
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__magic_name__           =					logging.get_logger(__name__)

__magic_name__           =					{
    '''apple/mobilevit-small''': '''https://huggingface.co/apple/mobilevit-small/resolve/main/config.json''',
    '''apple/mobilevit-x-small''': '''https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json''',
    '''apple/mobilevit-xx-small''': '''https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json''',
    '''apple/deeplabv3-mobilevit-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json'''
    ),
    '''apple/deeplabv3-mobilevit-x-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json'''
    ),
    '''apple/deeplabv3-mobilevit-xx-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json'''
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}




class    _SCREAMING_SNAKE_CASE					( __UpperCamelCase	):
     _A  :						Union[str, Any]      		=       'mobilevit'
     def __init__(     self						,		lowerCamelCase=3						,		lowerCamelCase=2_56						,		lowerCamelCase=2						,		lowerCamelCase=[1_44, 1_92, 2_40]						,		lowerCamelCase=[16, 32, 64, 96, 1_28, 1_60, 6_40]						,		lowerCamelCase=4						,		lowerCamelCase=2.0						,		lowerCamelCase=4.0						,		lowerCamelCase="silu"						,		lowerCamelCase=3						,		lowerCamelCase=32						,		lowerCamelCase=0.1						,		lowerCamelCase=0.0						,		lowerCamelCase=0.1						,		lowerCamelCase=0.0_2						,		lowerCamelCase=1e-5						,		lowerCamelCase=True						,		lowerCamelCase=2_56						,		lowerCamelCase=[6, 12, 18]						,		lowerCamelCase=0.1						,		lowerCamelCase=2_55						,		**lowerCamelCase						,		):
         super().__init__(**lowerCamelCase	)

         snake_case__  =			num_channels
         snake_case__  =			image_size
         snake_case__  =			patch_size
         snake_case__  =			hidden_sizes
         snake_case__  =			neck_hidden_sizes
         snake_case__  =			num_attention_heads
         snake_case__  =			mlp_ratio
         snake_case__  =			expand_ratio
         snake_case__  =			hidden_act
         snake_case__  =			conv_kernel_size
         snake_case__  =			output_stride
         snake_case__  =			hidden_dropout_prob
         snake_case__  =			attention_probs_dropout_prob
         snake_case__  =			classifier_dropout_prob
         snake_case__  =			initializer_range
         snake_case__  =			layer_norm_eps
         snake_case__  =			qkv_bias

         # decode head attributes for semantic segmentation
         snake_case__  =			aspp_out_channels
         snake_case__  =			atrous_rates
         snake_case__  =			aspp_dropout_prob
         snake_case__  =			semantic_loss_ignore_index





class    _SCREAMING_SNAKE_CASE					( __UpperCamelCase	):
     _A  :						Tuple      		=       version.parse('1.11'	)
     @property
     def A_     (     self	):
         return OrderedDict([("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"})]	)
     @property
     def A_     (     self	):
         if self.task == "image-classification":
             return OrderedDict([("logits", {0: "batch"})]	)
         else:
             return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]	)



     @property
     def A_     (     self	):
         return 1e-4





import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
     from PIL import Image




class    _SCREAMING_SNAKE_CASE					( unittest.TestCase    ,   __UpperCamelCase	):
      def A_     (     self	):
          snake_case__  =			load_tool("image-captioning"	)
          self.tool.setup()
          snake_case__  =			load_tool("image-captioning"						,		remote=lowerCamelCase	)
      def A_     (     self	):
          snake_case__  =			Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"	)	) / "000000039769.png"	)
          snake_case__  =			self.tool(lowerCamelCase	)
          self.assertEqual(lowerCamelCase						,		"two cats sleeping on a couch"	)
      def A_     (     self	):
          snake_case__  =			Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"	)	) / "000000039769.png"	)
          snake_case__  =			self.remote_tool(lowerCamelCase	)
          self.assertEqual(lowerCamelCase						,		"two cats sleeping on a couch"	)
      def A_     (     self	):
          snake_case__  =			Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"	)	) / "000000039769.png"	)
          snake_case__  =			self.tool(image=lowerCamelCase	)
          self.assertEqual(lowerCamelCase						,		"two cats sleeping on a couch"	)



      def A_     (     self	):
          snake_case__  =			Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"	)	) / "000000039769.png"	)
          snake_case__  =			self.remote_tool(image=lowerCamelCase	)
          self.assertEqual(lowerCamelCase						,		"two cats sleeping on a couch"	)



