Torch.empty(3).Random(2) . Tensor.random_(from=0, to=none, *, generator=none) → tensor. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Every time i run torch.empty(5, 3) i get one of those two results: # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The function torch.empty() returns a tensor filled with uninitialized data. The shape of the tensor is defined by the variable argument. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Fills self tensor with numbers sampled from the discrete. Random sampling creation ops are listed under random sampling and include:
from www.pngkey.com
Every time i run torch.empty(5, 3) i get one of those two results: Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Tensor.random_(from=0, to=none, *, generator=none) → tensor. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Random sampling creation ops are listed under random sampling and include: # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. The function torch.empty() returns a tensor filled with uninitialized data. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Fills self tensor with numbers sampled from the discrete.
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Torch.empty(3).Random(2) Random sampling creation ops are listed under random sampling and include: >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Fills self tensor with numbers sampled from the discrete. The function torch.empty() returns a tensor filled with uninitialized data. Tensor.random_(from=0, to=none, *, generator=none) → tensor. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Every time i run torch.empty(5, 3) i get one of those two results: Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The shape of the tensor is defined by the variable argument. Random sampling creation ops are listed under random sampling and include:
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2 Gram Torch Diamonds Rechargeable Disposable Vape Pen Kit E Cigarettes Torch.empty(3).Random(2) Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Random sampling creation ops are listed under random sampling and include: # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. The function torch.empty() returns a tensor. Torch.empty(3).Random(2).
From blog.csdn.net
小白学Pytorch 系列Torch API（2）_rng stateCSDN博客 Torch.empty(3).Random(2) Fills self tensor with numbers sampled from the discrete. Every time i run torch.empty(5, 3) i get one of those two results: >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Random sampling creation ops are listed under random sampling and include: Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. #. Torch.empty(3).Random(2).
From weldmetalsonline.com
20 Series CK Water Cooled Flex Head TIG Torch for Everlast Torch.empty(3).Random(2) Tensor.random_(from=0, to=none, *, generator=none) → tensor. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Random sampling creation ops are listed under random sampling and include: The function torch.empty() returns a tensor filled with. Torch.empty(3).Random(2).
From exoordqpq.blob.core.windows.net
Torch Brazing Near Me at Elfriede Downey blog Torch.empty(3).Random(2) Fills self tensor with numbers sampled from the discrete. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false,. Torch.empty(3).Random(2).
From www.youtube.com
Baldur's Gate 3 Light a Torch (How to Use a Torch) YouTube Torch.empty(3).Random(2) # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Every time i run torch.empty(5, 3) i get one of those two results: Fills self tensor with numbers sampled from the discrete. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Torch.empty(*size, *, out=none,. Torch.empty(3).Random(2).
From blog.csdn.net
【Pytorch 基础教程2】10分钟掌握Tensor基础 VSCode +Pytorch配置_vscode pytorchCSDN博客 Torch.empty(3).Random(2) Fills self tensor with numbers sampled from the discrete. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. The shape of the tensor is defined by the variable argument. Random sampling creation ops are listed under random sampling and include: Tensor.random_(from=0, to=none, *, generator=none) → tensor. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none,. Torch.empty(3).Random(2).
From blog.csdn.net
PyTorch 1000问_pytorch trainloader.samplerCSDN博客 Torch.empty(3).Random(2) Random sampling creation ops are listed under random sampling and include: Fills self tensor with numbers sampled from the discrete. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Torch.empty torch.empty(*size, *, out=none, dtype=none,. Torch.empty(3).Random(2).
From www.cnblogs.com
CLASS torch.nn.CrossEntropyLoss 朴素贝叶斯 博客园 Torch.empty(3).Random(2) Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The shape of the tensor is defined by the variable argument. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Every time i run torch.empty(5, 3) i get one of those two results: >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Tensor.random_(from=0, to=none,. Torch.empty(3).Random(2).
From exodggmoe.blob.core.windows.net
Minecraft Torch Out Of Paper at Heather Akins blog Torch.empty(3).Random(2) The shape of the tensor is defined by the variable argument. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Random sampling creation ops are listed under random sampling and include: Tensor.random_(from=0, to=none, *, generator=none) → tensor. Every time i run torch.empty(5, 3) i get one of those two results: >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Fills self. Torch.empty(3).Random(2).
From www.animalia-life.club
Portable Cutting Torch Torch.empty(3).Random(2) # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. The function torch.empty() returns a tensor filled with uninitialized data. Every time i run torch.empty(5, 3) i get one of those two results: Random sampling creation ops are listed under random sampling and. Torch.empty(3).Random(2).
From www.youtube.com
can the witch get empty potions Randomly Generated Droids YouTube Torch.empty(3).Random(2) Fills self tensor with numbers sampled from the discrete. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. The shape of the tensor is defined by the variable argument. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Every time i run torch.empty(5,. Torch.empty(3).Random(2).
From exovkexwt.blob.core.windows.net
Parts Of A Torch Lighter at Donald Perez blog Torch.empty(3).Random(2) Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The function torch.empty() returns a tensor filled with uninitialized data. The shape of the tensor is defined by the variable argument. Every time i run torch.empty(5, 3) i get one of those two results: Tensor.random_(from=0, to=none, *, generator=none) → tensor. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Fills self tensor. Torch.empty(3).Random(2).
From stackoverflow.com
python Use of torch.stack() Stack Overflow Torch.empty(3).Random(2) Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Tensor.random_(from=0, to=none, *, generator=none) → tensor. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The function torch.empty() returns a tensor filled with uninitialized data. Random sampling creation ops are listed under random sampling and include: The shape of the tensor is defined by the variable argument. Fills self tensor with numbers. Torch.empty(3).Random(2).
From c.realme.com
realme Community Torch.empty(3).Random(2) The function torch.empty() returns a tensor filled with uninitialized data. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The shape of the tensor is defined by the variable argument. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar,. Torch.empty(3).Random(2).
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Nontextured burning torch (2) Download Free 3D model by Nortenko Torch.empty(3).Random(2) Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Tensor.random_(from=0, to=none, *, generator=none) → tensor. The shape of the tensor is defined by the variable argument. Fills self tensor with numbers sampled from the discrete. Every time i run torch.empty(5, 3) i get one of those two results: The function torch.empty() returns a tensor filled with uninitialized data. Random sampling. Torch.empty(3).Random(2).
From smellproofmylar.com
Sprinklez Mylar Bags Torch Empty 3.5g Holographic Smell Proof Mylar Torch.empty(3).Random(2) The function torch.empty() returns a tensor filled with uninitialized data. The shape of the tensor is defined by the variable argument. Random sampling creation ops are listed under random sampling and include: # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Tensor.random_(from=0,. Torch.empty(3).Random(2).
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Sunnydaze Resin/Metal 3in1 Tiki Face Outdoor Lawn Torch Set of 4 Torch.empty(3).Random(2) # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Fills self tensor with numbers sampled from the discrete. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false,. Torch.empty(3).Random(2).
From www.pngkey.com
Torch Clipart Random Object Object Show Torch Free Transparent PNG Torch.empty(3).Random(2) Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The function torch.empty() returns a tensor filled with uninitialized data. Fills self tensor with numbers sampled from the discrete. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor. Torch.empty(3).Random(2).
From rangechange.ca
Gestire Dipendenza galoppo torch mod 1.12 2 Frontiera Richiamare Torch.empty(3).Random(2) Every time i run torch.empty(5, 3) i get one of those two results: The function torch.empty() returns a tensor filled with uninitialized data. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Random sampling creation ops are listed under random sampling and include: Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,.. Torch.empty(3).Random(2).
From blog.csdn.net
Torch.empty(3).Random(2) Random sampling creation ops are listed under random sampling and include: Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. The function torch.empty() returns a tensor filled with uninitialized data. Fills self tensor with numbers sampled from the discrete. # a tensor can have different dimensions # so it can be 1d,. Torch.empty(3).Random(2).
From exoultfcm.blob.core.windows.net
How Does An Air Acetylene Torch Work at Anthony Harris blog Torch.empty(3).Random(2) Tensor.random_(from=0, to=none, *, generator=none) → tensor. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Fills self tensor with numbers sampled from the discrete. The function torch.empty() returns a tensor filled with uninitialized data.. Torch.empty(3).Random(2).
From exomrykkk.blob.core.windows.net
Papercraft Minecraft Torch at Mark Greenhalgh blog Torch.empty(3).Random(2) The shape of the tensor is defined by the variable argument. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Fills self tensor with numbers sampled from the discrete. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix,. Torch.empty(3).Random(2).
From sheepsurim.tistory.com
torch.nn과 torch.nn.functional Torch.empty(3).Random(2) Fills self tensor with numbers sampled from the discrete. Every time i run torch.empty(5, 3) i get one of those two results: >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. The function torch.empty() returns a tensor filled with uninitialized data. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Tensor.random_(from=0, to=none, *, generator=none) → tensor. The shape of the tensor. Torch.empty(3).Random(2).
From torch-diamond.com
Home TORCH DIAMOND Torch.empty(3).Random(2) Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The shape of the tensor is defined by the variable argument. The function torch.empty() returns a tensor filled with uninitialized data. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Fills self tensor with. Torch.empty(3).Random(2).
From exobygfvi.blob.core.windows.net
Torch Full Form at Tim Crow blog Torch.empty(3).Random(2) Fills self tensor with numbers sampled from the discrete. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Every time i run torch.empty(5, 3) i get one of those two results: The function torch.empty() returns a tensor filled with uninitialized data. Tensor.random_(from=0, to=none, *, generator=none) → tensor. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Random sampling creation ops are listed. Torch.empty(3).Random(2).
From www.solveforum.com
[Solved] ERROR Could not find a version that satisfies the requirement Torch.empty(3).Random(2) Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Every time i run torch.empty(5, 3) i get one of those two results: Fills self tensor with numbers sampled from the discrete. The function torch.empty() returns a tensor filled with uninitialized data. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The shape. Torch.empty(3).Random(2).
From discuss.pytorch.org
Autograd not registering tensors does not require grad and does not Torch.empty(3).Random(2) Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Fills self tensor with numbers sampled from the discrete. The function torch.empty() returns a tensor filled with uninitialized data. Random sampling creation ops are. Torch.empty(3).Random(2).
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wholesale Torch diamond Disposable Vape pen torch bar Atomizers With Torch.empty(3).Random(2) Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Every time i run torch.empty(5, 3) i get one of those two results: Random sampling creation ops are listed under random sampling and include: # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher #. Torch.empty(3).Random(2).
From www.youtube.com
Where To Find Torches for Tushita Puzzle All 5 Torch Locations Blox Torch.empty(3).Random(2) # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Random sampling creation ops are listed under random sampling and include: Fills self tensor with numbers sampled from the discrete. The shape of the tensor is defined by the variable argument. Torch.empty(*size, out=none,. Torch.empty(3).Random(2).
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Can Stainless Steel Be Cut With A Torch at Julius Sandy blog Torch.empty(3).Random(2) Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. The function torch.empty() returns a tensor filled with uninitialized data. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The shape of the tensor is. Torch.empty(3).Random(2).
From nicodatouba.blogspot.com
Torch Vape Pen NicodaTouba Torch.empty(3).Random(2) Tensor.random_(from=0, to=none, *, generator=none) → tensor. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. The shape of the tensor is defined by the variable argument. # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor #. Torch.empty(3).Random(2).
From discuss.pytorch.org
Pytorch official example running error example? PyTorch Forums Torch.empty(3).Random(2) Tensor.random_(from=0, to=none, *, generator=none) → tensor. >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Fills self tensor with numbers sampled from the discrete. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. The function torch.empty() returns a tensor filled with uninitialized data. Random sampling creation ops are listed under random sampling and. Torch.empty(3).Random(2).
From blog.csdn.net
torch.empty()和torch.Tensor.random_()的使用举例CSDN博客 Torch.empty(3).Random(2) Fills self tensor with numbers sampled from the discrete. Every time i run torch.empty(5, 3) i get one of those two results: The function torch.empty() returns a tensor filled with uninitialized data. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Random sampling creation ops are listed under random sampling and include: The shape of the tensor is defined by the. Torch.empty(3).Random(2).
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Torch Skyrim Wiki Torch.empty(3).Random(2) Torch.empty torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,. Random sampling creation ops are listed under random sampling and include: >>> torch.empty(5, 3) tensor([[ 0.0000, 0.0000, 0.0000], [ 0.0000,. Torch.empty(*size, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false) →. Tensor.random_(from=0, to=none, *, generator=none) → tensor. The function torch.empty() returns a tensor filled with uninitialized data. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false,. Torch.empty(3).Random(2).
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torch.nn.init.constant_(tensor, val)怎么使用 编程宝库 Torch.empty(3).Random(2) # a tensor can have different dimensions # so it can be 1d, 2d, or even 3d and higher # scalar, vector, matrix, tensor # torch.empty (size):. Tensor.random_(from=0, to=none, *, generator=none) → tensor. The function torch.empty() returns a tensor filled with uninitialized data. Fills self tensor with numbers sampled from the discrete. Torch.empty(*size, *, out=none, dtype=none, layout=torch.strided, device=none, requires_grad=false, pin_memory=false,.. Torch.empty(3).Random(2).
