





import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference




@slow
@require_torch_gpu
class  __UpperCamelCase						(       unittest.TestCase						):





     def 		UpperCamelCase(    self				):
        _UpperCAmelCase											=      '''runwayml/stable-diffusion-v1-5'''
        _UpperCAmelCase											=      TextToVideoZeroPipeline.from_pretrained(_UpperCamelCase							,       torch_dtype=torch.floataa				).to('''cuda'''				)
        _UpperCAmelCase											=      DDIMScheduler.from_config(pipe.scheduler.config				)
        _UpperCAmelCase											=      torch.Generator(device='''cuda'''				).manual_seed(0				)

        _UpperCAmelCase											=      '''A bear is playing a guitar on Times Square'''
        _UpperCAmelCase											=      pipe(prompt=_UpperCamelCase							,       generator=_UpperCamelCase				).images

        _UpperCAmelCase											=      load_pt(
            '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt'''				)

        assert_mean_pixel_difference(_UpperCamelCase							,       _UpperCamelCase				)






from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

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


if TYPE_CHECKING:
   from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


UpperCAmelCase_											=  logging.get_logger(__name__)

UpperCAmelCase_											=  {
    "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/config.json",
    "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/config.json",
    "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json",
    "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json",
    "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json",
    "microsoft/deberta-xlarge-mnli": "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json",
}




class  __UpperCamelCase						(       A__						):
     __A  :     Dict            =      """deberta"""





     def __init__(    self							,       _UpperCamelCase=50265							,       _UpperCamelCase=768							,       _UpperCamelCase=12							,       _UpperCamelCase=12							,       _UpperCamelCase=3072							,       _UpperCamelCase="gelu"							,       _UpperCamelCase=0.1							,       _UpperCamelCase=0.1							,       _UpperCamelCase=512							,       _UpperCamelCase=0							,       _UpperCamelCase=0.02							,       _UpperCamelCase=1e-7							,       _UpperCamelCase=False							,       _UpperCamelCase=-1							,       _UpperCamelCase=0							,       _UpperCamelCase=True							,       _UpperCamelCase=None							,       _UpperCamelCase=0							,       _UpperCamelCase="gelu"							,       **_UpperCamelCase							,       ):
        super().__init__(**_UpperCamelCase				)

        _UpperCAmelCase											=      hidden_size
        _UpperCAmelCase											=      num_hidden_layers
        _UpperCAmelCase											=      num_attention_heads
        _UpperCAmelCase											=      intermediate_size
        _UpperCAmelCase											=      hidden_act
        _UpperCAmelCase											=      hidden_dropout_prob
        _UpperCAmelCase											=      attention_probs_dropout_prob
        _UpperCAmelCase											=      max_position_embeddings
        _UpperCAmelCase											=      type_vocab_size
        _UpperCAmelCase											=      initializer_range
        _UpperCAmelCase											=      relative_attention
        _UpperCAmelCase											=      max_relative_positions
        _UpperCAmelCase											=      pad_token_id
        _UpperCAmelCase											=      position_biased_input

        # Backwards compatibility
        if type(_UpperCamelCase				) == str:
           _UpperCAmelCase											=      [x.strip() for x in pos_att_type.lower().split('''|'''				)]

        _UpperCAmelCase											=      pos_att_type
        _UpperCAmelCase											=      vocab_size
        _UpperCAmelCase											=      layer_norm_eps

        _UpperCAmelCase											=      kwargs.get('''pooler_hidden_size'''							,       _UpperCamelCase				)
        _UpperCAmelCase											=      pooler_dropout
        _UpperCAmelCase											=      pooler_hidden_act




class  __UpperCamelCase						(       A__						):





     @property
     def 		UpperCamelCase(    self				):
        if self.task == "multiple-choice":
           _UpperCAmelCase											=      {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
        else:
           _UpperCAmelCase											=      {0: '''batch''', 1: '''sequence'''}
        if self._config.type_vocab_size > 0:
           return OrderedDict(
               [('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis), ('''token_type_ids''', dynamic_axis)]				)
        else:
           return OrderedDict([('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis)]				)





     @property
     def 		UpperCamelCase(    self				):
        return 12





     def 		UpperCamelCase(    self							,       _UpperCamelCase							,       _UpperCamelCase = -1							,       _UpperCamelCase = -1							,       _UpperCamelCase = -1							,       _UpperCamelCase = False							,       _UpperCamelCase = None							,       _UpperCamelCase = 3							,       _UpperCamelCase = 40							,       _UpperCamelCase = 40							,       _UpperCamelCase = None							,       ):
        _UpperCAmelCase											=      super().generate_dummy_inputs(preprocessor=_UpperCamelCase							,       framework=_UpperCamelCase				)
        if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
           del dummy_inputs["token_type_ids"]
        return dummy_inputs