id stringlengths 16 145 | text stringlengths 1 179k | title stringclasses 1
value |
|---|---|---|
pytorch_torch_tensor_functions/Pytorch_Documentations_55_10.txt | owledgements ](ddp_comm_hooks.html#acknowledgements)
* [ Pipeline Parallelism ](pipeline.html)
* [ Model Parallelism using multiple GPUs ](pipeline.html#model-parallelism-using-multiple-gpus)
* [ Pipelined Execution ](pipeline.html#pipelined-execution)
* [ Pipe APIs in PyTorch ](pipeline.html#pipe-apis-in... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_440_0.txt |
# torch.lgamma ¶
torch. lgamma ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the natural logarithm of the absolute value of the gamma function on
` input ` .
out i = ln ∣ Γ ( input i ) ∣ \text{out}_{i} = \ln
|\Gamma(\text... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_265_0.txt |
# torch.Tensor.floor_divide ¶
Tensor. floor_divide ( _ value _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_104_0.txt |
# torch.bitwise_not ¶
torch. bitwise_not ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the bitwise NOT of the given input tensor. The input tensor must be
of integral or Boolean types. For bool tensors, it computes the logical NOT.
Para... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_6_0.txt | [ ](https://pytorch.org/)
* [ Get Started ](https://pytorch.org/get-started)
* Ecosystem
[ Models (Beta) Discover, publish, and reuse pre-trained models
](https://pytorch.org/hub) [ Tools & Libraries Explore the ecosystem of tools
and libraries ](https://pytorch.org/ecosystem)
* [ Mobile ](https://pytorch.... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_17_0.txt | The documentation is [ here ](/audio/stable/index.html)
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_62_14.txt | ule. If your training program
uses GPUs for training and you would like to use [ `
torch.nn.parallel.DistributedDataParallel() `
](generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel
"torch.nn.parallel.DistributedDataParallel") module, here is how to configure
it.
... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_355_0.txt |
# torch.multinomial ¶
torch. multinomial ( _ input _ , _ num_samples _ , _ replacement =
False _ , _ * _ , _ generator = None _ , _ out = None _ ) →
LongTensor ¶
Returns a tensor where each row contains ` num_samples ` indices sampled from
the multinomial (a stricter definition would be mult... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_134_0.txt |
# torch.Tensor.to_sparse_csr ¶
Tensor. to_sparse_csr ( _ dense_dim = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Convert a tensor to compressed row storage format (CSR). Except for strided
tensors, only works with 2D tensors. If the ` self ` is strided, then the
number of de... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_55_8.txt | nversegamma)
* [ Kumaraswamy ](distributions.html#kumaraswamy)
* [ LKJCholesky ](distributions.html#lkjcholesky)
* [ Laplace ](distributions.html#laplace)
* [ LogNormal ](distributions.html#lognormal)
* [ LowRankMultivariateNormal ](distributions.html#lowrankmultivariatenormal)
* [ MixtureS... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_57_20.txt | bution.Distribution `
A circular von Mises distribution.
This implementation uses polar coordinates. The ` loc ` and ` value ` args
can be any real number (to facilitate unconstrained optimization), but are
interpreted as angles modulo 2 pi.
Example::
>>> m = dist.VonMises(torch.tensor([1.0]),... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_400_0.txt |
# torch.Tensor.dim_order ¶
Tensor. dim_order ( ) → [ tuple
](https://docs.python.org/3/library/stdtypes.html#tuple "\(in Python v3.12\)")
[ [source] ](../_modules/torch/_tensor.html#Tensor.dim_order) ¶
Returns a tuple of int describing the dim order or physical layout of ` self
` .
Parameters
*... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_60_9.txt | ptional_ ) – The default timeout, in seconds, for RPC requests (default: 60 seconds). If the RPC has not completed in this timeframe, an exception indicating so will be raised. Callers can override this timeout for individual RPCs in ` rpc_sync() ` and ` rpc_async() ` if necessary.
* **init_method** ( [ _str_ ]... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_48_0.txt |
# torch.Tensor.to_sparse_bsc ¶
Tensor. to_sparse_bsc ( _ blocksize _ , _ dense_dim _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Convert a tensor to a block sparse column (BSC) storage format of given
blocksize. If the ` self ` is strided, then the number of dense dimensions
could b... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_38_0.txt |
# torch.Tensor.q_per_channel_axis ¶
Tensor. q_per_channel_axis ( ) → [ int
](https://docs.python.org/3/library/functions.html#int "\(in Python v3.12\)")
¶
Given a Tensor quantized by linear (affine) per-channel quantization, returns
the index of dimension on which per-channel quantization is applied.
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_272_0.txt |
# torch.moveaxis ¶
torch. moveaxis ( _ input _ , _ source _ , _ destination _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.movedim() ` ](torch.movedim.html#torch.movedim
"torch.movedim") .
This function is equivalent to NumPy’s moveaxis function.
Examples:
... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_155_0.txt |
# torch.less_equal ¶
torch. less_equal ( _ input _ , _ other _ , _ * _ , _ out = None _ )
→ [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.le() ` ](torch.le.html#torch.le "torch.le") .
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_511_0.txt |
# torch.Tensor.real ¶
Tensor. real ¶
Returns a new tensor containing real values of the ` self ` tensor for a
complex-valued input tensor. The returned tensor and ` self ` share the same
underlying storage.
Returns ` self ` if ` self ` is a real-valued tensor tensor.
Example::
>>>... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_219_0.txt |
# torch.Tensor.square ¶
Tensor. square ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_281_0.txt |
# torch.Tensor.logical_xor ¶
Tensor. logical_xor ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_494_0.txt |
# torch.logsumexp ¶
torch. logsumexp ( _ input _ , _ dim _ , _ keepdim = False _ , _ * _
, _ out = None _ ) ¶
Returns the log of summed exponentials of each row of the ` input ` tensor in
the given dimension ` dim ` . The computation is numerically stabilized.
For summation index j j j gi... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_337_0.txt |
# torch.mvlgamma ¶
torch. mvlgamma ( _ input _ , _ p _ , _ * _ , _ out = None _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.special.multigammaln() `
](../special.html#torch.special.multigammaln "torch.special.multigammaln") .
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_196_0.txt |
# torch.bmm ¶
torch. bmm ( _ input _ , _ mat2 _ , _ * _ , _ out = None _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Performs a batch matrix-matrix product of matrices stored in ` input ` and `
mat2 ` .
` input ` and ` mat2 ` must be 3-D tensors each containing the same num... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_44_4.txt | ted)
* [ Features ](https://pytorch.org/features)
* [ Ecosystem ](https://pytorch.org/ecosystem)
* [ Mobile ](https://pytorch.org/mobile)
* [ PyTorch Hub ](https://pytorch.org/hub)
* [ Blog ](https://pytorch.org/blog/)
* [ Tutorials ](https://pytorch.org/tutorials)
* [ Docs ](https://pytorch.org/docs/stab... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_6_1.txt |
python -m torch.utils.bottleneck /path/to/source/script.py [args]
where [args] are any number of arguments to script.py , or run ` python -m
torch.utils.bottleneck -h ` for more usage instructions.
Warning
Because your script will be profiled, please ensure that it exits in a finite
amount of time.
W... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_296_0.txt |
# torch.Tensor.arccosh_ ¶
Tensor. arccosh_ ( ) ¶
acosh_() -> Tensor
In-place version of [ ` arccosh() `
](torch.Tensor.arccosh.html#torch.Tensor.arccosh "torch.Tensor.arccosh")
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_282_0.txt |
# torch.split ¶
torch. split ( _ tensor _ , _ split_size_or_sections _ , _ dim = 0 _ )
[ [source] ](../_modules/torch/functional.html#split) ¶
Splits the tensor into chunks. Each chunk is a view of the original tensor.
If ` split_size_or_sections ` is an integer type, then [ ` tensor `
](torch.te... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_62_8.txt | arameters
* **tensor** ( [ _Tensor_ ](tensors.html#torch.Tensor "torch.Tensor") ) – Output tensor.
* **scatter_list** ( [ _list_ ](https://docs.python.org/3/library/stdtypes.html#list "\(in Python v3.8\)") _[_ [ _Tensor_ ](tensors.html#torch.Tensor "torch.Tensor") _]_ ) – List of tensors to scatter (defaul... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_30.txt | el across the GPUs given in device_ids.
This is the functional version of the DataParallel module.
Parameters
* **module** ( [ _Module_ ](generated/torch.nn.Module.html#torch.nn.Module "torch.nn.Module") ) – the module to evaluate in parallel
* **inputs** ( [ _Tensor_ ](tensors.html#torch.Tensor "torch.T... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_60_6.txt | ` of
the current worker if ` worker_name ` is ` None ` .
` torch.distributed.rpc. ` ` shutdown ` ( _graceful=True_ ) [ [source]
](_modules/torch/distributed/rpc/api.html#shutdown) ¶
Perform a shutdown of the RPC agent, and then destroy the RPC agent. This
stops the local agent from accepting outstanding r... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_7_22.txt | _corners** ( [ _bool_ ](https://docs.python.org/3/library/functions.html#bool "\(in Python v3.8\)") _,_ _optional_ ) – Geometrically, we consider the pixels of the input and output as squares rather than points. If set to ` True ` , the input and output tensors are aligned by the center points of their corner pixels, ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_235_0.txt |
# torch.hsplit ¶
torch. hsplit ( _ input _ , _ indices_or_sections _ ) → List of
Tensors ¶
Splits ` input ` , a tensor with one or more dimensions, into multiple
tensors horizontally according to ` indices_or_sections ` . Each split is a
view of ` input ` .
If ` input ` is one dimensional this ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_120_0.txt |
# torch.cummin ¶
torch. cummin ( _ input _ , _ dim _ , _ * _ , _ out = None _ ) ¶
Returns a namedtuple ` (values, indices) ` where ` values ` is the
cumulative minimum of elements of ` input ` in the dimension ` dim ` . And `
indices ` is the index location of each maximum value found in the ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_25_8.txt | tion_ _or_ [ _list_ ](https://docs.python.org/3/library/stdtypes.html#list "\(in Python v3.8\)") ) – A function which computes a multiplicative factor given an integer parameter epoch, or a list of such functions, one for each group in optimizer.param_groups.
* **last_epoch** ( [ _int_ ](https://docs.python.org/3/l... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_14.txt | ch) ](generated/torch.diag_embed.html#torch.diag_embed)
* [ (torch.Tensor method) ](tensors.html#torch.Tensor.diag_embed)
* [ diagflat() (in module torch) ](generated/torch.diagflat.html#torch.diagflat)
* [ (torch.Tensor method) ](tensors.html#torch.Tensor.diagflat)
* [ diagonal() (in module torch) ](genera... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_21_4.txt | want to be able to
pass these types to functions like [ ` torch.add() `
](../generated/torch.add.html#torch.add "torch.add") in the top-level ` torch
` namespace that accept ` Tensor ` operands?
If your custom python type defines a method named ` __torch_function__ ` ,
PyTorch will invoke your ` __torch_function__... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_348_0.txt |
# torch.Tensor.arctan ¶
Tensor. arctan ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_488_0.txt |
# torch.triangular_solve ¶
torch. triangular_solve ( _ b _ , _ A _ , _ upper = True _ , _
transpose = False _ , _ unitriangular = False _ , _ * _ , _ out =
None _ ) ¶
Solves a system of equations with a square upper or lower triangular
invertible matrix A A A and multiple right-hand sid... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_207_0.txt |
# torch.Tensor.index_put ¶
Tensor. index_put ( _ indices _ , _ values _ , _ accumulate = False _
) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Out-place version of [ ` index_put_() `
](torch.Tensor.index_put_.html#torch.Tensor.index_put_
"torch.Tensor.index_put_") .
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_25_7.txt | ps/momentum.pdf) .
Parameters
* **params** ( _iterable_ ) – iterable of parameters to optimize or dicts defining parameter groups
* **lr** ( [ _float_ ](https://docs.python.org/3/library/functions.html#float "\(in Python v3.8\)") ) – learning rate
* **momentum** ( [ _float_ ](https://docs.python.org/3... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_36_4.txt | u agree to allow our usage of cookies. As
the current maintainers of this site, Facebook’s Cookies Policy applies. Learn
more, including about available controls: [ Cookies Policy
](https://www.facebook.com/policies/cookies/) .
[ ](https://pytorch.org/)
* [ Get Started ](https://p... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_391_0.txt |
# torch.Tensor.float ¶
Tensor. float ( _ memory_format = torch.preserve_format _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_49_27.txt | c
"torch.trunc")
` trunc_ ` ( ) → Tensor ¶
In-place version of ` trunc() `
` type ` ( _dtype=None_ , _non_blocking=False_ , _**kwargs_ ) → str or
Tensor ¶
Returns the type if dtype is not provided, else casts this object to the
specified type.
If this is already of the correct type, no copy i... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_56_0.txt |
# torch.msort ¶
torch. msort ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Sorts the elements of the ` input ` tensor along its first dimension in
ascending order by value.
Note
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_124_1.txt | unpack") is doing).
>
> * **infos** ( _IntTensor_ , _optional_ ): if ` get_infos ` is ` True ` ,
> this is a tensor of size ( ∗ ) (*) ( ∗ ) where non-zero values
> indicate whether factorization for the matrix or each minibatch has
> succeeded or failed
>
>
Return type
( [ Tensor ](../tensors.html#t... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_7_8.txt | ght-only quantization by default is performed for layers with large weights
size - i.e. Linear and RNN variants.
Fine grained control is possible with qconfig and mapping that act
similarly to quantize() . If qconfig is provided, the dtype argument is
ignored.
Parameters
* **module** – input model ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_295_0.txt |
# torch.flipud ¶
torch. flipud ( _ input _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Flip tensor in the up/down direction, returning a new tensor.
Flip the entries in each column in the up/down direction. Rows are preserved,
but appear in a different order than before.
Note
Requ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_27_8.txt | rns a new tensor with each of the elements of ` input ` rounded to the closest integer.
[ ` rsqrt ` ](generated/torch.rsqrt.html#torch.rsqrt "torch.rsqrt") | Returns a new tensor with the reciprocal of the square-root of each of the elements of ` input ` .
[ ` sigmoid ` ](generated/torch.sigmoid.html#torch.s... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_67_1.txt |
file;
` hubconf.py ` can have multiple entrypoints. Each entrypoint is defined as a
python function (example: a pre-trained model you want to publish).
def entrypoint_name(*args, **kwargs):
# args & kwargs are optional, for models which take positional/keyword arguments.
...
### ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_215_0.txt |
# torch.atanh ¶
torch. atanh ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the inverse hyperbolic tangent of the elements of `
input ` .
Note
The domain of the inverse hyperbolic tangent is (-1, 1) and values outsid... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_49_14.txt | _put ` ( _tensor1_ , _indices_ , _value_ , _accumulate=False_ ) →
Tensor ¶
Out-place version of ` index_put_() ` . tensor1 corresponds to self in
` torch.Tensor.index_put_() ` .
` index_select ` ( _dim_ , _index_ ) → Tensor ¶
See [ ` torch.index_select() `
](generated/torch.index_select.htm... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_37_5.txt | be computed in a differentiable way. Note that when ` strict ` is ` False ` , the result can not require gradients or be disconnected from the inputs. Defaults to ` False ` .
* **strict** ( [ _bool_ ](https://docs.python.org/3/library/functions.html#bool "\(in Python v3.8\)") _,_ _optional_ ) – If ` True ` , an... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_9_8.txt |
#### [ Neural Tangent Kernels Learn how to compute neural tangent kernels
using torch.func Frontend-APIs  ](intermediate/neural_tangent_kernels.html)
#### [ Performance Profiling in PyTorch Learn how to use the PyTorch Profiler
to benchmark your module... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_19_4.txt | org)
[
* Substra
* 
* *
Substra is a federated learning Python library to run federated learning
experiments at scale on real distributed data. ](https://github.com/Substra)
[
* Colossal-LLaMA-2
* 
* *
A complete and open-sou... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_35_3.txt | eference-doc) for a full list of the supported torch and tensor operations.
We do not yet support the following that is not covered by the link:
* indexing, advanced indexing.
For ` torch.nn.functional ` operators, we support the following:
* [ ` torch.nn.functional.relu() ` ](nn.functional.html#torch.nn.func... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_60_7.txt | never sent through RPC. This decorator is
useful when the wrapped function’s ( ` fn ` ) execution needs to pause and
resume due to, e.g., containing ` rpc_async() ` or waiting for other
signals.
Note
To enable asynchronous execution, applications must pass the function object
returned by this decorator to RPC API... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_49_0.txt |
# torch.Tensor.new_zeros ¶
Tensor. new_zeros ( _ size _ , _ * _ , _ dtype = None _ , _ device =
None _ , _ requires_grad = False _ , _ layout = torch.strided _ , _
pin_memory = False _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Returns a Tensor of size [ ` size `
](t... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_57_25.txt | egister ` ( _constraint_ , _factory=None_ ) [ [source]
](_modules/torch/distributions/constraint_registry.html#ConstraintRegistry.register)
¶
Registers a ` Constraint ` subclass in this registry. Usage:
@my_registry.register(MyConstraintClass)
def construct_transform(constraint):
a... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_53_0.txt | [ ](https://pytorch.org/)
* [ Get Started ](https://pytorch.org/get-started)
* Ecosystem
[ Models (Beta) Discover, publish, and reuse pre-trained models
](https://pytorch.org/hub) [ Tools & Libraries Explore the ecosystem of tools
and libraries ](https://pytorch.org/ecosystem)
* [ Mobile ](https://pytorch.... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_449_0.txt |
# torch.isclose ¶
torch. isclose ( _ input _ , _ other _ , _ rtol = 1e-05 _ , _ atol =
1e-08 _ , _ equal_nan = False _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with boolean elements representing if each element of `
input ` is “close” to the correspon... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_59_8.txt | dataset at specified indices.
Parameters
* **dataset** ( _Dataset_ ) – The whole Dataset
* **indices** ( _sequence_ ) – Indices in the whole set selected for subset
` torch.utils.data. ` ` get_worker_info ` ( ) [ [source]
](_modules/torch/utils/data/_utils/worker.html#get_worker_info) ¶
Return... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_383_0.txt |
# torch.sin ¶
torch. sin ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the sine of the elements of ` input ` .
out i = sin ( input i ) \text{out}_{i} = \sin(\text{input}_{i})
out i = sin ( input i ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_366_0.txt |
# torch.Tensor.bitwise_or ¶
Tensor. bitwise_or ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_490_0.txt |
# torch.Tensor.pow ¶
Tensor. pow ( _ exponent _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_42_0.txt | [ ](https://pytorch.org/)
* [ Get Started ](https://pytorch.org/get-started)
* Ecosystem
[ Models (Beta) Discover, publish, and reuse pre-trained models
](https://pytorch.org/hub) [ Tools & Libraries Explore the ecosystem of tools
and libraries ](https://pytorch.org/ecosystem)
* [ Mobile ](https://pytorch.... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_410_0.txt |
# torch.addcdiv ¶
torch. addcdiv ( _ input _ , _ tensor1 _ , _ tensor2 _ , _ * _ , _
value = 1 _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Performs the element-wise division of ` tensor1 ` by ` tensor2 ` ,
multiplies the result by the scalar ` value ` an... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_363_0.txt |
# torch.Tensor.requires_grad_ ¶
Tensor. requires_grad_ ( _ requires_grad = True _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Change if autograd should record operations on this tensor: sets this tensor’s
[ ` requires_grad `
](torch.Tensor.requires_grad.html#torch.Tensor.requires_g... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_334_0.txt |
# torch.Tensor.bitwise_left_shift ¶
Tensor. bitwise_left_shift ( _ other _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_508_0.txt |
# torch.fliplr ¶
torch. fliplr ( _ input _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Flip tensor in the left/right direction, returning a new tensor.
Flip the entries in each row in the left/right direction. Columns are
preserved, but appear in a different order than before.
Note... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_55_13.txt | utorials
Get in-depth tutorials for beginners and advanced developers
[ View Tutorials ](https://pytorch.org/tutorials)
## Resources
Find development resources and get your questions answered
[ View Resources ](https://pytorch.org/resources)
[ ](https://pytorch.org/)
* [ PyTorch ](https://pytorch.org/)
* [ ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_36_3.txt | queezed (see [ ` torch.squeeze() `
](generated/torch.squeeze.html#torch.squeeze "torch.squeeze") ), resulting an
output tensor having ` dim ` fewer dimensions than ` input ` .
During backward, only gradients at ` nnz ` locations of ` input ` will
propagate back. Note that the gradients of ` input ` is coalesced.... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_10_0.txt | [ ](https://pytorch.org)
* [ Get Started ](/get-started)
* Ecosystem
[ PyTorch Conference - 2024 September 18-19 in San Francisco
](https://events.linuxfoundation.org/pytorch-conference/) [ Tools Learn about
the tools and frameworks in the PyTorch Ecosystem ](/ecosystem)
* Edge
[ About PyTorch Edge ](/e... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_459_0.txt |
# torch.Tensor.reshape_as ¶
Tensor. reshape_as ( _ other _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns this tensor as the same shape as ` other ` . ` self.reshape_as(other)
` is equivalent to ` self.reshape(other.sizes()) ` . This method returns a
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_9_7.txt | els and lastly how to load it into a C++
application for inference workloads. Extending-PyTorch,Frontend-
APIs,TorchScript,C++ 
](advanced/torch_script_custom_ops.html)
#### [ Extending TorchScript with Custom C++ Classes This i... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_438_0.txt |
# torch.arccos ¶
torch. arccos ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.acos() ` ](torch.acos.html#torch.acos "torch.acos") .
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_153_0.txt |
# torch.addr ¶
torch. addr ( _ input _ , _ vec1 _ , _ vec2 _ , _ * _ , _ beta = 1 _
, _ alpha = 1 _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Performs the outer-product of vectors ` vec1 ` and ` vec2 ` and adds it to
the matrix ` input ` .
Optional v... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_55_2.txt | are not, however, committing to backwards compatibility.
>
> _Prototype:_ These features are typically not available as part of binary
> distributions like PyPI or Conda, except sometimes behind run-time flags,
> and are at an early stage for feedback and testing.
Community
* [ PyTorch Governance | Build + CI ](com... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_112_0.txt |
# torch.angle ¶
torch. angle ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the element-wise angle (in radians) of the given ` input ` tensor.
out i = a n g l e ( input i ) \text{out}_{i} =
angle(\text{input}_{i}) out i ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_37_0.txt | [ ](https://pytorch.org/)
* [ Get Started ](https://pytorch.org/get-started)
* Ecosystem
[ Models (Beta) Discover, publish, and reuse pre-trained models
](https://pytorch.org/hub) [ Tools & Libraries Explore the ecosystem of tools
and libraries ](https://pytorch.org/ecosystem)
* [ Mobile ](https://pytorch.... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_377_0.txt |
# torch.Tensor.cdouble ¶
Tensor. cdouble ( _ memory_format = torch.preserve_format _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_29.txt | nseNorm)
* [ log() (in module torch) ](generated/torch.log.html#torch.log)
* [ (torch.Tensor method) ](tensors.html#torch.Tensor.log)
* [ log10() (in module torch) ](generated/torch.log10.html#torch.log10)
* [ (torch.Tensor method) ](tensors.html#torch.Tensor.log10)
* [ log10_() (torch.Tensor method) ](te... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_287_0.txt |
# torch.tanh ¶
torch. tanh ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the hyperbolic tangent of the elements of ` input `
.
out i = tanh ( input i ) \text{out}_{i} = \tanh(\text{input}_{i})
out i = ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_491_0.txt |
# torch.inverse ¶
torch. inverse ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.linalg.inv() ` ](torch.linalg.inv.html#torch.linalg.inv
"torch.linalg.inv")
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_193_0.txt |
# torch.Tensor.sqrt ¶
Tensor. sqrt ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_24_0.txt |
# torch.Tensor.triu ¶
Tensor. triu ( _ diagonal = 0 _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_518_0.txt |
# torch.Tensor.subtract ¶
Tensor. subtract ( _ other _ , _ * _ , _ alpha = 1 _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_50_0.txt |
# torch.Tensor.sigmoid ¶
Tensor. sigmoid ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_6.txt | method) ](tensors.html#torch.Tensor.as_strided)
* [ as_subclass() (torch.Tensor method) ](tensors.html#torch.Tensor.as_subclass)
* [ as_tensor() (in module torch) ](generated/torch.as_tensor.html#torch.as_tensor)
* [ ASGD (class in torch.optim) ](optim.html#torch.optim.ASGD)
* [ asin() (in module torch) ](gene... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_57_12.txt | nt_shape
* **cov_factor** ( [ _Tensor_ ](tensors.html#torch.Tensor "torch.Tensor") ) – factor part of low-rank form of covariance matrix with shape batch_shape + event_shape + (rank,)
* **cov_diag** ( [ _Tensor_ ](tensors.html#torch.Tensor "torch.Tensor") ) – diagonal part of low-rank form of covariance matrix... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_62_2.txt | .nn.parallel.DistributedDataParallel") builds on this functionality to
provide synchronous distributed training as a wrapper around any PyTorch
model. This differs from the kinds of parallelism provided by [
Multiprocessing package - torch.multiprocessing ](multiprocessing.html) and [
` torch.nn.DataParallel() `
](ge... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_227_0.txt |
# torch.lt ¶
torch. lt ( _ input _ , _ other _ , _ * _ , _ out = None _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes input < other \text{input} < \text{other} input < other
element-wise.
The second argument can be a number or a tensor whose shape is [ broadcastable... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_24_1.txt | semantics ](notes/cuda.html#cuda-semantics) has more details about
working with CUDA.
` torch.cuda. ` ` current_blas_handle ` ( ) [ [source]
](_modules/torch/cuda.html#current_blas_handle) ¶
Returns cublasHandle_t pointer to current cuBLAS handle
` torch.cuda. ` ` current_device ` ( ) → int [ [source]
](... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_25.txt | tional height] x width .
The modes available for resizing are: nearest , linear (3D-only),
bilinear , bicubic (4D-only), trilinear (5D-only), area
Parameters
* **input** ( [ _Tensor_ ](tensors.html#torch.Tensor "torch.Tensor") ) – the input tensor
* **size** ( [ _int_ ](https://docs.python.org... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_7_24.txt | output zero point
See [ ` Conv1d ` ](generated/torch.nn.Conv1d.html#torch.nn.Conv1d
"torch.nn.Conv1d") for other attributes.
Examples:
>>> m = nn.quantized.Conv1d(16, 33, 3, stride=2)
>>> input = torch.randn(20, 16, 100)
>>> # quantize input to quint8
>>> q_input = torch.quantize_per_tens... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_24_8.txt | ` is ` None ` (default).
Note
See [ Memory management ](notes/cuda.html#cuda-memory-management) for more
details about GPU memory management.
` torch.cuda. ` ` reset_max_memory_allocated ` ( _device: Union[torch.device_
, _str_ , _None_ , _int] = None_ ) → None [ [source]
](_modules/torch/cuda/memory.html#reset... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_38_0.txt | [ ](https://pytorch.org/)
* [ Get Started ](https://pytorch.org/get-started)
* Ecosystem
[ Models (Beta) Discover, publish, and reuse pre-trained models
](https://pytorch.org/hub) [ Tools & Libraries Explore the ecosystem of tools
and libraries ](https://pytorch.org/ecosystem)
* [ Mobile ](https://pytorch.... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_56_2.txt | It’s also worth mentioning a few ops with special behaviors:
* [ ` reshape() ` ](tensors.html#torch.Tensor.reshape "torch.Tensor.reshape") and [ ` reshape_as() ` ](tensors.html#torch.Tensor.reshape_as "torch.Tensor.reshape_as") can return either a view or new tensor, user code shouldn’t rely on whether it’s view o... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_477_0.txt |
# torch.Tensor.log1p ¶
Tensor. log1p ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_19.txt | imation term. Default: ` False ` target ∗ log ( target ) − target \+ 0.5 ∗ log ( 2 ∗ π ∗ target ) \text{target} * \log(\text{target}) - \text{target} + 0.5 * \log(2 * \pi * \text{target}) target ∗ lo g ( target ) − target \+ 0 . 5 ∗ lo g ( 2 ∗ π ∗ target ) .
* **siz... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_57_10.txt | e)
Y = |X| ~ HalfNormal(scale)
Example:
>>> m = HalfNormal(torch.tensor([1.0]))
>>> m.sample() # half-normal distributed with scale=1
tensor([ 0.1046])
Parameters
**scale** ( [ _float_ ](https://docs.python.org/3/library/functions.html#float
"\(in Python v3.8\)") _or_ [ _T... |
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