
from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
				import numpy as np
				import tensorflow as tf

				from transformers import TFCamembertModel







@require_tf
@require_sentencepiece
@require_tokenizers
class        lowercase	(      unittest.TestCase	):




							@slow
							def 				A__   (       self):
												lowercase					=		TFCamembertModel.from_pretrained('''jplu/tf-camembert-base''')

												lowercase					=		tf.convert_to_tensor(
												    [[5, 1_2_1, 1_1, 6_6_0, 1_6, 7_3_0, 2_5_5_4_3, 1_1_0, 8_3, 6]]     ,dtype=tf.intaa     ,)  # J'aime le camembert !"

												lowercase					=		model(A__)['''last_hidden_state''']
												lowercase					=		tf.TensorShape((1, 1_0, 7_6_8))
												self.assertEqual(output.shape     ,A__)
												# compare the actual values for a slice.
												lowercase					=		tf.convert_to_tensor(
												    [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]     ,dtype=tf.floataa     ,)
												# camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
												# camembert.eval()
												# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

												self.assertTrue(np.allclose(output[:, :3, :3].numpy()     ,expected_slice.numpy()     ,atol=1E-4))






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__	:Tuple										=					{
    "configuration_instructblip": [
        "INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "InstructBlipConfig",
        "InstructBlipQFormerConfig",
        "InstructBlipVisionConfig",
    ],
    "processing_instructblip": ["InstructBlipProcessor"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__	:List[str]										=					[
							    "INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "InstructBlipQFormerModel",
							    "InstructBlipPreTrainedModel",
							    "InstructBlipForConditionalGeneration",
							    "InstructBlipVisionModel",
							]

if TYPE_CHECKING:
							from .configuration_instructblip import (
							    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    InstructBlipConfig,
							    InstructBlipQFormerConfig,
							    InstructBlipVisionConfig,
							)
							from .processing_instructblip import InstructBlipProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_instructblip import (
														    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    InstructBlipForConditionalGeneration,
														    InstructBlipPreTrainedModel,
														    InstructBlipQFormerModel,
														    InstructBlipVisionModel,
														)

else:
							import sys

							lowercase__	:List[str]										=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




