


"""simple docstring"""



import unittest

from transformers import SpeechaTextaConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device

from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
			import torch

			from transformers.models.speech_to_text_a.modeling_speech_to_text_a import (
			    SpeechaTextaDecoder,
			    SpeechaTextaForCausalLM,
			)







@require_torch
class       __a	:







				def __init__(   self			,  UpperCAmelCase			,  UpperCAmelCase=99			,  UpperCAmelCase=13			,  UpperCAmelCase=16			,  UpperCAmelCase=7			,  UpperCAmelCase=True			,  UpperCAmelCase=True			,  UpperCAmelCase=True			,  UpperCAmelCase=False			,  UpperCAmelCase=True			,  UpperCAmelCase=2			,  UpperCAmelCase=32			,  UpperCAmelCase=4			,  UpperCAmelCase=4			,  UpperCAmelCase=30			,  UpperCAmelCase=0			,  UpperCAmelCase=1			,  UpperCAmelCase=2			,  UpperCAmelCase=None			,  ):

					'''simple docstring'''






					lowerCAmelCase_			       = parent
					lowerCAmelCase_			       = batch_size
					lowerCAmelCase_			       = decoder_seq_length
					# For common tests
					lowerCAmelCase_			       = self.decoder_seq_length
					lowerCAmelCase_			       = is_training
					lowerCAmelCase_			       = use_attention_mask
					lowerCAmelCase_			       = use_labels

					lowerCAmelCase_			       = vocab_size
					lowerCAmelCase_			       = d_model
					lowerCAmelCase_			       = d_model
					lowerCAmelCase_			       = decoder_layers
					lowerCAmelCase_			       = decoder_layers
					lowerCAmelCase_			       = decoder_ffn_dim
					lowerCAmelCase_			       = decoder_attention_heads
					lowerCAmelCase_			       = decoder_attention_heads
					lowerCAmelCase_			       = eos_token_id
					lowerCAmelCase_			       = bos_token_id
					lowerCAmelCase_			       = pad_token_id
					lowerCAmelCase_			       = decoder_start_token_id
					lowerCAmelCase_			       = use_cache
					lowerCAmelCase_			       = max_position_embeddings

					lowerCAmelCase_			       = None
					lowerCAmelCase_			       = decoder_seq_length
					lowerCAmelCase_			       = 2
					lowerCAmelCase_			       = 1







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					lowerCAmelCase_			       = ids_tensor([self.batch_size, self.decoder_seq_length]			,  self.vocab_size      )

					lowerCAmelCase_			       = None
					if self.use_attention_mask:
						lowerCAmelCase_			       = ids_tensor([self.batch_size, self.decoder_seq_length]			,  vocab_size=2      )

					lowerCAmelCase_			       = None
					if self.use_labels:
						lowerCAmelCase_			       = ids_tensor([self.batch_size, self.decoder_seq_length]			,  self.vocab_size      )

					lowerCAmelCase_			       = SpeechaTextaConfig(
					    vocab_size=self.vocab_size			,  d_model=self.d_model			,  decoder_layers=self.decoder_layers			,  decoder_ffn_dim=self.decoder_ffn_dim			,  decoder_attention_heads=self.decoder_attention_heads			,  eos_token_id=self.eos_token_id			,  bos_token_id=self.bos_token_id			,  use_cache=self.use_cache			,  pad_token_id=self.pad_token_id			,  decoder_start_token_id=self.decoder_start_token_id			,  max_position_embeddings=self.max_position_embeddings			,  )

					return (
					    config,
					    input_ids,
					    attention_mask,
					    lm_labels,
					)







				def     lowerCamelCase_    (   self			,  UpperCAmelCase			,  UpperCAmelCase			,  UpperCAmelCase			,  UpperCAmelCase			,  ):

					'''simple docstring'''






					lowerCAmelCase_			       = True
					lowerCAmelCase_			       = SpeechaTextaDecoder(config=UpperCAmelCase      ).to(UpperCAmelCase      ).eval()
					lowerCAmelCase_			       = input_ids[:2]

					input_ids[input_ids == 0] += 1
					# first forward pass
					lowerCAmelCase_			       = model(UpperCAmelCase			,  use_cache=UpperCAmelCase      )
					lowerCAmelCase_			       = model(UpperCAmelCase      )
					lowerCAmelCase_			       = model(UpperCAmelCase			,  use_cache=UpperCAmelCase      )

					self.parent.assertTrue(len(UpperCAmelCase      ) == len(UpperCAmelCase      )      )
					self.parent.assertTrue(len(UpperCAmelCase      ) == len(UpperCAmelCase      ) + 1      )

					lowerCAmelCase_			       = outputs['''past_key_values''']

					# create hypothetical next token and extent to next_input_ids
					lowerCAmelCase_			       = ids_tensor((2, 1)			,  config.vocab_size - 1      ) + 1

					# append to next input_ids and
					lowerCAmelCase_			       = torch.cat([input_ids, next_tokens]			,  dim=-1      )

					print(UpperCAmelCase      )

					lowerCAmelCase_			       = model(UpperCAmelCase      )['''last_hidden_state''']
					lowerCAmelCase_			       = model(UpperCAmelCase			,  past_key_values=UpperCAmelCase      )['''last_hidden_state''']

					# select random slice
					lowerCAmelCase_			       = ids_tensor((1,)			,  output_from_past.shape[-1]      ).item()
					lowerCAmelCase_			       = output_from_no_past[:, next_input_ids.shape[-1] - 1, random_slice_idx].detach()
					lowerCAmelCase_			       = output_from_past[:, 0, random_slice_idx].detach()

					# test that outputs are equal for slice
					assert torch.allclose(UpperCAmelCase			,  UpperCAmelCase			,  atol=1E-3      )







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					lowerCAmelCase_			       = self.prepare_config_and_inputs()
					(
					    (
					    lowerCAmelCase_  
					)       ,  (
					    lowerCAmelCase_  
					)       ,  (
					    lowerCAmelCase_  
					)       ,  (
					    lowerCAmelCase_  
					)       ,    
					)			       = config_and_inputs

					lowerCAmelCase_			       = {
					    '''input_ids''': input_ids,
					    '''attention_mask''': attention_mask,
					}
					return config, inputs_dict







@require_torch
class       __a	(   __snake_case				, __snake_case				, __snake_case				, unittest.TestCase       ):
				lowerCamelCase    :					Any 					=(SpeechaTextaDecoder, SpeechaTextaForCausalLM) if is_torch_available() else ()
				lowerCamelCase    :					Optional[Any] 					=(SpeechaTextaForCausalLM,) if is_torch_available() else ()
				lowerCamelCase    :					str 					={'text-generation': SpeechaTextaForCausalLM} if is_torch_available() else {}
				lowerCamelCase    :					Any 					=True
				lowerCamelCase    :					Tuple 					=False







				def     lowerCamelCase_    (   self			,  ):

					'''simple docstring'''






					lowerCAmelCase_			       = SpeechaTextaStandaloneDecoderModelTester(self			,  is_training=UpperCAmelCase      )
					lowerCAmelCase_			       = ConfigTester(self			,  config_class=UpperCAmelCase      )







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					pass







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					pass







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					pass







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					self.config_tester.run_common_tests()







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					lowerCAmelCase_			       = self.model_tester.prepare_config_and_inputs()
					self.model_tester.create_and_check_decoder_model_past(*UpperCAmelCase      )







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					return



"""simple docstring"""



import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


lowercase_							 =       logging.get_logger(__name__)  # pylint: disable=invalid-name


lowercase_							 =       'lfs-multipart-upload'







class       __a	(   __snake_case       ):







				@staticmethod
				def     lowerCamelCase_    (   UpperCAmelCase      ):

					'''simple docstring'''






					lowerCAmelCase_			       = parser.add_parser(
					    '''lfs-enable-largefiles'''			,  help=(
					        '''Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB.'''
					    )			,  )
					enable_parser.add_argument('''path'''			,  type=UpperCAmelCase			,  help='''Local path to repository you want to configure.'''      )
					enable_parser.set_defaults(func=lambda UpperCAmelCase      : LfsEnableCommand(UpperCAmelCase      )      )

					lowerCAmelCase_			       = parser.add_parser(
					    UpperCAmelCase			,  help=(
					        '''Deprecated: use `huggingface-cli` instead. '''
					        '''Command will get called by git-lfs, do not call it directly.'''
					    )			,  )
					upload_parser.set_defaults(func=lambda UpperCAmelCase      : LfsUploadCommand(UpperCAmelCase      )      )







class       __a	:







				def __init__(   self			,  UpperCAmelCase      ):

					'''simple docstring'''






					lowerCAmelCase_			       = args







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					warnings.warn(
					    '''Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead.'''      )
					lowerCAmelCase_			       = os.path.abspath(self.args.path      )
					if not os.path.isdir(UpperCAmelCase      ):
						print('''This does not look like a valid git repo.'''      )
						exit(1      )
					subprocess.run(
					    '''git config lfs.customtransfer.multipart.path transformers-cli'''.split()			,  check=UpperCAmelCase			,  cwd=UpperCAmelCase      )
					subprocess.run(
					    F"""git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}""".split()			,  check=UpperCAmelCase			,  cwd=UpperCAmelCase			,  )
					print('''Local repo set up for largefiles'''      )




def     UpperCAmelCase    (					_lowercase   :      Dict  )	->   str:


	"""simple docstring"""




	lowerCAmelCase_			       = json.dumps(_lowercase  ) + '''\n'''
	sys.stdout.write(_lowercase  )
	sys.stdout.flush()
def     UpperCAmelCase    (					)	->   Optional[Dict]:


	"""simple docstring"""




	lowerCAmelCase_			       = json.loads(sys.stdin.readline().strip()  )

	if "terminate" in (msg.get('''type'''  ), msg.get('''event'''  )):
		# terminate message received
		return None

	if msg.get('''event'''  ) not in ("download", "upload"):
		logger.critical('''Received unexpected message'''  )
		sys.exit(1  )

	return msg







class       __a	(   __snake_case       ):







				def __init__(   self			,  UpperCAmelCase			,  UpperCAmelCase			,  UpperCAmelCase      ):

					'''simple docstring'''






					lowerCAmelCase_			       = filepath
					lowerCAmelCase_			       = seek_from
					lowerCAmelCase_			       = read_limit
					lowerCAmelCase_			       = 0







				def __enter__(   self      ):

					'''simple docstring'''






					lowerCAmelCase_			       = open(self.filepath			,  '''rb'''      )
					self.f.seek(self.seek_from      )
					return self







				def __len__(   self      ):

					'''simple docstring'''






					lowerCAmelCase_			       = os.fstat(self.f.fileno()      ).st_size
					return min(self.read_limit			,  total_length - self.seek_from      )







				def     lowerCamelCase_    (   self			,  UpperCAmelCase=-1      ):

					'''simple docstring'''






					if self.n_seen >= self.read_limit:
						return b""
					lowerCAmelCase_			       = self.read_limit - self.n_seen
					lowerCAmelCase_			       = self.f.read(remaining_amount if n < 0 else min(UpperCAmelCase			,  UpperCAmelCase      )      )
					self.n_seen += len(UpperCAmelCase      )
					return data







				def __iter__(   self      ):

					'''simple docstring'''






					yield self.read(n=4 * 1024 * 1024      )







				def __exit__(   self			,  *UpperCAmelCase      ):

					'''simple docstring'''






					self.f.close()







class       __a	:







				def __init__(   self			,  UpperCAmelCase      ):

					'''simple docstring'''






					lowerCAmelCase_			       = args







				def     lowerCamelCase_    (   self      ):

					'''simple docstring'''






					lowerCAmelCase_			       = json.loads(sys.stdin.readline().strip()      )
					if not (init_msg.get('''event'''      ) == "init" and init_msg.get('''operation'''      ) == "upload"):
						write_msg({'''error''': {'''code''': 32, '''message''': '''Wrong lfs init operation'''}}      )
						sys.exit(1      )

					# The transfer process should use the information it needs from the
					# initiation structure, and also perform any one-off setup tasks it
					# needs to do. It should then respond on stdout with a simple empty
					# confirmation structure, as follows:
					write_msg({}      )

					# After the initiation exchange, git-lfs will send any number of
					# transfer requests to the stdin of the transfer process, in a serial sequence.
					while True:
						lowerCAmelCase_			       = read_msg()
						if msg is None:
							# When all transfers have been processed, git-lfs will send
							# a terminate event to the stdin of the transfer process.
							# On receiving this message the transfer process should
							# clean up and terminate. No response is expected.
							sys.exit(0      )

						lowerCAmelCase_			       = msg['''oid''']
						lowerCAmelCase_			       = msg['''path''']
						lowerCAmelCase_			       = msg['''action''']['''href''']
						lowerCAmelCase_			       = msg['''action''']['''header''']
						lowerCAmelCase_			       = int(header.pop('''chunk_size'''      )      )
						lowerCAmelCase_			       = list(header.values()      )

						lowerCAmelCase_			       = []
						for i, presigned_url in enumerate(UpperCAmelCase      ):
							with FileSlice(UpperCAmelCase			,  seek_from=i * chunk_size			,  read_limit=UpperCAmelCase      ) as data:
								lowerCAmelCase_			       = requests.put(UpperCAmelCase			,  data=UpperCAmelCase      )
								r.raise_for_status()
								parts.append(
								    {
								        '''etag''': r.headers.get('''etag'''      ),
								        '''partNumber''': i + 1,
								    }      )
								# In order to support progress reporting while data is uploading / downloading,
								# the transfer process should post messages to stdout
								write_msg(
								    {
								        '''event''': '''progress''',
								        '''oid''': oid,
								        '''bytesSoFar''': (i + 1) * chunk_size,
								        '''bytesSinceLast''': chunk_size,
								    }      )
								# Not precise but that's ok.

						lowerCAmelCase_			       = requests.post(
						    UpperCAmelCase			,  json={
						        '''oid''': oid,
						        '''parts''': parts,
						    }			,  )
						r.raise_for_status()

						write_msg({'''event''': '''complete''', '''oid''': oid}      )