





'''simple docstring'''







from collections.abc import Generator
from math import sin





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			str   ) ->	List[str]:
						if len(__A   ) != 32:
												raise ValueError('''Input must be of length 32'''   )

						UpperCAmelCase_			:      Any     						=  b''''''
						for i in [3, 2, 1, 0]:
												little_endian += string_aa[8 * i : 8 * i + 8]
						return little_endian





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			Any   ) ->	Union[str, Any]:
						if i < 0:
												raise ValueError('''Input must be non-negative'''   )

						UpperCAmelCase_			:      str     						=  format(__A,			'''08x'''   )[-8:]
						UpperCAmelCase_			:      List[str]     						=  b''''''
						for i in [3, 2, 1, 0]:
												little_endian_hex += hex_rep[2 * i : 2 * i + 2].encode('''utf-8'''   )
						return little_endian_hex





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			Optional[Any]   ) ->	int:
						UpperCAmelCase_			:      List[str]     						=  b''''''
						for char in message:
												bit_string += format(__A,			'''08b'''   ).encode('''utf-8'''   )
						UpperCAmelCase_			:      List[str]     						=  format(len(__A   ),			'''064b'''   ).encode('''utf-8'''   )

						# Pad bit_string to a multiple of 512 chars
						bit_string += b"1"
						while len(__A   ) % 512 != 448:
												bit_string += b"0"
						bit_string += to_little_endian(start_len[32:]   ) + to_little_endian(start_len[:32]   )

						return bit_string





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			Tuple   ) ->	Any:
						if len(__A   ) % 512 != 0:
												raise ValueError('''Input must have length that\'s a multiple of 512'''   )

						for pos in range(0,			len(__A   ),			512   ):
												UpperCAmelCase_			:      Optional[int]     						=  bit_string[pos : pos + 512]
												UpperCAmelCase_			:      str     						=  []
												for i in range(0,			512,			32   ):
																		block_words.append(int(to_little_endian(block[i : i + 32]   ),			2   )   )
												yield block_words





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			Optional[int]   ) ->	Optional[Any]:
						if i < 0:
												raise ValueError('''Input must be non-negative'''   )

						UpperCAmelCase_			:      Optional[Any]     						=  format(__A,			'''032b'''   )
						UpperCAmelCase_			:      List[str]     						=  ''''''
						for c in i_str:
												new_str += "1" if c == "0" else "0"
						return int(__A,			2   )





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			int,			SCREAMING_SNAKE_CASE__      :			Dict   ) ->	Any:
						return (a + b) % 2**32





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			str,			SCREAMING_SNAKE_CASE__      :			Dict   ) ->	Any:
						if i < 0:
												raise ValueError('''Input must be non-negative'''   )
						if shift < 0:
												raise ValueError('''Shift must be non-negative'''   )
						return ((i << shift) ^ (i >> (32 - shift))) % 2**32





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			int   ) ->	Optional[int]:
						UpperCAmelCase_			:      List[Any]     						=  preprocess(__A   )

						UpperCAmelCase_			:      int     						=  [int(2**32 * abs(sin(i + 1   )   )   ) for i in range(64   )]

						# Starting states
						UpperCAmelCase_			:      int     						=  0x67_452_301
						UpperCAmelCase_			:      Any     						=  0xEF_CDA_B89
						UpperCAmelCase_			:      Optional[Any]     						=  0x98_BAD_CFE
						UpperCAmelCase_			:      int     						=  0x10_325_476

						UpperCAmelCase_			:      int     						=  [
						    7,
						    12,
						    17,
						    22,
						    7,
						    12,
						    17,
						    22,
						    7,
						    12,
						    17,
						    22,
						    7,
						    12,
						    17,
						    22,
						    5,
						    9,
						    14,
						    20,
						    5,
						    9,
						    14,
						    20,
						    5,
						    9,
						    14,
						    20,
						    5,
						    9,
						    14,
						    20,
						    4,
						    11,
						    16,
						    23,
						    4,
						    11,
						    16,
						    23,
						    4,
						    11,
						    16,
						    23,
						    4,
						    11,
						    16,
						    23,
						    6,
						    10,
						    15,
						    21,
						    6,
						    10,
						    15,
						    21,
						    6,
						    10,
						    15,
						    21,
						    6,
						    10,
						    15,
						    21,
						]

						# Process bit string in chunks, each with 16 32-char words
						for block_words in get_block_words(__A   ):
												UpperCAmelCase_			:      List[str]     						=  aa
												UpperCAmelCase_			:      Union[str, Any]     						=  ba
												UpperCAmelCase_			:      List[str]     						=  ca
												UpperCAmelCase_			:      Optional[Any]     						=  da

												# Hash current chunk
												for i in range(64   ):
																		if i <= 15:
																								# f = (b & c) | (not_32(b) & d)     # Alternate definition for f
																								UpperCAmelCase_			:      int     						=  d ^ (b & (c ^ d))
																								UpperCAmelCase_			:      Optional[int]     						=  i
																		elif i <= 31:
																								# f = (d & b) | (not_32(d) & c)     # Alternate definition for f
																								UpperCAmelCase_			:      Tuple     						=  c ^ (d & (b ^ c))
																								UpperCAmelCase_			:      Union[str, Any]     						=  (5 * i + 1) % 16
																		elif i <= 47:
																								UpperCAmelCase_			:      Tuple     						=  b ^ c ^ d
																								UpperCAmelCase_			:      Union[str, Any]     						=  (3 * i + 5) % 16
																		else:
																								UpperCAmelCase_			:      Any     						=  c ^ (b | not_aa(__A   ))
																								UpperCAmelCase_			:      Tuple     						=  (7 * i) % 16
																		UpperCAmelCase_			:      Tuple     						=  (f + a + added_consts[i] + block_words[g]) % 2**32
																		UpperCAmelCase_			:      Optional[int]     						=  d
																		UpperCAmelCase_			:      int     						=  c
																		UpperCAmelCase_			:      Any     						=  b
																		UpperCAmelCase_			:      List[Any]     						=  sum_aa(__A,			left_rotate_aa(__A,			shift_amounts[i]   )   )

												# Add hashed chunk to running total
												UpperCAmelCase_			:      int     						=  sum_aa(__A,			__A   )
												UpperCAmelCase_			:      int     						=  sum_aa(__A,			__A   )
												UpperCAmelCase_			:      List[Any]     						=  sum_aa(__A,			__A   )
												UpperCAmelCase_			:      Optional[int]     						=  sum_aa(__A,			__A   )

						UpperCAmelCase_			:      Any     						=  reformat_hex(__A   ) + reformat_hex(__A   ) + reformat_hex(__A   ) + reformat_hex(__A   )
						return digest


if __name__ == "__main__":
					import doctest

					doctest.testmod()












'''simple docstring'''







import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential

if __name__ == "__main__":
					snake_case_     :       List[Any]						=  pd.read_csv("sample_data.csv", header=None)
					snake_case_     :       Optional[Any]						=  df.shape[:1][0]
					# If you're using some other dataset input the target column
					snake_case_     :       Any						=  df.iloc[:, 1:2]
					snake_case_     :       str						=  actual_data.values.reshape(len_data, 1)
					snake_case_     :       Optional[Any]						=  MinMaxScaler().fit_transform(actual_data)
					snake_case_     :       List[str]						=  10
					snake_case_     :       Any						=  5
					snake_case_     :       Any						=  20
					snake_case_     :       Tuple						=  len_data - periods * look_back
					snake_case_     :       str						=  actual_data[:division]
					snake_case_     :       Optional[int]						=  actual_data[division - look_back :]
					snake_case_			,snake_case_     :       Any						=  [], []
					snake_case_			,snake_case_     :       Union[str, Any]						=  [], []

					for i in range(0, len(train_data) - forward_days - look_back + 1):
										train_x.append(train_data[i : i + look_back])
										train_y.append(train_data[i + look_back : i + look_back + forward_days])
					for i in range(0, len(test_data) - forward_days - look_back + 1):
										test_x.append(test_data[i : i + look_back])
										test_y.append(test_data[i + look_back : i + look_back + forward_days])
					snake_case_     :       Any						=  np.array(train_x)
					snake_case_     :       Optional[Any]						=  np.array(test_x)
					snake_case_     :       Optional[Any]						=  np.array([list(i.ravel()) for i in train_y])
					snake_case_     :       List[str]						=  np.array([list(i.ravel()) for i in test_y])

					snake_case_     :       List[Any]						=  Sequential()
					model.add(LSTM(1_28, input_shape=(look_back, 1), return_sequences=True))
					model.add(LSTM(64, input_shape=(1_28, 1)))
					model.add(Dense(forward_days))
					model.compile(loss="mean_squared_error", optimizer="adam")
					snake_case_     :       Dict						=  model.fit(
					    x_train, y_train, epochs=1_50, verbose=1, shuffle=True, batch_size=4
					)
					snake_case_     :       Optional[Any]						=  model.predict(x_test)





