



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


UpperCAmelCase							 =					logging.get_logger(__name__)

UpperCAmelCase							 =					{
    """vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}

class  __snake_case      (   SCREAMING_SNAKE_CASE):







							'''simple docstring'''






							UpperCamelCase__				:      int         =					"""glpn"""


							def __init__(							self  ,  a_=3  ,  a_=4  ,  a_=[2, 2, 2, 2]  ,  a_=[8, 4, 2, 1]  ,  a_=[32, 64, 160, 256]  ,  a_=[7, 3, 3, 3]  ,  a_=[4, 2, 2, 2]  ,  a_=[1, 2, 5, 8]  ,  a_=[4, 4, 4, 4]  ,  a_="gelu"  ,  a_=0.0  ,  a_=0.0  ,  a_=0.02  ,  a_=0.1  ,  a_=1E-6  ,  a_=64  ,  a_=10  ,  a_=-1  ,  **a_  ,  ):
											super().__init__(**a_		)

											a__				      =		num_channels
											a__				      =		num_encoder_blocks
											a__				      =		depths
											a__				      =		sr_ratios
											a__				      =		hidden_sizes
											a__				      =		patch_sizes
											a__				      =		strides
											a__				      =		mlp_ratios
											a__				      =		num_attention_heads
											a__				      =		hidden_act
											a__				      =		hidden_dropout_prob
											a__				      =		attention_probs_dropout_prob
											a__				      =		initializer_range
											a__				      =		drop_path_rate
											a__				      =		layer_norm_eps
											a__				      =		decoder_hidden_size
											a__				      =		max_depth
											a__				      =		head_in_index






from math import sqrt

import numpy as np
from sympy import symbols

# Coefficient
# Speed of light (m/s)
UpperCAmelCase							 =					299_792_458

# Symbols
UpperCAmelCase ,       UpperCAmelCase ,       UpperCAmelCase ,       UpperCAmelCase							 =					symbols("""ct x y z""")

def 			A_      (	__a     :				float		):

				"""simple docstring"""
				if velocity > c:
								raise ValueError("""Speed must not exceed light speed 299,792,458 [m/s]!"""		)
				elif velocity < 1:
								# Usually the speed should be much higher than 1 (c order of magnitude)
								raise ValueError("""Speed must be greater than or equal to 1!"""		)

				return velocity / c

def 			A_      (	__a     :				float		):

				"""simple docstring"""
				return 1 / sqrt(1 - beta(__a		) ** 2		)

def 			A_      (	__a     :				float		):

				"""simple docstring"""
				return np.array(
				    [
				        [gamma(__a		), -gamma(__a		) * beta(__a		), 0, 0],
				        [-gamma(__a		) * beta(__a		), gamma(__a		), 0, 0],
				        [0, 0, 1, 0],
				        [0, 0, 0, 1],
				    ]		)

def 			A_      (	__a     :				float ,		__a     :				np.ndarray | None = None		):

				"""simple docstring"""
				# Ensure event is not empty
				if event is None:
								a__				      =		np.array([ct, x, y, z]		)  # Symbolic four vector
				else:
								event[0] *= c  # x0 is ct (speed of light * time)

				return transformation_matrix(__a		) @ event


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	# Example of symbolic vector:
	UpperCAmelCase							 =					transform(29_979_245)
	print("""Example of four vector: """)
	print(f"""ct' = {four_vector[0]}""")
	print(f"""x' = {four_vector[1]}""")
	print(f"""y' = {four_vector[2]}""")
	print(f"""z' = {four_vector[3]}""")

	# Substitute symbols with numerical values
	UpperCAmelCase							 =					{ct: c, x: 1, y: 1, z: 1}
	UpperCAmelCase							 =					[four_vector[i].subs(sub_dict) for i in range(4)]

	print(f"""\n{numerical_vector}""")

