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TensorFlow.NET/src/TensorFlowNET.Core/APIs/tf.array.cs at master · Jiuyong/TensorFlow.NET · GitHub
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TensorFlow.NET
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src
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TensorFlowNET.Core
/
APIs
/
tf.array.cs
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TensorFlow.NET
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TensorFlowNET.Core
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APIs
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tf.array.cs
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/*****************************************************************************
Copyright 2018 The TensorFlow.NET Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
******************************************************************************/
using
System
;
using
System
.
Collections
.
Generic
;
using
System
.
Linq
;
namespace
Tensorflow
{
public
static
partial
class
tf
{
/// <summary>
/// Concatenates tensors along one dimension.
/// </summary>
/// <param name="values">A list of `Tensor` objects or a single `Tensor`.</param>
/// <param name="axis"></param>
/// <param name="name"></param>
/// <returns>A `Tensor` resulting from concatenation of the input tensors.</returns>
public
static
Tensor
concat
(
IList
<
Tensor
>
values
,
int
axis
,
string
name
=
"concat"
)
{
if
(
values
.
Count
==
1
)
throw
new
NotImplementedException
(
"tf.concat length is 1"
)
;
return
gen_array_ops
.
concat_v2
(
values
.
ToArray
(
)
,
axis
,
name
:
name
)
;
}
/// <summary>
/// Inserts a dimension of 1 into a tensor's shape.
/// </summary>
/// <param name="input"></param>
/// <param name="axis"></param>
/// <param name="name"></param>
/// <param name="dim"></param>
/// <returns>
/// A `Tensor` with the same data as `input`, but its shape has an additional
/// dimension of size 1 added.
/// </returns>
public
static
Tensor
expand_dims
(
Tensor
input
,
int
axis
=
-
1
,
string
name
=
null
,
int
dim
=
-
1
)
=>
array_ops
.
expand_dims
(
input
,
axis
,
name
,
dim
)
;
/// <summary>
/// Creates a tensor filled with a scalar value.
/// </summary>
/// <param name="dims"></param>
/// <param name="value"></param>
/// <param name="name"></param>
/// <returns></returns>
public
static
Tensor
fill
<
T
>
(
Tensor
dims
,
T
value
,
string
name
=
null
)
=>
gen_array_ops
.
fill
(
dims
,
value
,
name
:
name
)
;
/// <summary>
/// Return the elements, either from `x` or `y`, depending on the `condition`.
/// </summary>
/// <returns></returns>
public
static
Tensor
where
<
Tx
,
Ty
>
(
Tensor
condition
,
Tx
x
,
Ty
y
,
string
name
=
null
)
=>
array_ops
.
where
(
condition
,
x
,
y
,
name
)
;
/// <summary>
/// Transposes `a`. Permutes the dimensions according to `perm`.
/// </summary>
/// <param name="a"></param>
/// <param name="perm"></param>
/// <param name="name"></param>
/// <param name="conjugate"></param>
/// <returns></returns>
public
static
Tensor
transpose
<
T1
>
(
T1
a
,
int
[
]
perm
=
null
,
string
name
=
"transpose"
,
bool
conjugate
=
false
)
=>
array_ops
.
transpose
(
a
,
perm
,
name
,
conjugate
)
;
public
static
Tensor
squeeze
(
Tensor
input
,
int
[
]
axis
=
null
,
string
name
=
null
,
int
squeeze_dims
=
-
1
)
=>
gen_array_ops
.
squeeze
(
input
,
axis
,
name
)
;
/// <summary>
/// Stacks a list of rank-`R` tensors into one rank-`(R+1)` tensor.
/// </summary>
/// <param name="values"></param>
/// <param name="axis"></param>
/// <param name="name"></param>
/// <returns></returns>
public
static
Tensor
stack
(
object
values
,
int
axis
=
0
,
string
name
=
"stack"
)
=>
array_ops
.
stack
(
values
,
axis
,
name
:
name
)
;
public
static
Tensor
one_hot
(
Tensor
indices
,
int
depth
,
Tensor
on_value
=
null
,
Tensor
off_value
=
null
,
TF_DataType
dtype
=
TF_DataType
.
DtInvalid
,
int
axis
=
-
1
,
string
name
=
null
)
=>
array_ops
.
one_hot
(
indices
,
depth
,
dtype
:
dtype
,
axis
:
axis
,
name
:
name
)
;
/// <summary>
/// A placeholder op that passes through `input` when its output is not fed.
/// </summary>
/// <typeparam name="T"></typeparam>
/// <param name="input">A `Tensor`. The default value to produce when output is not fed.</param>
/// <param name="shape">
/// A `tf.TensorShape` or list of `int`s. The (possibly partial) shape of
/// the tensor.
/// </param>
/// <param name="name">A name for the operation (optional).</param>
/// <returns>A `Tensor`. Has the same type as `input`.</returns>
public
static
Tensor
placeholder_with_default
<
T
>
(
T
input
,
int
[
]
shape
,
string
name
=
null
)
=>
gen_array_ops
.
placeholder_with_default
(
input
,
shape
,
name
:
name
)
;
}
}
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