





import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
_SCREAMING_SNAKE_CASE 		=						object()

# For specifying empty leaf dict `{}`
_SCREAMING_SNAKE_CASE 		=						object()


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				):
	snake_case_						:     Any     =		tuple((re.compile(x + '$'				) for x in qs)				)
	for i in range(len(__a				) - len(__a				) + 1				):
		snake_case_						:     List[str]     =		[x.match(__a				) for x, y in zip(__a				,	ks[i:]				)]
		if matches and all(__a				):
			return True
	return False


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	def replace(__a				,	__a				):
		for rule, replacement in rules:
			if _match(__a				,	__a				):
				return replacement
		return val

	return replace


def 							SCREAMING_SNAKE_CASE__  (      ):
	return [
	    # embeddings
	    (("transformer", "wpe", "embedding"), P('mp'				,	__a				)),
	    (("transformer", "wte", "embedding"), P('mp'				,	__a				)),
	    # atention
	    (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(__a				,	'mp'				)),
	    (("attention", "out_proj", "kernel"), P('mp'				,	__a				)),
	    (("attention", "out_proj", "bias"), None),
	    # mlp
	    (("mlp", "c_fc", "kernel"), P(__a				,	'mp'				)),
	    (("mlp", "c_fc", "bias"), P('mp'				)),
	    (("mlp", "c_proj", "kernel"), P('mp'				,	__a				)),
	    (("mlp", "c_proj", "bias"), None),
	    # layer norms
	    ((r"ln_\d+", "bias"), None),
	    ((r"\d+", r"ln_\d+", "scale"), None),
	    (("ln_f", "bias"), None),
	    (("ln_f", "scale"), None),
	]


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	snake_case_						:     Optional[int]     =		_get_partition_rules()
	snake_case_						:     Any     =		_replacement_rules(__a				)
	snake_case_						:     int     =		{k: _unmatched for k in flatten_dict(__a				)}
	snake_case_						:     Union[str, Any]     =		{k: replace(__a				,	__a				) for k, v in initd.items()}
	assert _unmatched not in result.values(), "Incomplete partition spec."
	return freeze(unflatten_dict(__a				)				)








from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				):
	snake_case_						:     List[Any]     =		k_size // 2
	snake_case_  ,snake_case_						:     Any     =		mgrid[0 - center : k_size - center, 0 - center : k_size - center]
	snake_case_						:     Optional[Any]     =		1 / (2 * pi * sigma) * exp(-(square(__a				) + square(__a				)) / (2 * square(__a				))				)
	return g


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				,	__a				):
	snake_case_  ,snake_case_						:     Union[str, Any]     =		image.shape[0], image.shape[1]
	# dst image height and width
	snake_case_						:     int     =		height - k_size + 1
	snake_case_						:     Optional[int]     =		width - k_size + 1

	# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
	snake_case_						:     Optional[Any]     =		zeros((dst_height * dst_width, k_size * k_size)				)
	snake_case_						:     Tuple     =		0
	for i, j in product(range(__a				)				,	range(__a				)				):
		snake_case_						:     Optional[int]     =		ravel(image[i : i + k_size, j : j + k_size]				)
		snake_case_						:     str     =		window
		row += 1

	#  turn the kernel into shape(k*k, 1)
	snake_case_						:     List[Any]     =		gen_gaussian_kernel(__a				,	__a				)
	snake_case_						:     str     =		ravel(__a				)

	# reshape and get the dst image
	snake_case_						:     Optional[int]     =		dot(__a				,	__a				).reshape(__a				,	__a				).astype(__a				)

	return dst


if __name__ == "__main__":
						# read original image
						_SCREAMING_SNAKE_CASE 		=						imread(R"""../image_data/lena.jpg""")
						# turn image in gray scale value
						_SCREAMING_SNAKE_CASE 		=						cvtColor(img, COLOR_BGR2GRAY)

						# get values with two different mask size
						_SCREAMING_SNAKE_CASE 		=						gaussian_filter(gray, 3, sigma=1)
						_SCREAMING_SNAKE_CASE 		=						gaussian_filter(gray, 5, sigma=0.8)

						# show result images
						imshow("""gaussian filter with 3x3 mask""", gaussianaxa)
						imshow("""gaussian filter with 5x5 mask""", gaussianaxa)
						waitKey()

