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deepxde
deepxde.data
deepxde.geometry
deepxde.gradients
deepxde.icbc
deepxde.nn
deepxde.nn.jax
deepxde.nn.paddle
deepxde.nn.pytorch
deepxde.nn.tensorflow
deepxde.nn.tensorflow_compat_v1
deepxde.optimizers
deepxde.utils
DeepXDE
deepxde.backend.pytorch package
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deepxde.backend.pytorch package
Submodules
deepxde.backend.pytorch.tensor module
pytorch backend implementation
deepxde.backend.pytorch.tensor.
Variable
(
initial_value
,
dtype
=
None
)
[source]
deepxde.backend.pytorch.tensor.
abs
(
x
)
[source]
deepxde.backend.pytorch.tensor.
as_tensor
(
data
,
dtype
=
None
)
[source]
deepxde.backend.pytorch.tensor.
concat
(
values
,
axis
)
[source]
deepxde.backend.pytorch.tensor.
cos
(
x
)
[source]
deepxde.backend.pytorch.tensor.
data_type_dict
(
)
[source]
deepxde.backend.pytorch.tensor.
elu
(
x
)
[source]
deepxde.backend.pytorch.tensor.
exp
(
x
)
[source]
deepxde.backend.pytorch.tensor.
expand_dims
(
tensor
,
axis
)
[source]
deepxde.backend.pytorch.tensor.
from_numpy
(
np_array
)
[source]
deepxde.backend.pytorch.tensor.
gelu
(
x
)
[source]
deepxde.backend.pytorch.tensor.
is_gpu_available
(
)
[source]
deepxde.backend.pytorch.tensor.
is_tensor
(
obj
)
[source]
deepxde.backend.pytorch.tensor.
lgamma
(
x
)
[source]
deepxde.backend.pytorch.tensor.
matmul
(
x
,
y
)
[source]
deepxde.backend.pytorch.tensor.
max
(
input_tensor
,
dim
,
keepdims
=
False
)
[source]
deepxde.backend.pytorch.tensor.
mean
(
input_tensor
,
dim
,
keepdims
=
False
)
[source]
deepxde.backend.pytorch.tensor.
min
(
input_tensor
,
dim
,
keepdims
=
False
)
[source]
deepxde.backend.pytorch.tensor.
minimum
(
x
,
y
)
[source]
deepxde.backend.pytorch.tensor.
ndim
(
input_tensor
)
[source]
deepxde.backend.pytorch.tensor.
norm
(
tensor
,
ord
=
None
,
axis
=
None
,
keepdims
=
False
)
[source]
deepxde.backend.pytorch.tensor.
pow
(
x
,
y
)
[source]
deepxde.backend.pytorch.tensor.
prod
(
input_tensor
,
dim
,
keepdims
=
False
)
[source]
deepxde.backend.pytorch.tensor.
reduce_max
(
input_tensor
)
[source]
deepxde.backend.pytorch.tensor.
reduce_mean
(
input_tensor
)
[source]
deepxde.backend.pytorch.tensor.
reduce_min
(
input_tensor
)
[source]
deepxde.backend.pytorch.tensor.
reduce_prod
(
input_tensor
)
[source]
deepxde.backend.pytorch.tensor.
reduce_sum
(
input_tensor
)
[source]
deepxde.backend.pytorch.tensor.
relu
(
x
)
[source]
deepxde.backend.pytorch.tensor.
reshape
(
tensor
,
shape
)
[source]
deepxde.backend.pytorch.tensor.
reverse
(
tensor
,
axis
)
[source]
deepxde.backend.pytorch.tensor.
roll
(
tensor
,
shift
,
axis
)
[source]
deepxde.backend.pytorch.tensor.
selu
(
x
)
[source]
deepxde.backend.pytorch.tensor.
shape
(
input_tensor
)
[source]
deepxde.backend.pytorch.tensor.
sigmoid
(
x
)
[source]
deepxde.backend.pytorch.tensor.
silu
(
x
)
[source]
deepxde.backend.pytorch.tensor.
sin
(
x
)
[source]
deepxde.backend.pytorch.tensor.
size
(
tensor
)
[source]
deepxde.backend.pytorch.tensor.
sparse_dense_matmul
(
x
,
y
)
[source]
deepxde.backend.pytorch.tensor.
sparse_tensor
(
indices
,
values
,
shape
)
[source]
deepxde.backend.pytorch.tensor.
square
(
x
)
[source]
deepxde.backend.pytorch.tensor.
stack
(
values
,
axis
)
[source]
deepxde.backend.pytorch.tensor.
sum
(
input_tensor
,
dim
,
keepdims
=
False
)
[source]
deepxde.backend.pytorch.tensor.
tanh
(
x
)
[source]
deepxde.backend.pytorch.tensor.
to_numpy
(
input_tensor
)
[source]
deepxde.backend.pytorch.tensor.
transpose
(
tensor
,
axes
=
None
)
[source]
deepxde.backend.pytorch.tensor.
zeros
(
shape
,
dtype
)
[source]
deepxde.backend.pytorch.tensor.
zeros_like
(
input_tensor
)
[source]
Module contents
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v: stable
Versions
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stable
v1.11.1
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