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<li class="toctree-l1"><a class="reference internal" href="notes/amp_examples.html">Automatic Mixed Precision examples</a></li>
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<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="torchvision/datasets.html#torchvision.datasets.CIFAR10.__getitem__">__getitem__() (torchvision.datasets.CIFAR10 method)</a>
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<li><a href="torchvision/datasets.html#torchvision.datasets.Cityscapes.__getitem__">(torchvision.datasets.Cityscapes method)</a>
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<li><a href="torchvision/datasets.html#torchvision.datasets.STL10.__getitem__">(torchvision.datasets.STL10 method)</a>
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<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.__init__">__init__() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
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<li><a href="sparse.html#torch.sparse.FloatTensor._indices">_indices() (torch.sparse.FloatTensor method)</a>
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<li><a href="sparse.html#torch.sparse.FloatTensor._nnz">_nnz() (torch.sparse.FloatTensor method)</a>
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<li><a href="sparse.html#torch.sparse.FloatTensor._values">_values() (torch.sparse.FloatTensor method)</a>
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<h2 id="A">A</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="generated/torch.abs.html#torch.abs">abs() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.abs">(torch.Tensor method)</a>
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<li><a href="tensors.html#torch.Tensor.abs_">abs_() (torch.Tensor method)</a>
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<li><a href="generated/torch.absolute.html#torch.absolute">absolute() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.absolute">(torch.Tensor method)</a>
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<li><a href="tensors.html#torch.Tensor.absolute_">absolute_() (torch.Tensor method)</a>
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<li><a href="distributions.html#torch.distributions.transforms.AbsTransform">AbsTransform (class in torch.distributions.transforms)</a>
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<li><a href="generated/torch.acos.html#torch.acos">acos() (in module torch)</a>
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<li><a href="tensors.html#torch.Tensor.acos">(torch.Tensor method)</a>
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<li><a href="tensors.html#torch.Tensor.acos_">acos_() (torch.Tensor method)</a>
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<li><a href="generated/torch.acosh.html#torch.acosh">acosh() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.acosh">(torch.Tensor method)</a>
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<li><a href="tensors.html#torch.Tensor.acosh_">acosh_() (torch.Tensor method)</a>
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<li><a href="optim.html#torch.optim.Adadelta">Adadelta (class in torch.optim)</a>
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<li><a href="optim.html#torch.optim.Adagrad">Adagrad (class in torch.optim)</a>
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<li><a href="optim.html#torch.optim.Adam">Adam (class in torch.optim)</a>
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<li><a href="optim.html#torch.optim.Adamax">Adamax (class in torch.optim)</a>
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<li><a href="optim.html#torch.optim.AdamW">AdamW (class in torch.optim)</a>
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<li><a href="nn.functional.html#torch.nn.functional.adaptive_avg_pool1d">adaptive_avg_pool1d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.functional.html#torch.nn.functional.adaptive_avg_pool2d">adaptive_avg_pool2d() (in module torch.nn.functional)</a>
<ul>
<li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.adaptive_avg_pool2d">(in module torch.nn.quantized.functional)</a>
</li>
</ul></li>
<li><a href="nn.functional.html#torch.nn.functional.adaptive_avg_pool3d">adaptive_avg_pool3d() (in module torch.nn.functional)</a>
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<li><a href="nn.functional.html#torch.nn.functional.adaptive_max_pool1d">adaptive_max_pool1d() (in module torch.nn.functional)</a>
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<li><a href="nn.functional.html#torch.nn.functional.adaptive_max_pool2d">adaptive_max_pool2d() (in module torch.nn.functional)</a>
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<li><a href="nn.functional.html#torch.nn.functional.adaptive_max_pool3d">adaptive_max_pool3d() (in module torch.nn.functional)</a>
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<li><a href="generated/torch.nn.AdaptiveAvgPool1d.html#torch.nn.AdaptiveAvgPool1d">AdaptiveAvgPool1d (class in torch.nn)</a>
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<li><a href="generated/torch.nn.AdaptiveAvgPool3d.html#torch.nn.AdaptiveAvgPool3d">AdaptiveAvgPool3d (class in torch.nn)</a>
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<li><a href="generated/torch.nn.AdaptiveLogSoftmaxWithLoss.html#torch.nn.AdaptiveLogSoftmaxWithLoss">AdaptiveLogSoftmaxWithLoss (class in torch.nn)</a>
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<li><a href="generated/torch.nn.AdaptiveMaxPool1d.html#torch.nn.AdaptiveMaxPool1d">AdaptiveMaxPool1d (class in torch.nn)</a>
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<li><a href="generated/torch.nn.AdaptiveMaxPool2d.html#torch.nn.AdaptiveMaxPool2d">AdaptiveMaxPool2d (class in torch.nn)</a>
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<li><a href="generated/torch.nn.AdaptiveMaxPool3d.html#torch.nn.AdaptiveMaxPool3d">AdaptiveMaxPool3d (class in torch.nn)</a>
</li>
<li><a href="generated/torch.add.html#torch.add">add() (in module torch)</a>, <a href="generated/torch.add.html#torch.add">[1]</a>
<ul>
<li><a href="distributed.html#torch.distributed.Store.add">(in module torch.distributed.Store)</a>
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<li><a href="sparse.html#torch.sparse.FloatTensor.add">(torch.sparse.FloatTensor method)</a>
</li>
<li><a href="tensors.html#torch.Tensor.add">(torch.Tensor method)</a>
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</ul></li>
<li><a href="sparse.html#torch.sparse.FloatTensor.add_">add_() (torch.sparse.FloatTensor method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.add_">(torch.Tensor method)</a>
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<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_audio">add_audio() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
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<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_figure">add_figure() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
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<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_graph">add_graph() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
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<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_histogram">add_histogram() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
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<li><a href="torch.quantization.html#torch.quantization.add_observer_">add_observer_() (in module torch.quantization)</a>
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<li><a href="optim.html#torch.optim.Optimizer.add_param_group">add_param_group() (torch.optim.Optimizer method)</a>
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<li><a href="torch.quantization.html#torch.quantization.add_quant_dequant">add_quant_dequant() (in module torch.quantization)</a>
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<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_scalar">add_scalar() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
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<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_scalars">add_scalars() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
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<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_text">add_text() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
<li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_video">add_video() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
<li><a href="generated/torch.addbmm.html#torch.addbmm">addbmm() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addbmm">(torch.Tensor method)</a>
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<li><a href="tensors.html#torch.Tensor.addbmm_">addbmm_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.addcdiv.html#torch.addcdiv">addcdiv() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addcdiv">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.addcdiv_">addcdiv_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.addcmul.html#torch.addcmul">addcmul() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addcmul">(torch.Tensor method)</a>
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</ul></li>
<li><a href="tensors.html#torch.Tensor.addcmul_">addcmul_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.addmm.html#torch.addmm">addmm() (in module torch)</a>
<ul>
<li><a href="sparse.html#torch.sparse.addmm">(in module torch.sparse)</a>
</li>
<li><a href="tensors.html#torch.Tensor.addmm">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.addmm_">addmm_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.addmv.html#torch.addmv">addmv() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addmv">(torch.Tensor method)</a>
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</ul></li>
<li><a href="tensors.html#torch.Tensor.addmv_">addmv_() (torch.Tensor method)</a>
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<li><a href="generated/torch.addr.html#torch.addr">addr() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addr">(torch.Tensor method)</a>
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<li><a href="tensors.html#torch.Tensor.addr_">addr_() (torch.Tensor method)</a>
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<li><a href="torchvision/transforms.html#torchvision.transforms.functional.adjust_brightness">adjust_brightness() (in module torchvision.transforms.functional)</a>
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<li><a href="torchvision/transforms.html#torchvision.transforms.functional.adjust_contrast">adjust_contrast() (in module torchvision.transforms.functional)</a>
</li>
<li><a href="torchvision/transforms.html#torchvision.transforms.functional.adjust_gamma">adjust_gamma() (in module torchvision.transforms.functional)</a>
</li>
<li><a href="torchvision/transforms.html#torchvision.transforms.functional.adjust_hue">adjust_hue() (in module torchvision.transforms.functional)</a>
</li>
<li><a href="torchvision/transforms.html#torchvision.transforms.functional.adjust_saturation">adjust_saturation() (in module torchvision.transforms.functional)</a>
</li>
<li><a href="torchvision/transforms.html#torchvision.transforms.functional.affine">affine() (in module torchvision.transforms.functional)</a>
</li>
<li><a href="nn.functional.html#torch.nn.functional.affine_grid">affine_grid() (in module torch.nn.functional)</a>
</li>
<li><a href="distributions.html#torch.distributions.transforms.AffineTransform">AffineTransform (class in torch.distributions.transforms)</a>
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<li><a href="torchvision/models.html#torchvision.models.alexnet">alexnet() (in module torchvision.models)</a>
</li>
<li><a href="named_tensor.html#torch.Tensor.align_as">align_as() (torch.Tensor method)</a>
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<li><a href="named_tensor.html#torch.Tensor.align_to">align_to() (torch.Tensor method)</a>
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<li><a href="tensors.html#torch.BoolTensor.all">all() (torch.BoolTensor method)</a>
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<li><a href="distributed.html#torch.distributed.all_gather">all_gather() (in module torch.distributed)</a>
</li>
<li><a href="distributed.html#torch.distributed.all_gather_multigpu">all_gather_multigpu() (in module torch.distributed)</a>
</li>
<li><a href="distributed.html#torch.distributed.all_reduce">all_reduce() (in module torch.distributed)</a>
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<li><a href="distributed.html#torch.distributed.all_reduce_multigpu">all_reduce_multigpu() (in module torch.distributed)</a>
</li>
<li><a href="distributed.html#torch.distributed.all_to_all">all_to_all() (in module torch.distributed)</a>
</li>
<li><a href="generated/torch.allclose.html#torch.allclose">allclose() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.allclose">(torch.Tensor method)</a>
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<li><a href="backends.html#torch.backends.cuda.matmul.allow_tf32">allow_tf32 (torch.backends.cuda.matmul attribute)</a>
<ul>
<li><a href="backends.html#torch.backends.cudnn.allow_tf32">(torch.backends.cudnn attribute)</a>
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<li><a href="nn.functional.html#torch.nn.functional.alpha_dropout">alpha_dropout() (in module torch.nn.functional)</a>
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<li><a href="generated/torch.nn.AlphaDropout.html#torch.nn.AlphaDropout">AlphaDropout (class in torch.nn)</a>
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<li><a href="generated/torch.amax.html#torch.amax">amax() (in module torch)</a>
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<li><a href="tensors.html#torch.Tensor.amax">(torch.Tensor method)</a>
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<li><a href="generated/torch.amin.html#torch.amin">amin() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.amin">(torch.Tensor method)</a>
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</ul></li>
<li><a href="generated/torch.angle.html#torch.angle">angle() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.angle">(torch.Tensor method)</a>
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</ul></li>
<li><a href="tensors.html#torch.BoolTensor.any">any() (torch.BoolTensor method)</a>
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<li><a href="generated/torch.nn.ModuleList.html#torch.nn.ModuleList.append">append() (torch.nn.ModuleList method)</a>
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<li><a href="generated/torch.nn.ParameterList.html#torch.nn.ParameterList.append">(torch.nn.ParameterList method)</a>
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</ul></li>
<li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.apply">apply() (torch.jit.ScriptModule method)</a>
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<li><a href="generated/torch.nn.Flatten.html#torch.nn.Flatten.apply">(torch.nn.Flatten method)</a>
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<li><a href="generated/torch.nn.Module.html#torch.nn.Module.apply">(torch.nn.Module method)</a>
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<li><a href="generated/torch.nn.Unflatten.html#torch.nn.Unflatten.apply">(torch.nn.Unflatten method)</a>
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<li><a href="generated/torch.nn.utils.prune.BasePruningMethod.html#torch.nn.utils.prune.BasePruningMethod.apply">(torch.nn.utils.prune.BasePruningMethod class method)</a>
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<li><a href="generated/torch.nn.utils.prune.CustomFromMask.html#torch.nn.utils.prune.CustomFromMask.apply">(torch.nn.utils.prune.CustomFromMask class method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.Identity.html#torch.nn.utils.prune.Identity.apply">(torch.nn.utils.prune.Identity class method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.L1Unstructured.html#torch.nn.utils.prune.L1Unstructured.apply">(torch.nn.utils.prune.L1Unstructured class method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.LnStructured.html#torch.nn.utils.prune.LnStructured.apply">(torch.nn.utils.prune.LnStructured class method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer.apply">(torch.nn.utils.prune.PruningContainer class method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.RandomStructured.html#torch.nn.utils.prune.RandomStructured.apply">(torch.nn.utils.prune.RandomStructured class method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.RandomUnstructured.html#torch.nn.utils.prune.RandomUnstructured.apply">(torch.nn.utils.prune.RandomUnstructured class method)</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="tensors.html#torch.Tensor.apply_">apply_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.BasePruningMethod.html#torch.nn.utils.prune.BasePruningMethod.apply_mask">apply_mask() (torch.nn.utils.prune.BasePruningMethod method)</a>
<ul>
<li><a href="generated/torch.nn.utils.prune.CustomFromMask.html#torch.nn.utils.prune.CustomFromMask.apply_mask">(torch.nn.utils.prune.CustomFromMask method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.Identity.html#torch.nn.utils.prune.Identity.apply_mask">(torch.nn.utils.prune.Identity method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.L1Unstructured.html#torch.nn.utils.prune.L1Unstructured.apply_mask">(torch.nn.utils.prune.L1Unstructured method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.LnStructured.html#torch.nn.utils.prune.LnStructured.apply_mask">(torch.nn.utils.prune.LnStructured method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer.apply_mask">(torch.nn.utils.prune.PruningContainer method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.RandomStructured.html#torch.nn.utils.prune.RandomStructured.apply_mask">(torch.nn.utils.prune.RandomStructured method)</a>
</li>
<li><a href="generated/torch.nn.utils.prune.RandomUnstructured.html#torch.nn.utils.prune.RandomUnstructured.apply_mask">(torch.nn.utils.prune.RandomUnstructured method)</a>
</li>
</ul></li>
<li><a href="generated/torch.arange.html#torch.arange">arange() (in module torch)</a>
</li>
<li><a href="generated/torch.arccos.html#torch.arccos">arccos() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.arccos">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.arccos_">arccos_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.arccosh.html#torch.arccosh">arccosh() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.arccosh">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.arccosh_">arccosh_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.arcsin.html#torch.arcsin">arcsin() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.arcsin">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.arcsin_">arcsin_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.arcsinh.html#torch.arcsinh">arcsinh() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.arcsinh">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.arcsinh_">arcsinh_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.arctan.html#torch.arctan">arctan() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.arctan">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.arctan_">arctan_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.arctanh.html#torch.arctanh">arctanh() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.arctanh">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.arctanh_">arctanh_() (torch.Tensor method)</a>
</li>
<li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.arg_constraints">arg_constraints (torch.distributions.bernoulli.Bernoulli attribute)</a>
<ul>
<li><a href="distributions.html#torch.distributions.beta.Beta.arg_constraints">(torch.distributions.beta.Beta attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.binomial.Binomial.arg_constraints">(torch.distributions.binomial.Binomial attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.categorical.Categorical.arg_constraints">(torch.distributions.categorical.Categorical attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.cauchy.Cauchy.arg_constraints">(torch.distributions.cauchy.Cauchy attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.chi2.Chi2.arg_constraints">(torch.distributions.chi2.Chi2 attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.arg_constraints">(torch.distributions.continuous_bernoulli.ContinuousBernoulli attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.arg_constraints">(torch.distributions.dirichlet.Dirichlet attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.exponential.Exponential.arg_constraints">(torch.distributions.exponential.Exponential attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.arg_constraints">(torch.distributions.fishersnedecor.FisherSnedecor attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.gamma.Gamma.arg_constraints">(torch.distributions.gamma.Gamma attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.geometric.Geometric.arg_constraints">(torch.distributions.geometric.Geometric attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.gumbel.Gumbel.arg_constraints">(torch.distributions.gumbel.Gumbel attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.arg_constraints">(torch.distributions.half_cauchy.HalfCauchy attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.arg_constraints">(torch.distributions.half_normal.HalfNormal attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.independent.Independent.arg_constraints">(torch.distributions.independent.Independent attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.laplace.Laplace.arg_constraints">(torch.distributions.laplace.Laplace attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.log_normal.LogNormal.arg_constraints">(torch.distributions.log_normal.LogNormal attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.arg_constraints">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.arg_constraints">(torch.distributions.mixture_same_family.MixtureSameFamily attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.multinomial.Multinomial.arg_constraints">(torch.distributions.multinomial.Multinomial attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.arg_constraints">(torch.distributions.multivariate_normal.MultivariateNormal attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.arg_constraints">(torch.distributions.negative_binomial.NegativeBinomial attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.normal.Normal.arg_constraints">(torch.distributions.normal.Normal attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.arg_constraints">(torch.distributions.one_hot_categorical.OneHotCategorical attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.pareto.Pareto.arg_constraints">(torch.distributions.pareto.Pareto attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.poisson.Poisson.arg_constraints">(torch.distributions.poisson.Poisson attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.arg_constraints">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli.arg_constraints">(torch.distributions.relaxed_bernoulli.RelaxedBernoulli attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical.arg_constraints">(torch.distributions.relaxed_categorical.RelaxedOneHotCategorical attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.studentT.StudentT.arg_constraints">(torch.distributions.studentT.StudentT attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.arg_constraints">(torch.distributions.transformed_distribution.TransformedDistribution attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.uniform.Uniform.arg_constraints">(torch.distributions.uniform.Uniform attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.von_mises.VonMises.arg_constraints">(torch.distributions.von_mises.VonMises attribute)</a>
</li>
<li><a href="distributions.html#torch.distributions.weibull.Weibull.arg_constraints">(torch.distributions.weibull.Weibull attribute)</a>
</li>
</ul></li>
<li><a href="distributions.html#torch.distributions.distribution.Distribution.arg_constraints">arg_constraints() (torch.distributions.distribution.Distribution property)</a>
</li>
<li><a href="generated/torch.argmax.html#torch.argmax">argmax() (in module torch)</a>, <a href="generated/torch.argmax.html#torch.argmax">[1]</a>
<ul>
<li><a href="tensors.html#torch.Tensor.argmax">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="generated/torch.argmin.html#torch.argmin">argmin() (in module torch)</a>, <a href="generated/torch.argmin.html#torch.argmin">[1]</a>
<ul>
<li><a href="tensors.html#torch.Tensor.argmin">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="generated/torch.argsort.html#torch.argsort">argsort() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.argsort">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="generated/torch.as_strided.html#torch.as_strided">as_strided() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.as_strided">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.as_subclass">as_subclass() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.as_tensor.html#torch.as_tensor">as_tensor() (in module torch)</a>
</li>
<li><a href="optim.html#torch.optim.ASGD">ASGD (class in torch.optim)</a>
</li>
<li><a href="generated/torch.asin.html#torch.asin">asin() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.asin">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.asin_">asin_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.asinh.html#torch.asinh">asinh() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.asinh">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.asinh_">asinh_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.Assert.html#torch.Assert">Assert() (in module torch)</a>
</li>
<li><a href="rpc.html#torch.distributed.rpc.functions.async_execution">async_execution() (in module torch.distributed.rpc.functions)</a>
</li>
<li><a href="generated/torch.atan.html#torch.atan">atan() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.atan">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="generated/torch.atan2.html#torch.atan2">atan2() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.atan2">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.atan2_">atan2_() (torch.Tensor method)</a>
</li>
<li><a href="tensors.html#torch.Tensor.atan_">atan_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.atanh.html#torch.atanh">atanh() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.atanh">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.atanh_">atanh_() (torch.Tensor method)</a>
</li>
<li><a href="generated/torch.atleast_1d.html#torch.atleast_1d">atleast_1d() (in module torch)</a>
</li>
<li><a href="generated/torch.atleast_2d.html#torch.atleast_2d">atleast_2d() (in module torch)</a>
</li>
<li><a href="generated/torch.atleast_3d.html#torch.atleast_3d">atleast_3d() (in module torch)</a>
</li>
<li><a href="amp.html#torch.cuda.amp.autocast">autocast (class in torch.cuda.amp)</a>
</li>
<li><a href="nn.functional.html#torch.nn.functional.avg_pool1d">avg_pool1d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.functional.html#torch.nn.functional.avg_pool2d">avg_pool2d() (in module torch.nn.functional)</a>
<ul>
<li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.avg_pool2d">(in module torch.nn.quantized.functional)</a>
</li>
</ul></li>
<li><a href="nn.functional.html#torch.nn.functional.avg_pool3d">avg_pool3d() (in module torch.nn.functional)</a>
</li>
<li><a href="generated/torch.nn.AvgPool1d.html#torch.nn.AvgPool1d">AvgPool1d (class in torch.nn)</a>
</li>
<li><a href="generated/torch.nn.AvgPool2d.html#torch.nn.AvgPool2d">AvgPool2d (class in torch.nn)</a>
</li>
<li><a href="generated/torch.nn.AvgPool3d.html#torch.nn.AvgPool3d">AvgPool3d (class in torch.nn)</a>
</li>
</ul></td>
</tr></table>
<h2 id="B">B</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="distributed.html#torch.distributed.Backend">Backend (class in torch.distributed)</a>
</li>
<li><a href="rpc.html#torch.distributed.rpc.BackendType">BackendType (class in torch.distributed.rpc)</a>
</li>