models at https://huggingface.co/models?filter=altclip
}



class   __lowercase    (			UpperCAmelCase_     ):




			"""simple docstring"""







			_UpperCAmelCase       :							Dict      							=					'''altclip_text_model'''



			def __init__(			self  :					Any       ,						lowerCAmelCase__  :					List[Any]=25_0002       ,						lowerCAmelCase__  :					Union[str, Any]=1024       ,						lowerCAmelCase__  :					Tuple=24       ,						lowerCAmelCase__  :					List[str]=16       ,						lowerCAmelCase__  :					Tuple=4096       ,						lowerCAmelCase__  :					Tuple="gelu"       ,						lowerCAmelCase__  :					Tuple=0.1       ,						lowerCAmelCase__  :					Optional[int]=0.1       ,						lowerCAmelCase__  :					Union[str, Any]=514       ,						lowerCAmelCase__  :					Dict=1       ,						lowerCAmelCase__  :					Optional[Any]=0.02       ,						lowerCAmelCase__  :					Union[str, Any]=0.02       ,						lowerCAmelCase__  :					int=1E-05       ,						lowerCAmelCase__  :					List[Any]=1       ,						lowerCAmelCase__  :					Optional[Any]=0       ,						lowerCAmelCase__  :					Any=2       ,						lowerCAmelCase__  :					Optional[int]="absolute"       ,						lowerCAmelCase__  :					List[str]=True       ,						lowerCAmelCase__  :					List[str]=768       ,						**lowerCAmelCase__  :					Any       ,						):
									super().__init__(pad_token_id=lowerCAmelCase__       ,						bos_token_id=lowerCAmelCase__       ,						eos_token_id=lowerCAmelCase__       ,						**lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_:			int  		=	vocab_size
									SCREAMING_SNAKE_CASE_:			List[str]  		=	hidden_size
									SCREAMING_SNAKE_CASE_:			Tuple  		=	num_hidden_layers
									SCREAMING_SNAKE_CASE_:			List[str]  		=	num_attention_heads
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	hidden_act
									SCREAMING_SNAKE_CASE_:			Any  		=	intermediate_size
									SCREAMING_SNAKE_CASE_:			int  		=	hidden_dropout_prob
									SCREAMING_SNAKE_CASE_:			List[Any]  		=	attention_probs_dropout_prob
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	max_position_embeddings
									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	type_vocab_size
									SCREAMING_SNAKE_CASE_:			str  		=	initializer_range
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	initializer_factor
									SCREAMING_SNAKE_CASE_:			Dict  		=	layer_norm_eps
									SCREAMING_SNAKE_CASE_:			Tuple  		=	position_embedding_type
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	use_cache
									SCREAMING_SNAKE_CASE_:			Tuple  		=	project_dim







class   __lowercase    (			UpperCAmelCase_     ):




			"""simple docstring"""







			_UpperCAmelCase       :							int      							=					'''altclip_vision_model'''



			def __init__(			self  :					Optional[Any]       ,						lowerCAmelCase__  :					Optional[int]=768       ,						lowerCAmelCase__  :					str=3072       ,						lowerCAmelCase__  :					Optional[Any]=512       ,						lowerCAmelCase__  :					int=12       ,						lowerCAmelCase__  :					Any=12       ,						lowerCAmelCase__  :					Optional[Any]=3       ,						lowerCAmelCase__  :					List[str]=224       ,						lowerCAmelCase__  :					Optional[int]=32       ,						lowerCAmelCase__  :					Union[str, Any]="quick_gelu"       ,						lowerCAmelCase__  :					Optional[Any]=1E-5       ,						lowerCAmelCase__  :					List[Any]=0.0       ,						lowerCAmelCase__  :					Any=0.02       ,						lowerCAmelCase__  :					Dict=1.0       ,						**lowerCAmelCase__  :					Tuple       ,						):
									super().__init__(**lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_:			Tuple  		=	hidden_size
									SCREAMING_SNAKE_CASE_:			Tuple  		=	intermediate_size
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	projection_dim
									SCREAMING_SNAKE_CASE_:			int  		=	num_hidden_layers
									SCREAMING_SNAKE_CASE_:			Tuple  		=	num_attention_heads
									SCREAMING_SNAKE_CASE_:			Any  		=	num_channels
									SCREAMING_SNAKE_CASE_:			int  		=	patch_size
									SCREAMING_SNAKE_CASE_:			List[Any]  		=	image_size
									SCREAMING_SNAKE_CASE_:			Any  		=	initializer_range
									SCREAMING_SNAKE_CASE_:			List[str]  		=	initializer_factor
									SCREAMING_SNAKE_CASE_:			Tuple  		=	attention_dropout
									SCREAMING_SNAKE_CASE_:			int  		=	layer_norm_eps
									SCREAMING_SNAKE_CASE_:			List[str]  		=	hidden_act




			@classmethod
			def 	_SCREAMING_SNAKE_CASE      (			cls  :					Union[str, Any]       ,						lowerCAmelCase__  :					Union[str, os.PathLike]       ,						**lowerCAmelCase__  :					Optional[Any]):
									cls._set_token_in_kwargs(lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_		,   SCREAMING_SNAKE_CASE_:			List[str]  		=	cls.get_config_dict(lowerCAmelCase__       ,						**lowerCAmelCase__)

									# get the vision config dict if we are loading from AltCLIPConfig
									if config_dict.get("model_type") == "altclip":
															SCREAMING_SNAKE_CASE_:			Tuple  		=	config_dict["vision_config"]

									if "model_type" in config_dict and hasattr(cls       ,						"model_type") and config_dict["model_type"] != cls.model_type:
															logger.warning(
															    F"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
															    F"{cls.model_type}. This is not supported for all configurations of models and can yield errors.")

									return cls.from_dict(lowerCAmelCase__       ,						**lowerCAmelCase__)







class   __lowercase    (			UpperCAmelCase_     ):




			"""simple docstring"""







			_UpperCAmelCase       :							int      							=					'''altclip'''
			_UpperCAmelCase       :							Dict      							=					True



			def __init__(			self  :					Optional[Any]       ,						lowerCAmelCase__  :					int=None       ,						lowerCAmelCase__  :					Union[str, Any]=None       ,						lowerCAmelCase__  :					List[str]=768       ,						lowerCAmelCase__  :					Optional[Any]=2.6592       ,						**lowerCAmelCase__  :					str):
									# If `_config_dict` exist, we use them for the backward compatibility.
									# We pop out these 2 attributes before calling `super().__init__` to avoid them being saved (which causes a lot
									# of confusion!).
									SCREAMING_SNAKE_CASE_:			str  		=	kwargs.pop("text_config_dict"       ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	kwargs.pop("vision_config_dict"       ,						lowerCAmelCase__)

									super().__init__(**lowerCAmelCase__)

									# Instead of simply assigning `[text|vision]_config_dict` to `[text|vision]_config`, we use the values in
									# `[text|vision]_config_dict` to update the values in `[text|vision]_config`. The values should be same in most
									# cases, but we don't want to break anything regarding `_config_dict` that existed before commit `8827e1b2`.
									if text_config_dict is not None:
															if text_config is None:
																					SCREAMING_SNAKE_CASE_:			Any  		=	{}

															# This is the complete result when using `text_config_dict`.
															SCREAMING_SNAKE_CASE_:			int  		=	AltCLIPTextConfig(**lowerCAmelCase__).to_dict()

															# Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
															for key, value in _text_config_dict.items():
																					if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
																											# If specified in `text_config_dict`
																											if key in text_config_dict:
																																	SCREAMING_SNAKE_CASE_:			Dict  		=	(
																																	    F"`{key}` is found in both `text_config_dict` and `text_config` but with different values. "
																																	    F"The value `text_config_dict[\"{key}\"]` will be used instead."
																																	)
																											# If inferred from default argument values (just to be super careful)
																											else:
																																	SCREAMING_SNAKE_CASE_:			Any  		=	(
																																	    F"`text_config_dict` is provided which will be used to initialize `AltCLIPTextConfig`. The "
																																	    F"value `text_config[\"{key}\"]` will be overriden."
																																	)
																											logger.warning(lowerCAmelCase__)

            # Update all values in `text_config` with the ones in `_text_config_dict`.
															text_config.update(_text_config_dict)

									if vision_config_dict is not None:
															if vision_config is None:
																					SCREAMING_SNAKE_CASE_:			Tuple  		=	{}

															# This is the complete result when using `vision_config_dict`.
															SCREAMING_SNAKE_CASE_:			Optional[int]  		=	AltCLIPVisionConfig(**lowerCAmelCase__).to_dict()
															# convert keys to string instead of integer
															if "id2label" in _vision_config_dict:
																					SCREAMING_SNAKE_CASE_:			int  		=	{
																					    str(lowerCAmelCase__): value for key, value in _vision_config_dict["id2label"].items()
																					}

															# Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
															for key, value in _vision_config_dict.items():
																					if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
																											# If specified in `vision_config_dict`
																											if key in vision_config_dict:
																																	SCREAMING_SNAKE_CASE_:			List[str]  		=	(
																																	    F"`{key}` is found in both `vision_config_dict` and `vision_config` but with different "
																																	    F"values. The value `vision_config_dict[\"{key}\"]` will be used instead."
																																	)
																											# If inferred from default argument values (just to be super careful)
																											else:
																																	SCREAMING_SNAKE_CASE_:			List[Any]  		=	(
																																	    F"`vision_config_dict` is provided which will be used to initialize `AltCLIPVisionConfig`. "
																																	    F"The value `vision_config[\"{key}\"]` will be overriden."
																																	)
																											logger.warning(lowerCAmelCase__)

            # Update all values in `vision_config` with the ones in `_vision_config_dict`.
															vision_config.update(_vision_config_dict)

									if text_config is None:
															SCREAMING_SNAKE_CASE_:			List[Any]  		=	{}
															logger.info("`text_config` is `None`. Initializing the `AltCLIPTextConfig` with default values.")

									if vision_config is None:
															SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	{}
															logger.info("`vision_config` is `None`. initializing the `AltCLIPVisionConfig` with default values.")

									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	AltCLIPTextConfig(**lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_:			List[str]  		=	AltCLIPVisionConfig(**lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_:			str  		=	projection_dim
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	logit_scale_init_value
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	1.0



			@classmethod
			def 	_SCREAMING_SNAKE_CASE      (			cls  :					Tuple       ,						lowerCAmelCase__  :					AltCLIPTextConfig       ,						lowerCAmelCase__  :					AltCLIPVisionConfig       ,						**lowerCAmelCase__  :					Dict):
									return cls(text_config=text_config.to_dict()       ,						vision_config=vision_config.to_dict()       ,						**lowerCAmelCase__)




			def 	_SCREAMING_SNAKE_CASE      (			self  :					Tuple):
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	copy.deepcopy(self.__dict__)
									SCREAMING_SNAKE_CASE_:			Any  		=	self.text_config.to_dict()
									SCREAMING_SNAKE_CASE_:			int  		=	self.vision_config.to_dict()
									SCREAMING_SNAKE_CASE_:			Dict  		=	self.__class__.model_type
									return output









import doctest
from collections import deque

import numpy as np



class   __lowercase    :




			"""simple docstring"""







			def __init__(			self  :					Union[str, Any]):
									SCREAMING_SNAKE_CASE_:			int  		=	[2, 1, 2, -1]
									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	[1, 2, 3, 4]




			def 	_SCREAMING_SNAKE_CASE      (			self  :					Tuple):
									SCREAMING_SNAKE_CASE_:			Any  		=	len(self.first_signal)
									SCREAMING_SNAKE_CASE_:			Dict  		=	len(self.second_signal)

									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	max(lowerCAmelCase__       ,						lowerCAmelCase__)

									# create a zero matrix of max_length x max_length
									SCREAMING_SNAKE_CASE_:			List[Any]  		=	[[0] * max_length for i in range(lowerCAmelCase__)]

									# 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(lowerCAmelCase__):
															SCREAMING_SNAKE_CASE_:			Tuple  		=	deque(self.second_signal)
															rotated_signal.rotate(lowerCAmelCase__)
															for j, item in enumerate(lowerCAmelCase__):
																					matrix[i][j] += item

        # multiply the matrix with the first signal
									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	np.matmul(np.transpose(lowerCAmelCase__)       ,						np.transpose(self.first_signal))

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


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






