(in module torch.cuda) ](cuda.html#torch.cuda.manual_seed_all)
  * [ map_() (torch.Tensor method) ](tensors.html#torch.Tensor.map_)
  * [ margin_ranking_loss() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.margin_ranking_loss)
  * [ MarginRankingLoss (class in torch.nn) ](generated/torch.nn.MarginRankingLoss.html#torch.nn.MarginRankingLoss)
  * [ mark() (in module torch.cuda.nvtx) ](cuda.html#torch.cuda.nvtx.mark)
  * [ mark_dirty() (torch.autograd.function._ContextMethodMixin method) ](autograd.html#torch.autograd.function._ContextMethodMixin.mark_dirty)
  * [ mark_non_differentiable() (torch.autograd.function._ContextMethodMixin method) ](autograd.html#torch.autograd.function._ContextMethodMixin.mark_non_differentiable)
  * [ masked_fill() (torch.Tensor method) ](tensors.html#torch.Tensor.masked_fill)
  * [ masked_fill_() (torch.Tensor method) ](tensors.html#torch.Tensor.masked_fill_)
  * [ masked_scatter() (torch.Tensor method) ](tensors.html#torch.Tensor.masked_scatter)
  * [ masked_scatter_() (torch.Tensor method) ](tensors.html#torch.Tensor.masked_scatter_)
  * [ masked_select() (in module torch) ](generated/torch.masked_select.html#torch.masked_select)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.masked_select)
  * [ maskrcnn_resnet50_fpn() (in module torchvision.models.detection) ](torchvision/models.html#torchvision.models.detection.maskrcnn_resnet50_fpn)
  * [ matmul() (in module torch) ](generated/torch.matmul.html#torch.matmul)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.matmul)
  * [ matrix_power() (in module torch) ](generated/torch.matrix_power.html#torch.matrix_power)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.matrix_power)
  * [ matrix_rank() (in module torch) ](generated/torch.matrix_rank.html#torch.matrix_rank)
  * [ max() (in module torch) ](generated/torch.max.html#torch.max) , [ [1] ](generated/torch.max.html#torch.max) , [ [2] ](generated/torch.max.html#torch.max)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.max)
  * [ max_memory_allocated() (in module torch.cuda) ](cuda.html#torch.cuda.max_memory_allocated)
  * [ max_memory_cached() (in module torch.cuda) ](cuda.html#torch.cuda.max_memory_cached)
  * [ max_memory_reserved() (in module torch.cuda) ](cuda.html#torch.cuda.max_memory_reserved)
  * [ max_pool1d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.max_pool1d)
  * [ max_pool2d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.max_pool2d)
    * [ (in module torch.nn.quantized.functional) ](quantization.html#torch.nn.quantized.functional.max_pool2d)
  * [ max_pool3d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.max_pool3d)
  * [ max_unpool1d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.max_unpool1d)
  * [ max_unpool2d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.max_unpool2d)
  * [ max_unpool3d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.max_unpool3d)
  * [ MaxPool1d (class in torch.nn) ](generated/torch.nn.MaxPool1d.html#torch.nn.MaxPool1d)
  * [ MaxPool2d (class in torch.nn) ](generated/torch.nn.MaxPool2d.html#torch.nn.MaxPool2d)
  * [ MaxPool3d (class in torch.nn) ](generated/torch.nn.MaxPool3d.html#torch.nn.MaxPool3d)
  * [ MaxUnpool1d (class in torch.nn) ](generated/torch.nn.MaxUnpool1d.html#torch.nn.MaxUnpool1d)
  * [ MaxUnpool2d (class in torch.nn) ](generated/torch.nn.MaxUnpool2d.html#torch.nn.MaxUnpool2d)
  * [ MaxUnpool3d (class in torch.nn) ](generated/torch.nn.MaxUnpool3d.html#torch.nn.MaxUnpool3d)
  * [ mc3_18() (in module torchvision.models.video) ](torchvision/models.html#torchvision.models.video.mc3_18)
  * [ mean() (in module torch) ](generated/torch.mean.html#torch.mean) , [ [1] ](generated/torch.mean.html#torch.mean)
    * [ (torch.distributions.bernoulli.Bernoulli property) ](distributions.html#torch.distributions.bernoulli.Bernou