"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase					: Optional[int]        =logging.get_logger(__name__)

__lowerCAmelCase					: str        ={
    """vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}





class 				_A		( lowercase_			):
      snake_case__    :     Optional[int]													=			'''glpn'''

      def __init__(		self	, __lowerCAmelCase=3	, __lowerCAmelCase=4	, __lowerCAmelCase=[2, 2, 2, 2]	, __lowerCAmelCase=[8, 4, 2, 1]	, __lowerCAmelCase=[32, 64, 160, 256]	, __lowerCAmelCase=[7, 3, 3, 3]	, __lowerCAmelCase=[4, 2, 2, 2]	, __lowerCAmelCase=[1, 2, 5, 8]	, __lowerCAmelCase=[4, 4, 4, 4]	, __lowerCAmelCase="gelu"	, __lowerCAmelCase=0.0	, __lowerCAmelCase=0.0	, __lowerCAmelCase=0.0_2	, __lowerCAmelCase=0.1	, __lowerCAmelCase=1E-6	, __lowerCAmelCase=64	, __lowerCAmelCase=10	, __lowerCAmelCase=-1	, **__lowerCAmelCase	, ):







            """simple docstring"""



            super().__init__(**UpperCamelCase__		)

            lowercase														=			num_channels
            lowercase														=			num_encoder_blocks
            lowercase														=			depths
            lowercase														=			sr_ratios
            lowercase														=			hidden_sizes
            lowercase														=			patch_sizes
            lowercase														=			strides
            lowercase														=			mlp_ratios
            lowercase														=			num_attention_heads
            lowercase														=			hidden_act
            lowercase														=			hidden_dropout_prob
            lowercase														=			attention_probs_dropout_prob
            lowercase														=			initializer_range
            lowercase														=			drop_path_rate
            lowercase														=			layer_norm_eps
            lowercase														=			decoder_hidden_size
            lowercase														=			max_depth
            lowercase														=			head_in_index




"""simple docstring"""






import unittest

from transformers import (
    MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
    TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
    TextClassificationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow

from .test_pipelines_common import ANY


# These 2 model types require different inputs than those of the usual text models.
__lowerCAmelCase					: int        ={"""LayoutLMv2Config""", """LayoutLMv3Config"""}





@is_pipeline_test
class 				_A		( unittest.TestCase			):
      snake_case__    :     Optional[int]													=			MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
      snake_case__    :     str													=			TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING

      if model_mapping is not None:
            snake_case__    :     Optional[Any]													=			{config: model for config, model in model_mapping.items() if config.__name__ not in _TO_SKIP}
      if tf_model_mapping is not None:
            snake_case__    :     List[Any]													=			{
                config: model for config, model in tf_model_mapping.items() if config.__name__ not in _TO_SKIP
            }

      @require_torch
      def        A__ (		self		):







            """simple docstring"""



            lowercase														=			pipeline(
                task="""text-classification"""	, model="""hf-internal-testing/tiny-random-distilbert"""	, framework="""pt"""		)

            lowercase														=			text_classifier("""This is great !"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """LABEL_0""", """score""": 0.5_0_4}]		)

            lowercase														=			text_classifier("""This is great !"""	, top_k=2		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}]		)

            lowercase														=			text_classifier(["""This is great !""", """This is bad"""]	, top_k=2		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, [
                    [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}],
                    [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}],
                ]	, )

            lowercase														=			text_classifier("""This is great !"""	, top_k=1		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """LABEL_0""", """score""": 0.5_0_4}]		)

            # Legacy behavior
            lowercase														=			text_classifier("""This is great !"""	, return_all_scores=__lowerCAmelCase		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """LABEL_0""", """score""": 0.5_0_4}]		)

            lowercase														=			text_classifier("""This is great !"""	, return_all_scores=__lowerCAmelCase		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, [[{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}]]		)

            lowercase														=			text_classifier(["""This is great !""", """Something else"""]	, return_all_scores=__lowerCAmelCase		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, [
                    [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}],
                    [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}],
                ]	, )

            lowercase														=			text_classifier(["""This is great !""", """Something else"""]	, return_all_scores=__lowerCAmelCase		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, [
                    {"""label""": """LABEL_0""", """score""": 0.5_0_4},
                    {"""label""": """LABEL_0""", """score""": 0.5_0_4},
                ]	, )

      @require_torch
      def        A__ (		self		):







            """simple docstring"""



            import torch

            lowercase														=			pipeline(
                task="""text-classification"""	, model="""hf-internal-testing/tiny-random-distilbert"""	, framework="""pt"""	, device=torch.device("""cpu"""		)	, )

            lowercase														=			text_classifier("""This is great !"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """LABEL_0""", """score""": 0.5_0_4}]		)

      @require_tf
      def        A__ (		self		):







            """simple docstring"""



            lowercase														=			pipeline(
                task="""text-classification"""	, model="""hf-internal-testing/tiny-random-distilbert"""	, framework="""tf"""		)

            lowercase														=			text_classifier("""This is great !"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """LABEL_0""", """score""": 0.5_0_4}]		)

      @slow
      @require_torch
      def        A__ (		self		):







            """simple docstring"""



            lowercase														=			pipeline("""text-classification"""		)

            lowercase														=			text_classifier("""This is great !"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """POSITIVE""", """score""": 1.0}]		)
            lowercase														=			text_classifier("""This is bad !"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """NEGATIVE""", """score""": 1.0}]		)
            lowercase														=			text_classifier("""Birds are a type of animal"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """POSITIVE""", """score""": 0.9_8_8}]		)

      @slow
      @require_tf
      def        A__ (		self		):







            """simple docstring"""



            lowercase														=			pipeline("""text-classification"""	, framework="""tf"""		)

            lowercase														=			text_classifier("""This is great !"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """POSITIVE""", """score""": 1.0}]		)
            lowercase														=			text_classifier("""This is bad !"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """NEGATIVE""", """score""": 1.0}]		)
            lowercase														=			text_classifier("""Birds are a type of animal"""		)
            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": """POSITIVE""", """score""": 0.9_8_8}]		)

      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase	, __lowerCAmelCase		):







            """simple docstring"""



            lowercase														=			TextClassificationPipeline(model=__lowerCAmelCase	, tokenizer=__lowerCAmelCase		)
            return text_classifier, ["HuggingFace is in", "This is another test"]







      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase		):







            """simple docstring"""



            lowercase														=			text_classifier.model
            # Small inputs because BartTokenizer tiny has maximum position embeddings = 22
            lowercase														=			"""HuggingFace is in"""
            lowercase														=			text_classifier(__lowerCAmelCase		)

            self.assertEqual(nested_simplify(__lowerCAmelCase		)	, [{"""label""": ANY(__lowerCAmelCase		), """score""": ANY(__lowerCAmelCase		)}]		)
            self.assertTrue(outputs[0]["""label"""] in model.config.idalabel.values()		)

            lowercase														=			["""HuggingFace is in """, """Paris is in France"""]
            lowercase														=			text_classifier(__lowerCAmelCase		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, [{"""label""": ANY(__lowerCAmelCase		), """score""": ANY(__lowerCAmelCase		)}, {"""label""": ANY(__lowerCAmelCase		), """score""": ANY(__lowerCAmelCase		)}]	, )
            self.assertTrue(outputs[0]["""label"""] in model.config.idalabel.values()		)
            self.assertTrue(outputs[1]["""label"""] in model.config.idalabel.values()		)

            # Forcing to get all results with `top_k=None`
            # This is NOT the legacy format
            lowercase														=			text_classifier(__lowerCAmelCase	, top_k=__lowerCAmelCase		)
            lowercase														=			len(model.config.idalabel.values()		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, [[{"""label""": ANY(__lowerCAmelCase		), """score""": ANY(__lowerCAmelCase		)}] * N, [{"""label""": ANY(__lowerCAmelCase		), """score""": ANY(__lowerCAmelCase		)}] * N]	, )

            lowercase														=			{"""text""": """HuggingFace is in """, """text_pair""": """Paris is in France"""}
            lowercase														=			text_classifier(__lowerCAmelCase		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, {"""label""": ANY(__lowerCAmelCase		), """score""": ANY(__lowerCAmelCase		)}	, )
            self.assertTrue(outputs["""label"""] in model.config.idalabel.values()		)

            # This might be used a text pair, but tokenizer + pipe interaction
            # makes it hard to understand that it's not using the pair properly
            # https://github.com/huggingface/transformers/issues/17305
            # We disabled this usage instead as it was outputting wrong outputs.
            lowercase														=			[["""HuggingFace is in """, """Paris is in France"""]]
            with self.assertRaises(__lowerCAmelCase		):
                  text_classifier(__lowerCAmelCase		)

            # This used to be valid for doing text pairs
            # We're keeping it working because of backward compatibility
            lowercase														=			text_classifier([[["""HuggingFace is in """, """Paris is in France"""]]]		)
            self.assertEqual(
                nested_simplify(__lowerCAmelCase		)	, [{"""label""": ANY(__lowerCAmelCase		), """score""": ANY(__lowerCAmelCase		)}]	, )
            self.assertTrue(outputs[0]["""label"""] in model.config.idalabel.values()		)



