
import os
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
	import torch

	from transformers import GPTaLMHeadModel

@require_torch
@require_sentencepiece
@require_tokenizers
class        UpperCamelCase__(    unittest.TestCase	):

	"""simple docstring"""

	@slow
	@unittest.skip("Model is not available." )
	def        _a					(      self				:			Tuple ):
			"""simple docstring"""





			A				="nvidia/megatron-gpt2-345m/"
			if "MYDIR" in os.environ:
					A				=os.path.join(os.environ["MYDIR"]							,			snake_case__ )
			A				=GPTaLMHeadModel.from_pretrained(snake_case__ )
			model.to(snake_case__ )
			model.half()

			A				=torch.tensor(
			    [[1_01, 71_10, 10_05, 10_56, 20_23, 1_13_33, 1_74_13, 10_29, 1_02]]							,			device=snake_case__							,			dtype=torch.long							,			)

			with torch.no_grad():
					A				=model(snake_case__ ).logits

			A				=torch.Size((1, 9, 5_02_57) )
			self.assertEqual(output.shape							,			snake_case__ )

			A				=torch.tensor(
			    [
			        4.9_414,
			        -0.2_920,
			        -1.2_148,
			        -4.0_273,
			        -0.5_161,
			        -5.2_109,
			        -1.2_412,
			        -1.8_301,
			        -1.7_734,
			        -4.7_148,
			        -0.2_317,
			        -1.0_811,
			        -2.1_777,
			        0.4_141,
			        -3.7_969,
			        -4.0_586,
			        -2.5_332,
			        -3.3_809,
			        4.3_867,
			    ]							,			device=snake_case__							,			dtype=torch.half							,			)

			for i in range(19 ):
					A			,    A				=8 * i // 17, 27_92 * i  # along the diagonal
					A			,    A				=output[0, r, c], expected_diag[i]
					A				=f'''row={r} col={c} computed={computed} expected={expected}'''
					self.assertAlmostEqual(snake_case__							,			snake_case__							,			delta=1E-4							,			msg=snake_case__ )






from __future__ import annotations

from typing import Any

class        UpperCamelCase__:

	"""simple docstring"""

	def __init__(      self				:			Dict							,			snake_case__				:			Any							,			snake_case__				:			Any ):  # noqa: A002
			"""simple docstring"""





			A				=item
			A				=next


class        UpperCamelCase__:

	"""simple docstring"""

	def __init__(      self				:			Optional[Any] ):
			"""simple docstring"""





			A				=None
			A				=0







	def        _a					(      self				:			str							,			snake_case__				:			Any ):
			"""simple docstring"""





			A				=Node(snake_case__							,			self.head )
			self.size += 1







	def        _a					(      self				:			Dict ):
			"""simple docstring"""





			if self.head is None:
					return None
			else:
					A				=self.head.item
					A				=self.head.next
					self.size -= 1
					return item







	def        _a					(      self				:			Any ):
			"""simple docstring"""





			return self.head is None







	def __str__(      self				:			Dict ):
			"""simple docstring"""





			if self.is_empty():
					return ""
			else:
					A				=self.head
					A				=""
					A				=[]
					while iterate:
							item_list.append(str(iterate.item ) )
							A				=iterate.next

					A				=" --> ".join(snake_case__ )

					return item_str







	def __len__(      self				:			Union[str, Any] ):
			"""simple docstring"""





			return self.size




