id stringlengths 16 145 | text stringlengths 1 179k | title stringclasses 1
value |
|---|---|---|
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_111_0.txt |
# torch.Tensor.divide ¶
Tensor. divide ( _ value _ , _ * _ , _ rounding_mode = None _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_23_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
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* [ Mobile ](https://pytorch.... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_443_0.txt |
# torch.Tensor.arccosh ¶
Tensor. arccosh ( ) ¶
acosh() -> Tensor
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_49_28.txt | ith ` torch.sparse_coo ` layout),
this returns a view of the contained values tensor. Otherwise, this throws an
error.
See also ` Tensor.indices() ` .
Note
This method can only be called on a coalesced sparse tensor. See `
Tensor.coalesce() ` for details.
` var ` ( _dim=None_ , _unbiased=True_ , _keepdim=False... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_288_0.txt |
# torch.acos ¶
torch. acos ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the inverse cosine of each element in ` input ` .
out i = cos − 1 ( input i ) \text{out}_{i} =
\cos^{-1}(\text{input}_{i}) out i = cos − 1 ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_52_6.txt | ¶
[ ` nn.Embedding ` ](generated/torch.nn.Embedding.html#torch.nn.Embedding "torch.nn.Embedding") | A simple lookup table that stores embeddings of a fixed dictionary and size.
---|---
[ ` nn.EmbeddingBag ` ](generated/torch.nn.EmbeddingBag.html#torch.nn.EmbeddingBag "torch.nn.EmbeddingBag") | Computes sums ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_85_0.txt |
# torch.Tensor.register_post_accumulate_grad_hook ¶
Tensor. register_post_accumulate_grad_hook ( _ hook _ ) [ [source]
](../_modules/torch/_tensor.html#Tensor.register_post_accumulate_grad_hook) ¶
Registers a backward hook that runs after grad accumulation.
The hook will be called after all gradients f... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_89_0.txt |
# torch.cholesky_solve ¶
torch. cholesky_solve ( _ B _ , _ L _ , _ upper = False _ , _ * _ , _
out = None _ ) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor")
¶
Computes the solution of a system of linear equations with complex Hermitian
or real symmetric positive-definite lhs given i... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_13_0.txt |
# torch.Tensor.tanh ¶
Tensor. tanh ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_396_0.txt |
# torch.Tensor.i0 ¶
Tensor. i0 ( ) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor")
¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_325_0.txt |
# torch.Tensor.tan ¶
Tensor. tan ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_486_0.txt |
# torch.rad2deg ¶
torch. rad2deg ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with each of the elements of ` input ` converted from
angles in radians to degrees.
Parameters
**input** ( [ _Tensor_ ](../tensors.html#t... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_238_0.txt |
# torch.Tensor.itemsize ¶
Tensor. itemsize ¶
Alias for [ ` element_size() `
](torch.Tensor.element_size.html#torch.Tensor.element_size
"torch.Tensor.element_size")
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_358_0.txt |
# torch.Tensor.is_leaf ¶
Tensor. is_leaf ¶
All Tensors that have [ ` requires_grad `
](torch.Tensor.requires_grad.html#torch.Tensor.requires_grad
"torch.Tensor.requires_grad") which is ` False ` will be leaf Tensors by
convention.
For Tensors that have [ ` requires_grad `
](torch.Tensor.requires_grad.h... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_123_0.txt |
# torch.Tensor.retain_grad ¶
Tensor. retain_grad ( ) → [ None
](https://docs.python.org/3/library/constants.html#None "\(in Python v3.12\)")
¶
Enables this Tensor to have their [ ` grad `
](torch.Tensor.grad.html#torch.Tensor.grad "torch.Tensor.grad") populated
during [ ` backward() ` ](torch.Tensor.b... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_387_0.txt |
# torch.Tensor.round ¶
Tensor. round ( _ decimals = 0 _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_17.txt | https://docs.python.org/3/library/functions.html#int "\(in Python v3.8\)") _,_ _optional_ ) – Dimension of vectors. Default: 1
* **eps** ( [ _float_ ](https://docs.python.org/3/library/functions.html#float "\(in Python v3.8\)") _,_ _optional_ ) – Small value to avoid division by zero. Default: 1e-8
Shape:
... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_100_0.txt |
# torch.Tensor.fmod ¶
Tensor. fmod ( _ divisor _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_46_4.txt | g/3/library/functions.html#int "\(in Python v3.8\)") ) – Global step value to record
* **walltime** ( [ _float_ ](https://docs.python.org/3/library/functions.html#float "\(in Python v3.8\)") ) – Optional override default walltime (time.time()) seconds after epoch of event
* **dataformats** ( _string_ ) – Image ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_417_0.txt |
# torch.expm1 ¶
torch. expm1 ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.special.expm1() ` ](../special.html#torch.special.expm1
"torch.special.expm1") .
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_507_0.txt |
# torch.count_nonzero ¶
torch. count_nonzero ( _ input _ , _ dim = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Counts the number of non-zero values in the tensor ` input ` along the given
` dim ` . If no dim is specified then all non-zeros in the tensor are
counted.
Param... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_163_0.txt |
# torch.Tensor.asinh ¶
Tensor. asinh ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_39_4.txt | h.gt "torch.gt") | Unifies names from inputs
[ ` Tensor.half() ` ](tensors.html#torch.Tensor.half "torch.Tensor.half") | Keeps input names
` Tensor.has_names() ` | See documentation
[ ` Tensor.index_fill() ` ](tensors.html#torch.Tensor.index_fill "torch.Tensor.index_fill") , ` torch.index_fill() ` | Ke... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_23_0.txt |
# torch.Tensor.not_equal ¶
Tensor. not_equal ( _ other _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_424_0.txt |
# torch.Tensor.fill_ ¶
Tensor. fill_ ( _ value _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Fills ` self ` tensor with the specified value.
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_49_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_382_0.txt |
# torch.diff ¶
torch. diff ( _ input _ , _ n = 1 _ , _ dim = -1 _ , _ prepend =
None _ , _ append = None _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Computes the n-th forward difference along the given dimension.
The first-order differences are given by out[i] = input[... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_285_0.txt |
# torch.ger ¶
torch. ger ( _ input _ , _ vec2 _ , _ * _ , _ out = None _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias of [ ` torch.outer() ` ](torch.outer.html#torch.outer "torch.outer") .
Warning
This function is deprecated and will be removed in a future PyTorch releas... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_480_0.txt |
# torch.svd ¶
torch. svd ( _ input _ , _ some = True _ , _ compute_uv = True _ , _
* _ , _ out = None _ ) ¶
Computes the singular value decomposition of either a matrix or batch of
matrices ` input ` . The singular value decomposition is represented as a
namedtuple (U, S, V) , such that ` i... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_5_2.txt | View Resources ](https://pytorch.org/resources)
[ ](https://pytorch.org/)
* [ PyTorch ](https://pytorch.org/)
* [ Get Started ](https://pytorch.org/get-started)
* [ Features ](https://pytorch.org/features)
* [ Ecosystem ](https://pytorch.org/ecosystem)
* [ Blog ](https://pytorch.org/blog/)
* [ Contributi... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_62_15.txt | /pytorch.org/)
* [ Get Started ](https://pytorch.org/get-started)
* [ Features ](https://pytorch.org/features)
* [ Ecosystem ](https://pytorch.org/ecosystem)
* [ Blog ](https://pytorch.org/blog/)
* [ Contributing ](https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md)
* [ Resources ](https://pyto... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_55_0.txt |
# torch.Tensor.q_per_channel_zero_points ¶
Tensor. q_per_channel_zero_points ( ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Given a Tensor quantized by linear (affine) per-channel quantization, returns
a tensor of zero_points of the underlying quantizer. It has the number of
elements th... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_22_2.txt | EXTENSIONS_DIR ` environment variable is set, it replaces `
<tmp>/torch_extensions ` and all extensions will be compiled into subfolders
of this directory. Second, if the ` build_directory ` argument to this
function is supplied, it overrides the entire path, i.e. the library will be
compiled into that folder direct... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_65_2.txt | cer ` cannot kick off the communication at the earliest possible time. Besides bucketing, the ` Reducer ` also registers autograd hooks during construction, one hook per parameter. These hooks will be triggered during the backward pass when the gradient becomes ready.
* **Forward Pass** : The DDP takes the input ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_55_6.txt | ng ` torch.distributed ` applications ](distributed.html#debugging-torch-distributed-applications)
* [ Logging ](distributed.html#logging)
* [ torch.distributed.algorithms.join ](distributed.algorithms.join.html)
* [ ` Join ` ](distributed.algorithms.join.html#torch.distributed.algorithms.Join)
* [ ` Jo... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_48_6.txt | see the error message as below:
UserWarning: ONNX export failed on elu because torch.onnx.symbolic_opset9.elu does not exist
RuntimeError: ONNX export failed: Couldn't export operator elu
The export fails because PyTorch does not support exporting ` elu ` operator.
We find ` virtual Tensor ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_19.txt | torch.Tensor method) ](tensors.html#torch.Tensor.fill_)
* [ fill_diagonal_() (torch.Tensor method) ](tensors.html#torch.Tensor.fill_diagonal_)
* [ FisherSnedecor (class in torch.distributions.fishersnedecor) ](distributions.html#torch.distributions.fishersnedecor.FisherSnedecor)
* [ five_crop() (in module torchvi... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_37_14.txt | nput_shape=False_ ) [ [source]
](_modules/torch/autograd/profiler.html#profile.key_averages) ¶
Averages all function events over their keys.
@param group_by_input_shapes The key would become (event name, input
dimensions) rather than just event name. This is useful to see which
dimensionality contributes to th... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_0_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_87_0.txt |
# torch.tile ¶
torch. tile ( _ input _ , _ dims _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Constructs a tensor by repeating the elements of ` input ` . The ` dims `
argument specifies the number of repetitions in each dimension.
If ` dims ` specifies fewer dimensions than ` in... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_12_5.txt | https://twitter.com/pytorch) [
](https://www.youtube.com/pytorch)
To analyze traffic and optimize your experience, we serve cookies on this
site. By clicking or navigating, you agree to allow our usage of cookies. As
the current maintainers of this site, Facebook’s Cookies Policy applies. Learn
more, including about a... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_179_0.txt |
# torch.Tensor.storage_type ¶
Tensor. storage_type ( ) → [ type
](https://docs.python.org/3/library/functions.html#type "\(in Python v3.12\)")
[ [source] ](../_modules/torch/_tensor.html#Tensor.storage_type) ¶
Returns the type of the underlying storage.
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_469_0.txt |
# torch.cross ¶
torch. cross ( _ input _ , _ other _ , _ dim = None _ , _ * _ , _ out
= None _ ) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns the cross product of vectors in dimension ` dim ` of ` input ` and `
other ` .
Supports input of float, double, cfloat and cdo... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_59_4.txt | to CUDA-enabled GPUs.
#### Platform-specific behaviors ¶
Since workers rely on Python [ ` multiprocessing `
](https://docs.python.org/3/library/multiprocessing.html#module-
multiprocessing "\(in Python v3.8\)") , worker launch behavior is different on
Windows compared to Unix.
* On Unix, ` fork() ` is the def... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_260_0.txt |
# torch.frexp ¶
torch. frexp ( _ input _ , _ * _ , _ out=None) -> (Tensor mantissa _ ,
_ Tensor exponent _ ) ¶
Decomposes ` input ` into mantissa and exponent tensors such that input =
mantissa × 2 exponent \text{input} = \text{mantissa} \times
2^{\text{exponent}} input = mantissa × 2 ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_184_0.txt |
# torch.Tensor.tolist ¶
Tensor. tolist ( ) → list or number ¶
Returns the tensor as a (nested) list. For scalars, a standard Python number
is returned, just like with [ ` item() `
](torch.Tensor.item.html#torch.Tensor.item "torch.Tensor.item") . Tensors are
automatically moved to the CPU first if ne... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_17_0.txt |
# torch.t ¶
torch. t ( _ input _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Expects ` input ` to be <= 2-D tensor and transposes dimensions 0 and 1.
0-D and 1-D tensors are returned as is. When input is a 2-D tensor this is
equivalent to ` transpose(input, 0, 1) ` .
Parameters... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_515_0.txt |
# torch.diagonal ¶
torch. diagonal ( _ input _ , _ offset = 0 _ , _ dim1 = 0 _ , _ dim2
= 1 _ ) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a partial view of ` input ` with the its diagonal elements with
respect to ` dim1 ` and ` dim2 ` appended as a dimension at the... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_35_4.txt | mes_ , _**rename_map_ ) [ [source]
](_modules/torch/tensor.html#Tensor.rename_) ¶
In-place version of ` rename() ` .
` refine_names ` ( _*names_ ) [ [source]
](_modules/torch/tensor.html#Tensor.refine_names) ¶
Refines the dimension names of ` self ` according to ` names ` .
Refining is a special... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_0_0.txt |
# torch.Tensor.sum_to_size ¶
Tensor. sum_to_size ( _ * size _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Sum ` this ` tensor to [ ` size ` ](torch.Tensor.size.html#torch.Tensor.size
"torch.Tensor.size") . [ ` size ` ](torch.Tensor.size.html#torch.Tensor.size
"torch.Tensor.size") ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_160_0.txt |
# torch.isneginf ¶
torch. isneginf ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Tests if each element of ` input ` is negative infinity or not.
Parameters
**input** ( [ _Tensor_ ](../tensors.html#torch.Tensor "torch.Tensor") ) – the
inp... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_484_0.txt |
# torch.cholesky ¶
torch. cholesky ( _ input _ , _ upper = False _ , _ * _ , _ out =
None _ ) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the Cholesky decomposition of a symmetric positive-definite matrix A
A A or for batches of symmetric positive-definite matrices.
... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_426_0.txt |
# torch.isinf ¶
torch. isinf ( _ input _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Tests if each element of ` input ` is infinite (positive or negative
infinity) or not.
Note
Complex values are infinite when their real or imaginary part is infinite.
Parameters
**input** ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_61_3.txt | / iters_to_accumulate
# Accumulates scaled gradients.
scaler.scale(loss).backward()
if (i + 1) % iters_to_accumulate == 0:
# may unscale_ here if desired (e.g., to allow clipping unscaled gradients)
scaler.step(optimizer)
... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_18.txt | ethod) ](distributions.html#torch.distributions.studentT.StudentT.expand)
* [ (torch.distributions.transformed_distribution.TransformedDistribution method) ](distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.expand)
* [ (torch.distributions.uniform.Uniform method) ](distrib... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_16_7.txt | ntropy_with_logits() `
](nn.functional.html#torch.nn.functional.binary_cross_entropy_with_logits
"torch.nn.functional.binary_cross_entropy_with_logits") or [ `
torch.nn.BCEWithLogitsLoss `
](generated/torch.nn.BCEWithLogitsLoss.html#torch.nn.BCEWithLogitsLoss
"torch.nn.BCEWithLogitsLoss") . ` binary_cross_entropy_wit... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_142_0.txt |
# torch.Tensor.index_add ¶
Tensor. index_add ( _ dim _ , _ index _ , _ source _ , _ * _ , _ alpha
= 1 _ ) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Out-of-place version of [ ` torch.Tensor.index_add_() `
](torch.Tensor.index_add_.html#torch.Tensor.index_add_
"torch.Tensor.index... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_31_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_Documentations_41_2.txt | ntent.com/pytorch/serve/master/benchmarks/predict_latency.png)
](performance_guide.html)
#### [ Metrics Topics: Metrics,Performance,Troubleshooting Collecting and
viewing Torcherve metrics 
](metrics.html)
##... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_21_7.txt | the result. Implementations can register that they do not implement an operation by returning ` NotImplemented ` .
* If all of the ` __torch_function__ ` implementations return ` NotImplemented ` , PyTorch raises a ` TypeError ` .
### Testing Coverage of Overrides for the PyTorch API ¶
One troublesome asp... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_37_2.txt | se ` , then gradient
w.r.t. all remaining leaves will still be computed, and will be accumulated
into their ` .grad ` attribute.
Parameters
* **outputs** ( _sequence of Tensor_ ) – outputs of the differentiated function.
* **inputs** ( _sequence of Tensor_ ) – Inputs w.r.t. which the gradient will be re... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_9.txt | (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.celu)
* [ center_crop() (in module torchvision.transforms.functional) ](torchvision/transforms.html#torchvision.transforms.functional.center_crop)
* [ CenterCrop (class in torchvision.transforms) ](torchvision/transforms.html#torchvision.trans... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_48_8.txt | oops in it?
> Please checkout Tracing vs Scripting .
Q: Does ONNX support implicit scalar datatype casting?
> No, but the exporter will try to handle that part. Scalars are converted to
> constant tensors in ONNX. The exporter will try to figure out the right
> datatype for scalars. However for cases that it faile... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_129_0.txt |
# torch.multiply ¶
torch. multiply ( _ input _ , _ other _ , _ * _ , _ out = None _ ) ¶
Alias for [ ` torch.mul() ` ](torch.mul.html#torch.mul "torch.mul") .
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_274_0.txt |
# torch.Tensor.masked_scatter_ ¶
Tensor. masked_scatter_ ( _ mask _ , _ source _ ) ¶
Copies elements from ` source ` into ` self ` tensor at positions where the
` mask ` is True. Elements from ` source ` are copied into ` self `
starting at position 0 of ` source ` and continuing in order one-by-... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_206_0.txt |
# torch.Tensor.erfc ¶
Tensor. erfc ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_47.txt | ipt.html#torch.jit.script)
* [ ScriptFunction (class in torch.jit) ](generated/torch.jit.ScriptFunction.html#torch.jit.ScriptFunction)
* [ ScriptModule (class in torch.jit) ](generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule)
* [ ScriptModule.to() (in module torch.jit) ](generated/torch.jit.ScriptModul... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_162_0.txt |
# torch.clamp ¶
torch. clamp ( _ input _ , _ min = None _ , _ max = None _ , _ * _
, _ out = None _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Clamps all elements in ` input ` into the range [ [ ` min `
](torch.min.html#torch.min "torch.min") , [ ` max `
](torch.max.h... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_66_0.txt |
# torch.Tensor.int_repr ¶
Tensor. int_repr ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Given a quantized Tensor, ` self.int_repr() ` returns a CPU Tensor with
uint8_t as data type that stores the underlying uint8_t values of the given
Tensor.
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_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_7_9.txt | er or fake quant modules, and qconfig
will be propagated.
Parameters
* **model** – input model to be modified in-place
* **inplace** – carry out model transformations in-place, the original module is mutated
* **white_list** – list of quantizable modules
* **observer_non_leaf_module_list** – list ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_502_0.txt |
# torch.pow ¶
torch. pow ( _ input _ , _ exponent _ , _ * _ , _ out = None _ ) →
[ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Takes the power of each element in ` input ` with ` exponent ` and returns a
tensor with the result.
` exponent ` can be either a single ` float ` number ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_15_1.txt | p ` ](amp.html#module-torch.cuda.amp) | __
| [ ` torch.distributed ` ](distributed.html#module-torch.distributed) | __
| [ ` torch.distributed.autograd ` ](rpc.html#module-torch.distributed.autograd) | __
| [ ` torch.distributed.launch ` ](distributed.html#module-torch.distributed.launch) | __
| [ ` tor... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_483_0.txt |
# torch.pinverse ¶
torch. pinverse ( _ input _ , _ rcond = 1e-15 _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.linalg.pinv() `
](torch.linalg.pinv.html#torch.linalg.pinv "torch.linalg.pinv")
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_110_0.txt |
# torch.bitwise_or ¶
torch. bitwise_or ( _ input _ , _ other _ , _ * _ , _ out = None _ )
→ [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the bitwise OR of ` input ` and ` other ` . The input tensor must
be of integral or Boolean types. For bool tensors, it computes the logi... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_33_4.txt | vironment details is helpful and appreciated.
* **CI tests failed, what does it mean?** Maybe you need to merge with master or rebase with latest changes. Pushing your changes should re-trigger CI tests. If the tests persist, you’ll want to trace through the error messages and resolve the related issues.
* **Wh... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_22_1.txt | creates a ` setuptools.Extension ` with the bare
minimum (but often sufficient) arguments to build a C++ extension.
All arguments are forwarded to the ` setuptools.Extension ` constructor.
Example
>>> from setuptools import setup
>>> from torch.utils.cpp_extension import BuildExtension, CppExtens... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_37_9.txt | # d does not require gradients and so has no operation creating it (that is tracked by the autograd engine)
>>> e = torch.rand(10).cuda().requires_grad_()
>>> e.is_leaf
True
# e requires gradients and has no operations creating it
>>> f = torch.rand(10, requires_grad=True, device="cuda")
>>>... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_432_0.txt |
# torch.bitwise_and ¶
torch. bitwise_and ( _ input _ , _ other _ , _ * _ , _ out = None _ )
→ [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the bitwise AND of ` input ` and ` other ` . The input tensor must
be of integral or Boolean types. For bool tensors, it computes the l... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_177_0.txt |
# torch.kthvalue ¶
torch. kthvalue ( _ input _ , _ k _ , _ dim = None _ , _ keepdim =
False _ , _ * _ , _ out = None _ ) ¶
Returns a namedtuple ` (values, indices) ` where ` values ` is the ` k `
th smallest element of each row of the ` input ` tensor in the given
dimension ` dim ` . And... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_403_0.txt |
# torch.sort ¶
torch. sort ( _ input _ , _ dim = -1 _ , _ descending = False _ , _
stable = False _ , _ * _ , _ out = None _ ) ¶
Sorts the elements of the ` input ` tensor along a given dimension in
ascending order by value.
If ` dim ` is not given, the last dimension of the input is c... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_66_3.txt | /pytorch.org/features)
* [ Ecosystem ](https://pytorch.org/ecosystem)
* [ Blog ](https://pytorch.org/blog/)
* [ Contributing ](https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md)
* [ Resources ](https://pytorch.org/resources)
* [ Tutorials ](https://pytorch.org/tutorials)
* [ Docs ](https://pyt... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_259_0.txt |
# torch.Tensor.int ¶
Tensor. int ( _ memory_format = torch.preserve_format _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_27_1.txt | at enables you to run your tensor computations on
an NVIDIA GPU with compute capability >= 3.0
## Tensors ¶
[ ` is_tensor ` ](generated/torch.is_tensor.html#torch.is_tensor "torch.is_tensor") | Returns True if obj is a PyTorch tensor.
---|---
[ ` is_storage ` ](generated/torch.is_storage.html#torch.is_sto... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_16_6.txt | . ` argument are not eligible, and will
produce output that respects the ` dtype ` argument.
### Op-Specific Behavior ¶
The following lists describe the behavior of eligible ops in autocast-enabled
regions. These ops always go through autocasting whether they are invoked as
part of a [ ` torch.nn.Module `
](gene... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_509_0.txt |
# torch.triu ¶
torch. triu ( _ input _ , _ diagonal = 0 _ , _ * _ , _ out = None _
) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns the upper triangular part of a matrix (2-D tensor) or batch of
matrices ` input ` , the other elements of the result tensor ` out ` are set
... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_22_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_128_0.txt |
# torch.Tensor.log_normal_ ¶
Tensor. log_normal_ ( _ mean = 1 _ , _ std = 2 _ , _ * _ , _
generator = None _ ) ¶
Fills ` self ` tensor with numbers samples from the log-normal distribution
parameterized by the given mean μ \mu μ and standard deviation σ \sigma
σ . Note that [ ` mean ` ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_65_0.txt |
# torch.cumsum ¶
torch. cumsum ( _ input _ , _ dim _ , _ * _ , _ dtype = None _ , _
out = None _ ) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor")
¶
Returns the cumulative sum of elements of ` input ` in the dimension ` dim `
.
For example, if ` input ` is a vector of size N, the... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_72_0.txt |
# torch.Tensor.lt ¶
Tensor. lt ( _ other _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_48_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_257_0.txt |
# torch.Tensor.zero_ ¶
Tensor. zero_ ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Fills ` self ` tensor with zeros.
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_7_28.txt | kwargs_ ) [
[source] ](_modules/torch/nn/quantized/dynamic/modules/rnn.html#LSTM) ¶
A dynamic quantized LSTM module with floating point tensor as inputs and
outputs. We adopt the same interface as torch.nn.LSTM , please see [
https://pytorch.org/docs/stable/nn.html#torch.nn.LSTM
](https://pytorch.org/docs/st... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_35_1.txt | , named tensors use names to automatically
check that APIs are being used correctly at runtime, providing extra safety.
Names can also be used to rearrange dimensions, for example, to support
“broadcasting by name” rather than “broadcasting by position”.
Warning
The named tensor API is experimental and subject to cha... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_2.txt | .nn.functional) ](nn.functional.html#torch.nn.functional.adaptive_avg_pool1d)
* [ adaptive_avg_pool2d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.adaptive_avg_pool2d)
* [ (in module torch.nn.quantized.functional) ](quantization.html#torch.nn.quantized.functional.adaptive_avg_pool2d)... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_141_0.txt |
# torch.dist ¶
torch. dist ( _ input _ , _ other _ , _ p = 2 _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns the p-norm of ( ` input ` \- ` other ` )
The shapes of ` input ` and ` other ` must be [ broadcastable
](../notes/broadcasting.html#broadcasting-semantics) .
Pa... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_254_0.txt |
# torch.cholesky_inverse ¶
torch. cholesky_inverse ( _ L _ , _ upper = False _ , _ * _ , _ out =
None _ ) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the inverse of a complex Hermitian or real symmetric positive-
definite matrix given its Cholesky decomposition.
Let A ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_61_5.txt | ke [ ` torch.nn.DataParallel `
](../generated/torch.nn.DataParallel.html#torch.nn.DataParallel
"torch.nn.DataParallel") . The fix is the same : apply autocast as part of
your model’s ` forward ` method to ensure it’s enabled in side threads.
## Autocast and Custom Autograd Functions ¶
If your network uses [ cus... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_80_0.txt |
# torch.le ¶
torch. le ( _ input _ , _ other _ , _ * _ , _ out = None _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes input ≤ other \text{input} \leq \text{other} input ≤ other
element-wise.
The second argument can be a number or a tensor whose shape is [ broadcas... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_57_26.txt | rch.org/hub)
* [ Blog ](https://pytorch.org/blog/)
* [ Tutorials ](https://pytorch.org/tutorials)
* [ Docs ](https://pytorch.org/docs/stable/index.html)
* [ Resources ](https://pytorch.org/resources)
* [ Github ](https://github.com/pytorch/pytorch)
|
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