id stringlengths 16 145 | text stringlengths 1 179k | title stringclasses 1
value |
|---|---|---|
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_301_0.txt |
# torch.Tensor.negative ¶
Tensor. negative ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_292_0.txt |
# torch.Tensor.byte ¶
Tensor. byte ( _ memory_format = torch.preserve_format _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_256_0.txt |
# torch.Tensor.is_set_to ¶
Tensor. is_set_to ( _ tensor _ ) → [ bool
](https://docs.python.org/3/library/functions.html#bool "\(in Python v3.12\)")
¶
Returns True if both tensors are pointing to the exact same memory (same
storage, offset, size and stride).
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_9.txt | ⊗ σ ( b )
where input is split in half along dim to form a and b , σ \sigma σ
is the sigmoid function and ⊗ \otimes ⊗ is the element-wise product
between matrices.
See [ Language Modeling with Gated Convolutional Networks
](https://arxiv.org/abs/1612.08083) .
Parameters
* **input** ( [ ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_62_1.txt | .
## Backends ¶
` torch.distributed ` supports three built-in backends, each with different
capabilities. The table below shows which functions are available for use with
CPU / CUDA tensors. MPI supports CUDA only if the implementation used to build
PyTorch supports it.
Backend | ` gloo ` | ` mpi ` | ` nccl... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_9_12.txt | ast/pytorch-developer-podcast/id1566080008)
* [ Google ](https://www.google.com/podcasts?feed=aHR0cHM6Ly9mZWVkcy5zaW1wbGVjYXN0LmNvbS9PQjVGa0lsOA%3D%3D)
* [ Amazon ](https://music.amazon.com/podcasts/7a4e6f0e-26c2-49e9-a478-41bd244197d0/PyTorch-Developer-Podcast?)
* [ Terms ](https://www.linuxfoundation.org/terms... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_57_7.txt | ml#ContinuousBernoulli.sample)
¶
_property_ ` stddev ` ¶
` support ` _= Interval(lower_bound=0.0, upper_bound=1.0)_ ¶
_property_ ` variance ` ¶
## Dirichlet ¶
_class_ ` torch.distributions.dirichlet. ` ` Dirichlet ` ( _concentration_ ,
_validate_args=None_ ) [ [source]
](_modules/torch/... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_63_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_43_0.txt |
# torch.Tensor.detach_ ¶
Tensor. detach_ ( ) ¶
Detaches the Tensor from the graph that created it, making it a leaf. Views
cannot be detached in-place.
This method also affects forward mode AD gradients and the result will never
have forward mode AD gradients.
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_519_0.txt |
# torch.Tensor.gt ¶
Tensor. gt ( _ other _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_118_0.txt |
# torch.Tensor.atan2 ¶
Tensor. atan2 ( _ other _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_482_0.txt |
# torch.argwhere ¶
torch. argwhere ( _ input _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
Returns a tensor containing the indices of all non-zero elements of ` input `
. Each row in the result contains the indices of a non-zero element in ` input
` . The result is sorted lexicograp... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_26.txt | or
is used to compute the output_size which will then be used to infer new scales
for the interpolation. The default behavior for recompute_scale_factor changed
to False in 1.6.0, and scale_factor is used in the interpolation calculation.
Note
When using the CUDA backend, this operation may induce nondeterministic
be... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_38_2.txt | ait_all ` ( _futures_ ) [ [source]
](_modules/torch/futures.html#wait_all) ¶
Waits for all provided futures to be complete, and returns the list of
completed values.
Parameters
**futures** ( [ _list_ ](https://docs.python.org/3/library/stdtypes.html#list
"\(in Python v3.8\)") ) – a list of ` Future `... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_386_0.txt |
# torch.Tensor.scatter_add ¶
Tensor. scatter_add ( _ dim _ , _ index _ , _ src _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Out-of-place version of [ ` torch.Tensor.scatter_add_() `
](torch.Tensor.scatter_add_.html#torch.Tensor.scatter_add_
"torch.Tensor.scatter_add_")
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_372_0.txt |
# torch.log ¶
torch. log ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the natural logarithm of the elements of ` input `
.
y i = log e ( x i ) y_{i} = \log_{e} (x_{i}) y i = lo g e
( x i ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_262_0.txt |
# torch.conj_physical ¶
torch. conj_physical ( _ input _ , _ * _ , _ out = None _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Computes the element-wise conjugate of the given ` input ` tensor. If ` input
` has a non-complex dtype, this function just returns ` input ` .
Note
T... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_49_6.txt | ` ( _callable_ ) → Tensor ¶
Applies the function ` callable ` to each element in the tensor, replacing
each element with the value returned by ` callable ` .
Note
This function only works with CPU tensors and should not be used in code
sections that require high performance.
` argmax ` ( _dim=None_ , _... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_6.txt |
Computes a partial inverse of ` MaxPool1d ` .
See [ ` MaxUnpool1d `
](generated/torch.nn.MaxUnpool1d.html#torch.nn.MaxUnpool1d
"torch.nn.MaxUnpool1d") for details.
### max_unpool2d ¶
` torch.nn.functional. ` ` max_unpool2d ` ( _input_ , _indices_ ,
_kernel_size_ , _stride=None_ , _padding=0_ , _output_size=... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_297_0.txt |
# torch.resolve_conj ¶
torch. resolve_conj ( _ input _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with materialized conjugation if ` input ` ’s conjugate
bit is set to True , else returns ` input ` . The output tensor will always
have its conjugate bit set to... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_253_0.txt |
# torch.slogdet ¶
torch. slogdet ( _ input _ ) ¶
Alias for [ ` torch.linalg.slogdet() `
](torch.linalg.slogdet.html#torch.linalg.slogdet "torch.linalg.slogdet")
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_24_3.txt | html#torch.torch.device
"torch.torch.device") _or_ [ _int_
](https://docs.python.org/3/library/functions.html#int "\(in Python v3.8\)")
_,_ _optional_ ) – The device to return the RNG state of. Default: ` 'cuda' `
(i.e., ` torch.device('cuda') ` , the current CUDA device).
Warning
This function eagerly initializes ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_275_0.txt |
# torch.Tensor.lcm ¶
Tensor. lcm ( _ other _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_0_2.txt | copy_() `
](../tensors.html#torch.Tensor.copy_ "torch.Tensor.copy_") admit an explicit `
non_blocking ` argument, which lets the caller bypass synchronization when it
is unnecessary. Another exception is CUDA streams, explained below.
### CUDA streams ¶
A [ CUDA stream ](http://docs.nvidia.com/cuda/cuda-c-program... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_146_0.txt |
# torch.Tensor.mul ¶
Tensor. mul ( _ value _ ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_402_0.txt |
# torch.Tensor.asin ¶
Tensor. asin ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/Memory Management_1_0.txt | # Memory Management using PYTORCH_CUDA_ALLOC_CONF
[ 
](/?source=post_page-----dabe7adec130--------------------------------)
[ Shittu Olumide Ayodeji ](/?source=post_page-----
dabe7adec130-----------------------------... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_40_1.txt | rmations for computer vision.
Package Reference
* [ torchvision.datasets ](datasets.html)
* [ MNIST ](datasets.html#mnist)
* [ Fashion-MNIST ](datasets.html#fashion-mnist)
* [ KMNIST ](datasets.html#kmnist)
* [ EMNIST ](datasets.html#emnist)
* [ QMNIST ](datasets.html#qmnist)
* [ FakeData ](... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_60_3.txt | r the ` func ` invocation.
* **timeout** ( [ _float_ ](https://docs.python.org/3/library/functions.html#float "\(in Python v3.8\)") _,_ _optional_ ) – timeout in seconds to use for this RPC. If the RPC does not complete in this amount of time, an exception indicating it has timed out will be raised. A value of 0 i... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_46_2.txt | hidden from TensorBoard. Note that crashed and resumed experiments should have the same ` log_dir ` .
* **max_queue** ( [ _int_ ](https://docs.python.org/3/library/functions.html#int "\(in Python v3.8\)") ) – Size of the queue for pending events and summaries before one of the ‘add’ calls forces a flush to disk. ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_27_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_21_0.txt |
# torch.Tensor.device ¶
Tensor. device ¶
Is the [ ` torch.device ` ](../tensor_attributes.html#torch.device
"torch.device") where this Tensor is.
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_166_0.txt |
# torch.logit ¶
torch. logit ( _ input _ , _ eps = None _ , _ * _ , _ out = None _
) → [ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.special.logit() ` ](../special.html#torch.special.logit
"torch.special.logit") .
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_121_0.txt |
# torch.Tensor.get_device ¶
Tensor. get_device ( _ ) -> Device ordinal (Integer _ ) ¶
For CUDA tensors, this function returns the device ordinal of the GPU on which
the tensor resides. For CPU tensors, this function returns -1 .
Example:
>>> x = torch.randn(3, 4, 5, device='cuda:0')... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_20_2.txt | Tiwari ( [ spandantiwari ](https://github.com/spandantiwari) )
* Bowen Bao ( [ BowenBao ](https://github.com/BowenBao) )
### Windows ¶
* Peter Johnson ( [ peterjc123 ](https://github.com/peterjc123) )
### PowerPC ¶
* Alfredo Mendoza ( [ avmgithub ](https://github.com/avmgithub) )
## Library-level ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_213_0.txt |
# torch.rsqrt ¶
torch. rsqrt ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the reciprocal of the square-root of each of the
elements of ` input ` .
out i = 1 input i \text{out}_{i} = \frac{1}{\sqrt{\text{input}_{... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_252_0.txt |
# torch.igammac ¶
torch. igammac ( _ input _ , _ other _ , _ * _ , _ out = None _ ) →
[ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.special.gammaincc() `
](../special.html#torch.special.gammaincc "torch.special.gammaincc") .
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_25_4.txt | l_ ) – coefficients used for computing running averages of gradient and its square (default: (0.9, 0.999))
* **eps** ( [ _float_ ](https://docs.python.org/3/library/functions.html#float "\(in Python v3.8\)") _,_ _optional_ ) – term added to the denominator to improve numerical stability (default: 1e-8)
* **weig... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_165_0.txt |
# torch.addcmul ¶
torch. addcmul ( _ input _ , _ tensor1 _ , _ tensor2 _ , _ * _ , _
value = 1 _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Performs the element-wise multiplication of ` tensor1 ` by ` tensor2 ` ,
multiplies the result by the scalar ` value... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_86_0.txt |
# torch.Tensor.atanh ¶
Tensor. atanh ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_45_0.txt |
# torch.atan ¶
torch. atan ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the arctangent of the elements of ` input ` .
out i = tan − 1 ( input i ) \text{out}_{i} =
\tan^{-1}(\text{input}_{i}) out i =... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_489_0.txt |
# torch.sign ¶
torch. sign ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the signs of the elements of ` input ` .
out i = sgn ( input i ) \text{out}_{i} =
\operatorname{sgn}(\text{input}_{i}) out i = ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_27_12.txt | with a reduced add step (all matrix multiplications get accumulated along the first dimension).
---|---
[ ` addmm ` ](generated/torch.addmm.html#torch.addmm "torch.addmm") | Performs a matrix multiplication of the matrices ` mat1 ` and ` mat2 ` .
[ ` addmv ` ](generated/torch.addmv.html#torch.addmv "torch.... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_39_2.txt | wise_not_") | None
[ ` Tensor.bmm() ` ](tensors.html#torch.Tensor.bmm "torch.Tensor.bmm") , [ ` torch.bmm() ` ](generated/torch.bmm.html#torch.bmm "torch.bmm") | Contracts away dims
[ ` Tensor.bool() ` ](tensors.html#torch.Tensor.bool "torch.Tensor.bool") | Keeps input names
[ ` Tensor.byte() ` ](tensor... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_38_1.txt | re ` type is primarily used by the [
Distributed RPC Framework ](rpc.html#distributed-rpc-framework) .
_class_ ` torch.futures. ` ` Future ` [ [source]
](_modules/torch/futures.html#Future) ¶
Wrapper around a ` torch._C.Future ` which encapsulates an asynchronous
execution of a callable, e.g. [ ` rpc_async()... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_266_0.txt |
# torch.tensor ¶
torch. tensor ( _ data _ , _ * _ , _ dtype = None _ , _ device =
None _ , _ requires_grad = False _ , _ pin_memory = False _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Constructs a tensor with no autograd history (also known as a “leaf tensor”,
see [ Aut... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_20_3.txt | -started)
* [ 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... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_59_10.txt | "\(in Python v3.8\)") _,_ _optional_ ) – If ` True ` (default), sampler will shuffle the indices.
* **seed** ( [ _int_ ](https://docs.python.org/3/library/functions.html#int "\(in Python v3.8\)") _,_ _optional_ ) – random seed used to shuffle the sampler if ` shuffle=True ` . This number should be identical acro... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_7.txt | in torch.nn.quantized) ](quantization.html#torch.nn.quantized.BatchNorm2d)
* [ BatchNorm3d (class in torch.nn) ](generated/torch.nn.BatchNorm3d.html#torch.nn.BatchNorm3d)
* [ (class in torch.nn.quantized) ](quantization.html#torch.nn.quantized.BatchNorm3d)
* [ BatchSampler (class in torch.utils.data) ](data.htm... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_53_3.txt | orted Pytorch Constructs ](jit_unsupported.html#jit-
unsupported) for a list of unsupported PyTorch functions and modules.
### Python Functions and Modules ¶
Many of Python’s [ built-in functions
](https://docs.python.org/3/library/functions.html) are supported in
TorchScript. The [ ` math `
](https://docs.python... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_28.txt | ric (5-D) ` input ` are supported.
In the spatial (4-D) case, for ` input ` with shape ( N , C , H in ,
W in ) (N, C, H_\text{in}, W_\text{in}) ( N , C , H in , W in
) and ` grid ` with shape ( N , H out , W out , 2 ) (N,
H_\text{out}, W_\text{out}, 2) ( N , H out , ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_523_0.txt |
# torch.Tensor.new_ones ¶
Tensor. new_ones ( _ 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 `
](tor... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_58_0.txt |
# torch.Tensor.numpy ¶
Tensor. numpy ( _ * _ , _ force = False _ ) → [ numpy.ndarray
](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray
"\(in NumPy v1.26\)") ¶
Returns the tensor as a NumPy ` ndarray ` .
If ` force ` is ` False ` (the default), the conversion is ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_186_0.txt |
# torch.stft ¶
torch. stft ( _ input _ , _ n_fft _ , _ hop_length = None _ , _
win_length = None _ , _ window = None _ , _ center = True _ , _
pad_mode = 'reflect' _ , _ normalized = False _ , _ onesided = None _
, _ return_complex = None _ ) [ [source]
](../_modules/torch/functional.h... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_143_0.txt |
# torch.mv ¶
torch. mv ( _ input _ , _ vec _ , _ * _ , _ out = None _ ) → [
Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Performs a matrix-vector product of the matrix ` input ` and the vector ` vec
` .
If ` input ` is a ( n × m ) (n \times m) ( n × m ) tensor, ` vec
` i... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_59_5.txt | def pin_memory(self):
self.inp = self.inp.pin_memory()
self.tgt = self.tgt.pin_memory()
return self
def collate_wrapper(batch):
return SimpleCustomBatch(batch)
inps = torch.arange(10 * 5, dtype=torch.float32).view(10, 5)
tgts = torch.arange(10 * 5, dtype... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_8_0.txt | # 404
**File not found**
The site configured at this address does not contain the requested file.
If this is your site, make sure that the filename case matches the URL as well
as any file permissions.
For root URLs (like ` http://example.com/ ` ) you must provide an ` index.html
` file.
[ Read the full document... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_25_13.txt | **verbose** ( [ _bool_ ](https://docs.python.org/3/library/functions.html#bool "\(in Python v3.8\)") ) – If ` True ` , prints a message to stdout for each update. Default: ` False ` .
Example
>>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
>>> scheduler = torch.optim.lr_... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_53_8.txt |
* The ` @torch.jit.script_method ` decorator
* Classes that inherit from ` torch.jit.ScriptModule `
* The ` torch.jit.Attribute ` wrapper class
* The ` __constants__ ` array
* The ` torch.jit.annotate ` function
#### Modules ¶
Warning
The [ ` @torch.jit.ignore `
](generated/torch.jit.igno... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_234_0.txt |
# torch.Tensor.bernoulli ¶
Tensor. bernoulli ( _ * _ , _ generator = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a result tensor where each result[i] \texttt{result[i]} result[i]
is independently sampled from Bernoulli ( self[i] )
\text{Bernoulli}(\texttt{self... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_21_8.txt | g custom C extensions
## Docs
Access comprehensive developer documentation for PyTorch
[ View Docs ](https://pytorch.org/docs/stable/index.html)
## Tutorials
Get in-depth tutorials for beginners and a... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_23_1.txt | e model parameters:
torch.save(the_model.state_dict(), PATH)
Then later:
the_model = TheModelClass(*args, **kwargs)
the_model.load_state_dict(torch.load(PATH))
The second saves and loads the entire model:
torch.save(the_model, PATH)
Then later:
... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_29.txt | e instead considered as referring to the corner points of the input’s corner pixels, making the sampling more resolution agnostic. This option parallels the ` align_corners ` option in ` interpolate() ` , and so whichever option is used here should also be used there to resize the input image before grid sampling. D... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_4_0.txt | # 404
**File not found**
The site configured at this address does not contain the requested file.
If this is your site, make sure that the filename case matches the URL as well
as any file permissions.
For root URLs (like ` http://example.com/ ` ) you must provide an ` index.html
` file.
[ Read the full document... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_48_13.txt | ub.com/pytorch/pytorch)
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_0.txt | [ ](https://pytorch.org/)
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pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_456_0.txt |
# torch.Tensor.cos ¶
Tensor. cos ( ) → [ Tensor ](../tensors.html#torch.Tensor
"torch.Tensor") ¶
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_91_0.txt |
# torch.cov ¶
torch. cov ( _ input _ , _ * _ , _ correction = 1 _ , _ fweights =
None _ , _ aweights = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Estimates the covariance matrix of the variables given by the ` input `
matrix, where rows are the variables and columns ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_27_5.txt | rch.save() ` ](generated/torch.save.html#torch.save "torch.save") from a file.
## Parallelism ¶
[ ` get_num_threads ` ](generated/torch.get_num_threads.html#torch.get_num_threads "torch.get_num_threads") | Returns the number of threads used for parallelizing CPU operations
---|---
[ ` set_num_threads ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_24_6.txt | _handle ` ( ) [ [source]
](_modules/torch/cuda/streams.html#Event.ipc_handle) ¶
Returns an IPC handle of this event. If not recorded yet, the event will use
the current device.
` query ` ( ) [ [source] ](_modules/torch/cuda/streams.html#Event.query) ¶
Checks if all work currently captured by event h... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_17.txt | method) ](distributions.html#torch.distributions.binomial.Binomial.expand)
* [ (torch.distributions.categorical.Categorical method) ](distributions.html#torch.distributions.categorical.Categorical.expand)
* [ (torch.distributions.cauchy.Cauchy method) ](distributions.html#torch.distributions.cauchy.Cauchy.expa... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_59_2.txt | a loader
yields batched samples instead of individual samples. ` batch_size ` and `
drop_last ` arguments are used to specify how the data loader obtains batches
of dataset keys. For map-style datasets, users can alternatively specify `
batch_sampler ` , which yields a list of keys at a time.
Note
The ` batch_size... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_58.txt | n() (in module torchvision.models) ](torchvision/models.html#torchvision.models.vgg11_bn)
* [ vgg13() (in module torchvision.models) ](torchvision/models.html#torchvision.models.vgg13)
* [ vgg13_bn() (in module torchvision.models) ](torchvision/models.html#torchvision.models.vgg13_bn)
* [ vgg16() (in module torch... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_51_0.txt |
# torch.tensor_split ¶
torch. tensor_split ( _ input _ , _ indices_or_sections _ , _ dim = 0
_ ) → List of Tensors ¶
Splits a tensor into multiple sub-tensors, all of which are views of ` input
` , along dimension ` dim ` according to the indices or number of sections
specified by ` indices_or_s... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_53_6.txt | tion. As an example, take a trace of a function that contains an in-
place assignment on a slice (a view) of a Tensor:
def fill_row_zero(x):
x[0] = torch.rand(*x.shape[1:2])
return x
traced = torch.jit.trace(fill_row_zero, (torch.rand(3, 4),))
print(traced.graph)
Produc... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_505_0.txt |
# torch.trunc ¶
torch. trunc ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the truncated integer values of the elements of `
input ` .
For integer inputs, follows the array-api convention of returning a copy of
the inp... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_49_15.txt | ad=True) + 2
>>> c.is_leaf
False
# c was created by the addition operation
>>> d = torch.rand(10).cuda()
>>> d.is_leaf
True
# 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... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_27_9.txt | var ` ](generated/torch.var.html#torch.var "torch.var") | Returns the variance of all elements in the ` input ` tensor.
[ ` var_mean ` ](generated/torch.var_mean.html#torch.var_mean "torch.var_mean") | Returns the variance and mean of all elements in the ` input ` tensor.
### Comparison Ops ¶
[ ` all... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_61_6.txt | [](../_static/images/chevron-right-orange.svg)
Previous ](../index.html "PyTorch documentation")
* * *
© Copyright 2019, Torch Contributors.
Built with [ Sphinx ](http://sphinx-doc.org/) using a [ theme
](https://github.com/rtfd/sphinx_rtd_theme) provided by [ Read the Docs
](https://readthedocs.org) .
* Automati... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_461_0.txt |
# torch.arcsinh ¶
torch. arcsinh ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Alias for [ ` torch.asinh() ` ](torch.asinh.html#torch.asinh "torch.asinh") .
| |
pytorch_torch_tensor_functions/Pytorch_Documentations_61_4.txt | p") on each of them individually.
However, [ ` scaler.update ` ](../amp.html#torch.cuda.amp.GradScaler.update
"torch.cuda.amp.GradScaler.update") should only be called once, after all
optimizers used this iteration have been stepped:
scaler = torch.cuda.amp.GradScaler()
for epoch in epochs:
... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_239_0.txt |
# torch.log1p ¶
torch. log1p ( _ input _ , _ * _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a new tensor with the natural logarithm of (1 + ` input ` ).
y i = log e ( x i \+ 1 ) y_i = \log_{e} (x_i + 1) y i =
lo g e ( x i ... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_322_0.txt |
# torch.Tensor.is_shared ¶
Tensor. is_shared ( ) [ [source]
](../_modules/torch/_tensor.html#Tensor.is_shared) ¶
Checks if tensor is in shared memory.
This is always ` True ` for CUDA tensors.
| |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_144_0.txt |
# torch.vsplit ¶
torch. vsplit ( _ input _ , _ indices_or_sections _ ) → List of
Tensors ¶
Splits ` input ` , a tensor with two or more dimensions, into multiple
tensors vertically according to ` indices_or_sections ` . Each split is a
view of ` input ` .
This is equivalent to calling torch.tens... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_1_1.txt | n using identical seeds.
However, in order to make computations deterministic on your specific problem
on one specific platform and PyTorch release, there are a couple of steps to
take.
There are two pseudorandom number generators involved in PyTorch, which you
will need to seed manually to make runs reproducible. Fu... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_58_37.txt | html#torch.quantization.ObserverBase)
* [ one_hot() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.one_hot)
* [ OneCycleLR (class in torch.optim.lr_scheduler) ](optim.html#torch.optim.lr_scheduler.OneCycleLR)
* [ OneHotCategorical (class in torch.distributions.one_hot_categorical) ](dist... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_231_0.txt |
# torch.Tensor.retains_grad ¶
Tensor. retains_grad ¶
Is ` True ` if this Tensor is non-leaf and its [ ` grad `
](torch.Tensor.grad.html#torch.Tensor.grad "torch.Tensor.grad") is enabled to
be populated during [ ` backward() `
](torch.Tensor.backward.html#torch.Tensor.backward "torch.Tensor.backward") ,
... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_97_0.txt |
# torch.squeeze ¶
torch. squeeze ( _ input _ , _ dim = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Returns a tensor with all specified dimensions of ` input ` of size 1
removed.
For example, if input is of shape: ( A × 1 × B × C × 1 × D )
(A \times 1 \times... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_109_0.txt |
# torch.addmv ¶
torch. addmv ( _ input _ , _ mat _ , _ vec _ , _ * _ , _ beta = 1 _
, _ alpha = 1 _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Performs a matrix-vector product of the matrix ` mat ` and the vector ` vec
` . The vector ` input ` is added ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_25_10.txt | ngLR ` ( _optimizer_ ,
_T_max_ , _eta_min=0_ , _last_epoch=-1_ , _verbose=False_ ) [ [source]
](_modules/torch/optim/lr_scheduler.html#CosineAnnealingLR) ¶
Set the learning rate of each parameter group using a cosine annealing
schedule, where η m a x \eta_{max} η m a x is set to the initial
lr and... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_75_0.txt |
# torch.Tensor.bernoulli_ ¶
Tensor. bernoulli_ ( _ p = 0.5 _ , _ * _ , _ generator = None _ ) →
[ Tensor ](../tensors.html#torch.Tensor "torch.Tensor") ¶
Fills each location of ` self ` with an independent sample from Bernoulli (
p ) \text{Bernoulli}(\texttt{p}) Bernoulli ( p ) . ` self... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_60_5.txt | , then the next time there is an attempt to use the RRef (such as ` to_here() ` ), a timeout will be raised indicating this failure. A value of 0 indicates an infinite timeout, i.e. a timeout error will never be raised. If not provided, the default value set during initialization or with ` _set_rpc_timeout ` is used.... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_29_2.txt | ed ](https://pytorch.org/get-started)
* [ 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)
* [ Doc... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_48_12.txt | olic ` ( _symbolic_name_ ,
_symbolic_fn_ , _opset_version_ ) [ [source]
](_modules/torch/onnx.html#register_custom_op_symbolic) ¶
` torch.onnx.operators. ` ` shape_as_tensor ` ( _x_ ) [ [source]
](_modules/torch/onnx/operators.html#shape_as_tensor) ¶
` torch.onnx. ` ` select_model_mode_for_export ` ( ... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_57_18.txt | 4, 0.3859, 0.2523])
Parameters
* **temperature** ( [ _Tensor_ ](tensors.html#torch.Tensor "torch.Tensor") ) – relaxation temperature
* **probs** ( [ _Tensor_ ](tensors.html#torch.Tensor "torch.Tensor") ) – event probabilities
* **logits** ( [ _Tensor_ ](tensors.html#torch.Tensor "torch.Tensor")... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_62_13.txt | n each of the training nodes.
The utility can be used for single-node distributed training, in which one or
more processes per node will be spawned. The utility can be used for either
CPU training or GPU training. If the utility is used for GPU training, each
distributed process will be operating on a single GPU. This... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_44_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_472_0.txt |
# torch.Tensor.copy_ ¶
Tensor. copy_ ( _ src _ , _ non_blocking = False _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Copies the elements from ` src ` into ` self ` tensor and returns ` self `
.
The ` src ` tensor must be [ broadcastable
](../notes/broadcasting.html#broadcasti... | |
pytorch_torch_tensor_functions/Pytorch_Documentations_47_10.txt | rary/functions.html#int "\(in Python v3.8\)") ) – A dimension along which softmin will be computed (so every slice along dim will sum to 1).
* **dtype** ( ` torch.dtype ` , optional) – the desired data type of returned tensor. If specified, the input tensor is casted to ` dtype ` before the operation is performed... | |
pytorch_torch_tensor_functions/pytorch_torch_tensor_functions_442_0.txt |
# torch.baddbmm ¶
torch. baddbmm ( _ input _ , _ batch1 _ , _ batch2 _ , _ * _ , _ beta
= 1 _ , _ alpha = 1 _ , _ out = None _ ) → [ Tensor
](../tensors.html#torch.Tensor "torch.Tensor") ¶
Performs a batch matrix-matrix product of matrices in ` batch1 ` and ` batch2
` . ` input ` is added ... |
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