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Shashank Suhas
seminar-breakout
Commits
23f2ccd6
Commit
23f2ccd6
authored
Apr 12, 2016
by
Yuxin Wu
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name correction in validatestatprinter
parent
dcbd4696
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7 additions
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6 deletions
+7
-6
README.md
README.md
+4
-5
tensorpack/callbacks/validation_callback.py
tensorpack/callbacks/validation_callback.py
+3
-1
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README.md
View file @
23f2ccd6
# tensorpack
# tensorpack
Neural Network Toolbox
based
on TensorFlow
Neural Network Toolbox on TensorFlow
In development. No document
, don't use
.
In development. No document.
## Features:
## Features:
+
Scoped abstraction of common models.
+
Scoped abstraction of common models.
+
Provide callbacks to control training behavior (as in
[
Keras
](
http://keras.io
)
)
.
+
Callbacks systems to control different aspects of training
.
+
Use
`Dataflow`
to gain fine-grained control on data preprocessing.
+
Use
`Dataflow`
to gain fine-grained control on data preprocessing.
+
Automatically use the Queue operator in tensorflow to speed up input.
+
Training and testing graph are modeled together. Just need to follow the conventions to setup stuffs.
+
Training and testing graph are modeled together. Just need to follow the conventions to setup stuffs.
+
Use tensorboard easily
.
+
Write summary easier for tensorboard
.
tensorpack/callbacks/validation_callback.py
View file @
23f2ccd6
...
@@ -9,6 +9,7 @@ from six.moves import zip
...
@@ -9,6 +9,7 @@ from six.moves import zip
from
..utils
import
*
from
..utils
import
*
from
..utils.stat
import
*
from
..utils.stat
import
*
from
..tfutils
import
*
from
..tfutils.summary
import
*
from
..tfutils.summary
import
*
from
.base
import
PeriodicCallback
,
Callback
,
TestCallbackType
from
.base
import
PeriodicCallback
,
Callback
,
TestCallbackType
...
@@ -82,7 +83,8 @@ class ValidationStatPrinter(ValidationCallback):
...
@@ -82,7 +83,8 @@ class ValidationStatPrinter(ValidationCallback):
self
.
names
=
names_to_print
self
.
names
=
names_to_print
def
_find_output_vars
(
self
):
def
_find_output_vars
(
self
):
self
.
vars_to_print
=
[
self
.
get_tensor
(
n
)
for
n
in
self
.
names
]
self
.
vars_to_print
=
[
self
.
get_tensor
(
get_op_var_name
(
n
)[
1
])
for
n
in
self
.
names
]
def
_get_output_vars
(
self
):
def
_get_output_vars
(
self
):
return
self
.
vars_to_print
return
self
.
vars_to_print
...
...
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