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TensorFlow.NET/src/TensorFlowNET.Core/tensorflow.cs at master · nhirschey/TensorFlow.NET · GitHub
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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
.
Collections
.
Generic
;
using
Serilog
;
using
Serilog
.
Core
;
using
Tensorflow
.
Contexts
;
using
Tensorflow
.
Eager
;
using
Tensorflow
.
Gradients
;
namespace
Tensorflow
{
public
delegate
Tensor
[
]
BackwardFunction
(
Tensor
[
]
grads
,
long
[
]
unneeded_gradients
)
;
public
partial
class
tensorflow
:
ITensorFlowObject
{
public
TF_DataType
byte8
=
TF_DataType
.
TF_UINT8
;
public
TF_DataType
int8
=
TF_DataType
.
TF_INT8
;
public
TF_DataType
int16
=
TF_DataType
.
TF_INT16
;
public
TF_DataType
int32
=
TF_DataType
.
TF_INT32
;
public
TF_DataType
int64
=
TF_DataType
.
TF_INT64
;
public
TF_DataType
float16
=
TF_DataType
.
TF_HALF
;
public
TF_DataType
float32
=
TF_DataType
.
TF_FLOAT
;
public
TF_DataType
float64
=
TF_DataType
.
TF_DOUBLE
;
public
TF_DataType
@bool
=
TF_DataType
.
TF_BOOL
;
public
TF_DataType
chars
=
TF_DataType
.
TF_STRING
;
public
TF_DataType
@string
=
TF_DataType
.
TF_STRING
;
public
Status
Status
;
public
OpDefLibrary
OpDefLib
;
public
Context
Context
;
public
IEagerRunner
Runner
;
public
Logger
Logger
;
public
tensorflow
(
)
{
Logger
=
new
LoggerConfiguration
(
)
.
MinimumLevel
.
Error
(
)
.
WriteTo
.
Console
(
)
.
CreateLogger
(
)
;
Status
=
new
Status
(
)
;
Context
=
new
Context
(
new
ContextOptions
(
)
,
Status
)
;
OpDefLib
=
new
OpDefLibrary
(
)
;
ConstructThreadingObjects
(
)
;
InitGradientEnvironment
(
)
;
Runner
=
new
EagerRunner
(
)
;
}
public
string
VERSION
=>
c_api
.
StringPiece
(
c_api
.
TF_Version
(
)
)
;
private
void
InitGradientEnvironment
(
)
{
ops
.
RegisterFromAssembly
(
)
;
}
public
ResourceVariable
Variable
<
T
>
(
T
data
,
bool
trainable
=
true
,
bool
validate_shape
=
true
,
bool
use_resource
=
true
,
string
name
=
null
,
TF_DataType
dtype
=
TF_DataType
.
DtInvalid
,
VariableAggregation
aggregation
=
VariableAggregation
.
None
,
int
[
]
shape
=
null
)
=>
new
ResourceVariable
(
data
,
trainable
:
trainable
,
validate_shape
:
validate_shape
,
name
:
name
,
dtype
:
dtype
,
aggregation
:
aggregation
,
shape
:
shape
)
;
public
Tensor
placeholder
(
TF_DataType
dtype
,
TensorShape
shape
=
null
,
string
name
=
null
)
=>
array_ops
.
placeholder
(
dtype
,
shape
,
name
)
;
public
void
enable_eager_execution
(
)
=>
Context
.
eager_mode
(
)
;
public
Session
get_default_session
(
)
=>
ops
.
get_default_session
(
)
;
public
Session
Session
(
)
{
return
new
Session
(
)
.
as_default
(
)
;
}
public
Session
Session
(
Graph
graph
,
ConfigProto
config
=
null
)
{
return
new
Session
(
graph
,
config
:
config
)
.
as_default
(
)
;
}
public
Session
Session
(
ConfigProto
config
)
{
return
new
Session
(
null
,
config
)
.
as_default
(
)
;
}
List
<
ITape
>
tape_set
;
public
List
<
ITape
>
GetTapeSet
(
)
{
if
(
tape_set
==
null
)
{
tape_set
=
new
List
<
ITape
>
(
)
;
}
return
tape_set
;
}
public
void
__init__
(
)
{
}
public
void
__enter__
(
)
{
}
public
void
__exit__
(
)
{
}
public
void
__del__
(
)
{
}
public
void
Dispose
(
)
{
}
}
}
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