





"""simple docstring"""






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


lowerCAmelCase_			=							logging.get_logger(__name__)

lowerCAmelCase_			=							{
    '''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 	lowerCAmelCase					(      snake_case							):
       lowerCAmelCase__						 =  """glpn"""






       def __init__(   self    ,  a__=3    ,  a__=4    ,  a__=[2, 2, 2, 2]    ,  a__=[8, 4, 2, 1]    ,  a__=[32, 64, 1_60, 2_56]    ,  a__=[7, 3, 3, 3]    ,  a__=[4, 2, 2, 2]    ,  a__=[1, 2, 5, 8]    ,  a__=[4, 4, 4, 4]    ,  a__="gelu"    ,  a__=0.0    ,  a__=0.0    ,  a__=0.02    ,  a__=0.1    ,  a__=1E-6    ,  a__=64    ,  a__=10    ,  a__=-1    ,  **a__    ,  ):
              super().__init__(**a__     )

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













"""simple docstring"""






import unittest

from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow


if is_flax_available():
    import optax
    from flax.training.common_utils import onehot

    from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
    from transformers.models.ta.modeling_flax_ta import shift_tokens_right



@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class 	lowerCAmelCase					(      unittest.TestCase							):






       @slow
       def 							__A (   self     ):
              _UpperCAmelCase     =     FlaxMTaForConditionalGeneration.from_pretrained('google/mt5-small'     )
              _UpperCAmelCase     =     AutoTokenizer.from_pretrained('google/mt5-small'     )

              _UpperCAmelCase     =     tokenizer('Hello there'    ,  return_tensors='np'     ).input_ids
              _UpperCAmelCase     =     tokenizer('Hi I am'    ,  return_tensors='np'     ).input_ids

              _UpperCAmelCase     =     shift_tokens_right(a__    ,  model.config.pad_token_id    ,  model.config.decoder_start_token_id     )

              _UpperCAmelCase     =     model(a__    ,  decoder_input_ids=a__     ).logits
              _UpperCAmelCase     =     optax.softmax_cross_entropy(a__    ,  onehot(a__    ,  logits.shape[-1]     )     ).mean()

              _UpperCAmelCase     =     -(labels.shape[-1] * loss.item())

              _UpperCAmelCase     =     -84.9_127
              self.assertTrue(abs(mtf_score - EXPECTED_SCORE     ) < 1E-4     )






