The class provide base functionalities to shuffle the data to train a neural network
**Parameters**
data: Input data to be trainer
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
This datashuffler deal with memory databases that are stored in a :py:class`numpy.array`
**Parameters**
data: Input data to be trainer
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
@@ -19,14 +19,31 @@ class SiameseDisk(Siamese, Disk):
The data is loaded on the fly,.
**Parameters**
data: Input data to be trainer
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
@@ -17,14 +17,31 @@ class SiameseMemory(Siamese, Memory):
The data is loaded on the fly.
**Parameters**
data: Input data to be trainer
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
@@ -23,14 +23,31 @@ class TripletDisk(Triplet, Disk):
The data is loaded on the fly.
**Parameters**
data: Input data to be trainer
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
@@ -17,14 +17,31 @@ class TripletMemory(Triplet, Memory):
The data is loaded on the fly.
**Parameters**
data: Input data to be trainer
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
@@ -23,14 +23,30 @@ class TripletWithSelectionDisk(Triplet, Disk, OnLineSampling):
The selection of the triplets are random.
**Parameters**
data: Input data to be trainer
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
labels: Labels. These labels should be set from 0..1
input_shape: The shape of the inputs
input_dtype: The type of the data,
batch_size: Batch size
seed: The seed of the random number generator
data_augmentation: The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer: The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`
data:
Input data to be trainer
labels:
Labels. These labels should be set from 0..1
input_shape:
The shape of the inputs
input_dtype:
The type of the data,
batch_size:
Batch size
seed:
The seed of the random number generator
data_augmentation:
The algorithm used for data augmentation. Look :py:class:`bob.learn.tensorflow.datashuffler.DataAugmentation`
normalizer:
The algorithm used for feature scaling. Look :py:class:`bob.learn.tensorflow.datashuffler.ScaleFactor`, :py:class:`bob.learn.tensorflow.datashuffler.Linear` and :py:class:`bob.learn.tensorflow.datashuffler.MeanOffset`