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Removed support for Tensorflow 1.x
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Min version is 2.3, for full compatibility with TFLite and Coral.
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@feranick
feranick committed May 11, 2021
1 parent a4f2fb8 commit d8e511b
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Showing 7 changed files with 36 additions and 76 deletions.
3 changes: 1 addition & 2 deletions README.md
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Expand Up @@ -42,8 +42,7 @@ This software requires Python (3.6 or higher). It has been tested with Python 3.
pydot
graphviz
h5py
tensorflow

tensorflow (>=2.3, not compatible with TF 1.x)

In addition, these packages may be needed depending on your platform (via ```apt-get``` in debian/ubuntu or ```port``` in OSX):

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48 changes: 15 additions & 33 deletions SpectraKeras/SpectraKeras_CNN.py
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Expand Up @@ -3,7 +3,7 @@
'''
**********************************************************
* SpectraKeras_CNN Classifier and Regressor
* 20201210a
* 20210510a
* Uses: TensorFlow
* By: Nicola Ferralis <[email protected]>
***********************************************************
Expand Down Expand Up @@ -214,34 +214,19 @@ def train(learnFile, testFile, flag):

from pkg_resources import parse_version
import tensorflow as tf

if parse_version(tf.version.VERSION) < parse_version('2.0.0'):
useTF2 = False
else:
useTF2 = True

if useTF2:
opts = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=1) # Tensorflow 2.0
conf = tf.compat.v1.ConfigProto(gpu_options=opts) # Tensorflow 2.0

gpus = tf.config.list_physical_devices('GPU')
if gpus:
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
# if dP.setMaxMem:
# tf.config.set_virtual_device_configuration(
# gpus[0],
# [tf.config.VirtualDeviceConfiguration(memory_limit=dP.maxMem)])

else:
tf.compat.v1.enable_eager_execution()
opts = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=1)
conf = tf.compat.v1.ConfigProto(gpu_options=opts)
conf.gpu_options.allow_growth = True

tf.compat.v1.Session(config=conf)

import tensorflow.keras as keras

opts = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=1) # Tensorflow 2.0
conf = tf.compat.v1.ConfigProto(gpu_options=opts) # Tensorflow 2.0

gpus = tf.config.list_physical_devices('GPU')
if gpus:
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
# if dP.setMaxMem:
# tf.config.set_virtual_device_configuration(
# gpus[0],
# [tf.config.VirtualDeviceConfiguration(memory_limit=dP.maxMem)])

learnFileRoot = os.path.splitext(learnFile)[0]
En, A, Cl = readLearnFile(learnFile, dP)
Expand Down Expand Up @@ -392,11 +377,8 @@ def train(learnFile, testFile, flag):
callbacks = tbLogs,
verbose=2,
validation_split=dP.cv_split)

if useTF2:
model.save(dP.model_name, save_format='h5')
else:
model.save(dP.model_name)

model.save(dP.model_name, save_format='h5')
keras.utils.plot_model(model, to_file=dP.model_png, show_shapes=True)
model.summary()

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46 changes: 14 additions & 32 deletions SpectraKeras/SpectraKeras_MLP.py
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Expand Up @@ -3,7 +3,7 @@
'''
**********************************************************
* SpectraKeras_MLP Classifier and Regressor
* 20201210a
* 20210510a
* Uses: TensorFlow
* By: Nicola Ferralis <[email protected]>
***********************************************************
Expand Down Expand Up @@ -191,33 +191,17 @@ def train(learnFile, testFile):
import tensorflow as tf
import tensorflow.keras as keras

if parse_version(tf.version.VERSION) < parse_version('2.0.0'):
useTF2 = False
else:
useTF2 = True

if useTF2:
opts = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=1) # Tensorflow 2.0
conf = tf.compat.v1.ConfigProto(gpu_options=opts) # Tensorflow 2.0
opts = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=1) # Tensorflow 2.0
conf = tf.compat.v1.ConfigProto(gpu_options=opts) # Tensorflow 2.0

gpus = tf.config.list_physical_devices('GPU')
if gpus:
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
# if dP.setMaxMem:
# tf.config.set_virtual_device_configuration(
# gpus[0],
# [tf.config.VirtualDeviceConfiguration(memory_limit=dP.maxMem)])

else:
tf.compat.v1.enable_eager_execution()
opts = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=1)
conf = tf.compat.v1.ConfigProto(gpu_options=opts)
conf.gpu_options.allow_growth = True

tf.compat.v1.Session(config=conf)

import tensorflow.keras as keras
gpus = tf.config.list_physical_devices('GPU')
if gpus:
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
# if dP.setMaxMem:
# tf.config.set_virtual_device_configuration(
# gpus[0],
# [tf.config.VirtualDeviceConfiguration(memory_limit=dP.maxMem)])

learnFileRoot = os.path.splitext(learnFile)[0]

Expand Down Expand Up @@ -332,11 +316,9 @@ def train(learnFile, testFile):
callbacks = tbLogs,
verbose=2,
validation_split=dP.cv_split)

if useTF2:
model.save(dP.model_name, save_format='h5')
else:
model.save(dP.model_name)

model.save(dP.model_name, save_format='h5')

keras.utils.plot_model(model, to_file=dP.model_png, show_shapes=True)
model.summary()

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9 changes: 3 additions & 6 deletions SpectraKeras/libSpectraKeras.py
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Expand Up @@ -2,7 +2,7 @@
'''
**********************************************************
* libSpectraKeas - Library for SpectraKeras
* 20201210a
* 20210510a
* Uses: TensorFlow
* By: Nicola Ferralis <[email protected]>
***********************************************************
Expand Down Expand Up @@ -144,11 +144,8 @@ def representative_dataset_gen():
for input_value in A.take(100):
yield[input_value]

try:
#converter = tf.compat.v1.lite.TFLiteConverter.from_keras_model_file(dP.model_name) # TF2.0-2.2 (will be deprecated)
converter = tf.lite.TFLiteConverter.from_keras_model(model) # TF2.3 and higher only.
except:
converter = tf.lite.TFLiteConverter.from_keras_model_file(dP.model_name) # T1.x
#converter = tf.compat.v1.lite.TFLiteConverter.from_keras_model_file(dP.model_name) # TF2.0-2.2 (will be deprecated)
converter = tf.lite.TFLiteConverter.from_keras_model(model) # TF2.3 and higher only.

#converter.optimizations = [tf.lite.Optimize.DEFAULT]
#converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_LATENCY]
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2 changes: 1 addition & 1 deletion SpectraKeras/setup-gpu.py
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Expand Up @@ -7,7 +7,7 @@
entry_points={'console_scripts' : ['SpectraKeras_MLP=SpectraKeras_MLP:SpectraKeras_MLP',
'SpectraKeras_CNN=SpectraKeras_CNN:SpectraKeras_CNN']},
py_modules=['SpectraKeras_MLP','SpectraKeras_CNN','libSpectraKeras'],
version='20201210a',
version='20210510a',
description='Machine learning for spectral data',
long_description= """ Machine learning for spectral data """,
author='Nicola Ferralis',
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2 changes: 1 addition & 1 deletion SpectraKeras/setup-tflite.py
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Expand Up @@ -7,7 +7,7 @@
entry_points={'console_scripts' : ['SpectraKeras_MLP=SpectraKeras_MLP:SpectraKeras_MLP',
'SpectraKeras_CNN=SpectraKeras_CNN:SpectraKeras_CNN']},
py_modules=['SpectraKeras_MLP','SpectraKeras_CNN','libSpectraKeras'],
version='20201210a',
version='20210510a',
description='Machine learning for spectral data',
long_description= """ Machine learning for spectral data """,
author='Nicola Ferralis',
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2 changes: 1 addition & 1 deletion SpectraKeras/setup.py
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Expand Up @@ -7,7 +7,7 @@
entry_points={'console_scripts' : ['SpectraKeras_MLP=SpectraKeras_MLP:SpectraKeras_MLP',
'SpectraKeras_CNN=SpectraKeras_CNN:SpectraKeras_CNN']},
py_modules=['SpectraKeras_MLP','SpectraKeras_CNN','libSpectraKeras'],
version='20201210a',
version='20210510a',
description='Machine learning for spectral data',
long_description= """ Machine learning for spectral data """,
author='Nicola Ferralis',
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