
from typing import Any






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							):
	_validation(
	    __SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							)
	# Creates data structures and fill initial step
	lowercase       =    {}
	lowercase       =    {}
	for state in states_space:
		lowercase       =    observations_space[0]
		lowercase       =    (
		    initial_probabilities[state] * emission_probabilities[state][observation]
		)
		lowercase       =    None

	# Fills the data structure with the probabilities of
	# different transitions and pointers to previous states
	for o in range(1 ,							len(__SCREAMING_SNAKE_CASE							)							):
		lowercase       =    observations_space[o]
		lowercase       =    observations_space[o - 1]
		for state in states_space:
			# Calculates the argmax for probability function
			lowercase       =    ''
			lowercase       =    -1
			for k_state in states_space:
				lowercase       =    (
				    probabilities[(k_state, prior_observation)]
				    * transition_probabilities[k_state][state]
				    * emission_probabilities[state][observation]
				)
				if probability > max_probability:
					lowercase       =    probability
					lowercase       =    k_state

            # Update probabilities and pointers dicts
			lowercase       =    (
			    probabilities[(arg_max, prior_observation)]
			    * transition_probabilities[arg_max][state]
			    * emission_probabilities[state][observation]
			)

			lowercase       =    arg_max

    # The final observation
	lowercase       =    observations_space[len(__SCREAMING_SNAKE_CASE							) - 1]

	# argmax for given final observation
	lowercase       =    ''
	lowercase       =    -1
	for k_state in states_space:
		lowercase       =    probabilities[(k_state, final_observation)]
		if probability > max_probability:
			lowercase       =    probability
			lowercase       =    k_state
	lowercase       =    arg_max

	# Process pointers backwards
	lowercase       =    last_state
	lowercase       =    []
	for o in range(len(__SCREAMING_SNAKE_CASE							) - 1 ,							-1 ,							-1							):
		result.append(__SCREAMING_SNAKE_CASE							)
		lowercase       =    pointers[previous, observations_space[o]]
	result.reverse()

	return result






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							):
	_validate_not_empty(
	    __SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							)
	_validate_lists(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)
	_validate_dicts(
	    __SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							):
	if not all(
	    [
	        observations_space,
	        states_space,
	        initial_probabilities,
	        transition_probabilities,
	        emission_probabilities,
	    ]							):
		raise ValueError('There\'s an empty parameter'							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	_validate_list(__SCREAMING_SNAKE_CASE ,							'observations_space'							)
	_validate_list(__SCREAMING_SNAKE_CASE ,							'states_space'							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	if not isinstance(_object ,							__SCREAMING_SNAKE_CASE							):
		lowercase       =    F'''{var_name} must be a list'''
		raise ValueError(__SCREAMING_SNAKE_CASE							)
	else:
		for x in _object:
			if not isinstance(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
				lowercase       =    F'''{var_name} must be a list of strings'''
				raise ValueError(__SCREAMING_SNAKE_CASE							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							):
	_validate_dict(__SCREAMING_SNAKE_CASE ,							'initial_probabilities' ,							__SCREAMING_SNAKE_CASE							)
	_validate_nested_dict(__SCREAMING_SNAKE_CASE ,							'transition_probabilities'							)
	_validate_nested_dict(__SCREAMING_SNAKE_CASE ,							'emission_probabilities'							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	_validate_dict(_object ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)
	for x in _object.values():
		_validate_dict(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE = False							):
	if not isinstance(_object ,							__SCREAMING_SNAKE_CASE							):
		lowercase       =    F'''{var_name} must be a dict'''
		raise ValueError(__SCREAMING_SNAKE_CASE							)
	if not all(isinstance(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							) for x in _object							):
		lowercase       =    F'''{var_name} all keys must be strings'''
		raise ValueError(__SCREAMING_SNAKE_CASE							)
	if not all(isinstance(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							) for x in _object.values()							):
		lowercase       =    'nested dictionary ' if nested else ''
		lowercase       =    F'''{var_name} {nested_text}all values must be {value_type.__name__}'''
		raise ValueError(__SCREAMING_SNAKE_CASE							)


if __name__ == "__main__":
	from doctest import testmod

	testmod()



# Copyright 2021 The HuggingFace 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 pathlib import Path

import torch

from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter


UpperCAmelCase	      = '''Create a default config file for Accelerate with only a few flags set.'''






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE="no" ,							__SCREAMING_SNAKE_CASE = default_json_config_file ,							__SCREAMING_SNAKE_CASE = False							):
	lowercase       =    Path(__SCREAMING_SNAKE_CASE							)
	path.parent.mkdir(parents=__SCREAMING_SNAKE_CASE ,							exist_ok=__SCREAMING_SNAKE_CASE							)
	if path.exists():
		print(
		    F'''Configuration already exists at {save_location}, will not override. Run `accelerate config` manually or pass a different `save_location`.'''							)
		return False
	lowercase       =    mixed_precision.lower()
	if mixed_precision not in ["no", "fp16", "bf16", "fp8"]:
		raise ValueError(
		    F'''`mixed_precision` should be one of \'no\', \'fp16\', \'bf16\', or \'fp8\'. Received {mixed_precision}'''							)
	lowercase       =    {
	    'compute_environment': 'LOCAL_MACHINE',
	    'mixed_precision': mixed_precision,
	}
	if torch.cuda.is_available():
		lowercase       =    torch.cuda.device_count()
		lowercase       =    num_gpus
		lowercase       =    False
		if num_gpus > 1:
			lowercase       =    'MULTI_GPU'
		else:
			lowercase       =    'NO'
	elif is_xpu_available() and use_xpu:
		lowercase       =    torch.xpu.device_count()
		lowercase       =    num_xpus
		lowercase       =    False
		if num_xpus > 1:
			lowercase       =    'MULTI_XPU'
		else:
			lowercase       =    'NO'
	elif is_npu_available():
		lowercase       =    torch.npu.device_count()
		lowercase       =    num_npus
		lowercase       =    False
		if num_npus > 1:
			lowercase       =    'MULTI_NPU'
		else:
			lowercase       =    'NO'
	else:
		lowercase       =    0
		lowercase       =    True
		lowercase       =    1
		lowercase       =    'NO'
	lowercase       =    ClusterConfig(**__SCREAMING_SNAKE_CASE							)
	config.to_json_file(__SCREAMING_SNAKE_CASE							)
	return path






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	lowercase       =    parser.add_parser('default' ,							parents=__SCREAMING_SNAKE_CASE ,							help=__SCREAMING_SNAKE_CASE ,							formatter_class=__SCREAMING_SNAKE_CASE							)
	parser.add_argument(
	    '--config_file' ,							default=__SCREAMING_SNAKE_CASE ,							help=(
	        'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
	        'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
	        'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
	        'with \'huggingface\'.'
	    ) ,							dest='save_location' ,							)

	parser.add_argument(
	    '--mixed_precision' ,							choices=['no', 'fp16', 'bf16'] ,							type=__SCREAMING_SNAKE_CASE ,							help='Whether or not to use mixed precision training. '
	    'Choose between FP16 and BF16 (bfloat16) training. '
	    'BF16 training is only supported on Nvidia Ampere GPUs and PyTorch 1.10 or later.' ,							default='no' ,							)
	parser.set_defaults(func=__SCREAMING_SNAKE_CASE							)
	return parser






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	lowercase       =    write_basic_config(args.mixed_precision ,							args.save_location							)
	if config_file:
		print(F'''accelerate configuration saved at {config_file}'''							)

