.TransformerDecoderLayer method) ](generated/torch.nn.TransformerDecoderLayer.html#torch.nn.TransformerDecoderLayer.forward)
    * [ (torch.nn.TransformerEncoder method) ](generated/torch.nn.TransformerEncoder.html#torch.nn.TransformerEncoder.forward)
    * [ (torch.nn.TransformerEncoderLayer method) ](generated/torch.nn.TransformerEncoderLayer.html#torch.nn.TransformerEncoderLayer.forward)
  * [ frac() (in module torch) ](generated/torch.frac.html#torch.frac)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.frac)
  * [ frac_() (torch.Tensor method) ](tensors.html#torch.Tensor.frac_)
  * [ FractionalMaxPool2d (class in torch.nn) ](generated/torch.nn.FractionalMaxPool2d.html#torch.nn.FractionalMaxPool2d)
  * [ freeze() (in module torch.jit) ](generated/torch.jit.freeze.html#torch.jit.freeze)
  * [ from_buffer() (torch.FloatStorage static method) ](storage.html#torch.FloatStorage.from_buffer)
  * [ from_dlpack() (in module torch.utils.dlpack) ](dlpack.html#torch.utils.dlpack.from_dlpack)
  * [ from_file() (torch.FloatStorage static method) ](storage.html#torch.FloatStorage.from_file)
  * [ from_float() (torch.nn.qat.Conv2d class method) ](quantization.html#torch.nn.qat.Conv2d.from_float)
    * [ (torch.nn.qat.Linear class method) ](quantization.html#torch.nn.qat.Linear.from_float)
    * [ (torch.nn.quantized.Conv1d class method) ](quantization.html#torch.nn.quantized.Conv1d.from_float)
    * [ (torch.nn.quantized.Conv2d class method) ](quantization.html#torch.nn.quantized.Conv2d.from_float)
    * [ (torch.nn.quantized.Conv3d class method) ](quantization.html#torch.nn.quantized.Conv3d.from_float)
    * [ (torch.nn.quantized.dynamic.Linear class method) ](quantization.html#torch.nn.quantized.dynamic.Linear.from_float)
    * [ (torch.nn.quantized.Linear class method) ](quantization.html#torch.nn.quantized.Linear.from_float)
  * [ from_ipc_handle() (torch.cuda.Event class method) ](cuda.html#torch.cuda.Event.from_ipc_handle)
  * [ from_numpy() (in module torch) ](generated/torch.from_numpy.html#torch.from_numpy)
  * [ from_pretrained() (torch.nn.Embedding class method) ](generated/torch.nn.Embedding.html#torch.nn.Embedding.from_pretrained)
    * [ (torch.nn.EmbeddingBag class method) ](generated/torch.nn.EmbeddingBag.html#torch.nn.EmbeddingBag.from_pretrained)
  * [ full() (in module torch) ](generated/torch.full.html#torch.full)
  * [ full_like() (in module torch) ](generated/torch.full_like.html#torch.full_like)
  * [ Function (class in torch.autograd) ](autograd.html#torch.autograd.Function)
  * [ fuse_modules() (in module torch.quantization) ](quantization.html#torch.quantization.fuse_modules)
  * [ Future (class in torch.futures) ](futures.html#torch.futures.Future)

  
---|---  
  
##  G

  * [ Gamma (class in torch.distributions.gamma) ](distributions.html#torch.distributions.gamma.Gamma)
  * [ gather() (in module torch) ](generated/torch.gather.html#torch.gather)
    * [ (in module torch.cuda.comm) ](cuda.html#torch.cuda.comm.gather)
    * [ (in module torch.distributed) ](distributed.html#torch.distributed.gather)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.gather)
  * [ ge() (in module torch) ](generated/torch.ge.html#torch.ge)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.ge)
  * [ ge_() (torch.Tensor method) ](tensors.html#torch.Tensor.ge_)
  * [ GELU (class in torch.nn) ](generated/torch.nn.GELU.html#torch.nn.GELU)
  * [ gelu() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.gelu)
  * [ generate_square_subsequent_mask() (torch.nn.Transformer method) ](generated/torch.nn.Transformer.html#torch.nn.Transformer.generate_square_subsequent_mask)
  * [ Generator (class in torch) ](generated/torch.Generator.html#torch.Generator)
  * [ Geometric (class in torch.distributions.geometric) ](distributions.html#torch.distributions.geometric.Geometric)
  * [ geometric_() (torch.Tensor method) ](tensors.html#torch.Tensor.geometric_)
  * [ geqrf() (in module torch) ](generated/