



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


UpperCAmelCase							=       {
    """configuration_speech_to_text_2""": ["""SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Speech2Text2Config"""],
    """processing_speech_to_text_2""": ["""Speech2Text2Processor"""],
    """tokenization_speech_to_text_2""": ["""Speech2Text2Tokenizer"""],
}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase							=       [
	    """SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """Speech2Text2ForCausalLM""",
	    """Speech2Text2PreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
	from .processing_speech_to_text_a import SpeechaTextaProcessor
	from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_speech_to_text_a import (
		    SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SpeechaTextaForCausalLM,
		    SpeechaTextaPreTrainedModel,
		)

else:
	import sys

	UpperCAmelCase							=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






from collections import defaultdict

def       A_   (						__a  :					str		):

				"""simple docstring"""
				a__					   =		defaultdict(__a		)
				# Creating a dictionary containing count of each word
				for word in sentence.split():
								occurrence[word] += 1
				return occurrence


if __name__ == "__main__":
	for word, count in word_occurrence("""INPUT STRING""").items():
		print(f"""{word}: {count}""")

