code: def scaled_dot_product_attention_v_2p0p0_and_above(
      q,
      k,
      v,
      scale: float,
      /,
      *,
      mask=None,
      out=None,
  ):
      if isinstance(mask, torch.Tensor):
          mask = torch.where(mask == 0, -torch.inf, 0)
      return torch.nn.functional.scaled_dot_product_attention(
          q, k, v, attn_mask=mask
      )
  
imports: from typing import Optional, Tuple, Union, Sequence
  import torch
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  from ivy.functional.ivy.layers import _get_embed_dim, _handle_padding, _deconv_length
label_desc: Use image node_id 20 for calling a global function with example usage: scaled_dot_product_attention_v_2p0p0_and_above() and returns: torch