Open GizemAyas517 opened 3 years ago
did you end up fixing this issue?
I Have the same problem.. Also trying to apply deeplift on a model which was trained with the cifar10 dataset. I use the same model from the Tutorial: Model: "sequential"
Layer (type) Output Shape Param
conv2d (Conv2D) (None, 32, 32, 32) 896
conv2d_1 (Conv2D) (None, 32, 32, 32) 9248
max_pooling2d (MaxPooling2D (None, 16, 16, 32) 0
)
dropout (Dropout) (None, 16, 16, 32) 0
conv2d_2 (Conv2D) (None, 16, 16, 64) 18496
conv2d_3 (Conv2D) (None, 16, 16, 64) 36928
max_pooling2d_1 (MaxPooling (None, 8, 8, 64) 0
2D)
dropout_1 (Dropout) (None, 8, 8, 64) 0
conv2d_4 (Conv2D) (None, 8, 8, 128) 73856
conv2d_5 (Conv2D) (None, 8, 8, 128) 147584
max_pooling2d_2 (MaxPooling (None, 4, 4, 128) 0
2D)
dropout_2 (Dropout) (None, 4, 4, 128) 0
flatten (Flatten) (None, 2048) 0
dense (Dense) (None, 128) 262272
dropout_3 (Dropout) (None, 128) 0
dense_1 (Dense) (None, 10) 774
================================================================= Total params: 550,054 Trainable params: 550,054 Non-trainable params: 0
The code for the DeepLIFT implementation is from the MNIST-example: Code:
import deeplift
from deeplift.layers import NonlinearMxtsMode
from deeplift.conversion import kerasapi_conversion as kc
deeplift_model =\
kc.convert_model_from_saved_files(
h5_file='model4cifar10.h5',
nonlinear_mxts_mode=deeplift.layers.NonlinearMxtsMode.DeepLIFT_GenomicsDefault)
And I get the exact same errormessage.
Hello all (sorry for the late reply, I've been navigating some health issues): deeplift was developed with what is now a very old version of tensorflow and keras, and was not designed to work with tf.keras; I recommend using one of the more recent implementations of deeplift mentioned in the FAQ, as those are being actively maintained. They don't have the revealcancel rule, but unfortunately I don't have the bandwidth to maintain this project since I've graduated
On Tue, 9 Aug 2022 at 14:47, Nico @.***> wrote:
I Have the same problem.. Also trying to apply deeplift on a model which was trained with the cifar10 dataset. I use this model: Model: "sequential"
Layer (type) Output Shape Param #
conv2d (Conv2D) (None, 32, 32, 32) 896
conv2d_1 (Conv2D) (None, 32, 32, 32) 9248
max_pooling2d (MaxPooling2D (None, 16, 16, 32) 0 )
dropout (Dropout) (None, 16, 16, 32) 0
conv2d_2 (Conv2D) (None, 16, 16, 64) 18496
conv2d_3 (Conv2D) (None, 16, 16, 64) 36928
max_pooling2d_1 (MaxPooling (None, 8, 8, 64) 0 2D)
dropout_1 (Dropout) (None, 8, 8, 64) 0
conv2d_4 (Conv2D) (None, 8, 8, 128) 73856
conv2d_5 (Conv2D) (None, 8, 8, 128) 147584
max_pooling2d_2 (MaxPooling (None, 4, 4, 128) 0 2D)
dropout_2 (Dropout) (None, 4, 4, 128) 0
flatten (Flatten) (None, 2048) 0
dense (Dense) (None, 128) 262272
dropout_3 (Dropout) (None, 128) 0
dense_1 (Dense) (None, 6) 774
================================================================= Total params: 550,054 Trainable params: 550,054 Non-trainable params: 0
The code for the DeepLIFT implementation is from the MNIST-example: https://github.com/kundajelab/deeplift/blob/master/examples/mnist/MNIST_replicate_figures.ipynb Code:
import deeplift from deeplift.layers import NonlinearMxtsMode from deeplift.conversion import kerasapi_conversion as kc deeplift_model =\ kc.convert_model_from_saved_files( h5_file='model4cifar10.h5', nonlinear_mxts_mode=deeplift.layers.NonlinearMxtsMode.DeepLIFT_GenomicsDefault)
And I get the exact same errormessage.
— Reply to this email directly, view it on GitHub https://github.com/kundajelab/deeplift/issues/124#issuecomment-1209126702, or unsubscribe https://github.com/notifications/unsubscribe-auth/AARSFBXRHB7K6SGAMGSVRD3VYIOY3ANCNFSM5EZGAX6A . You are receiving this because you are subscribed to this thread.Message ID: @.***>
Hello,
Before getting into my question, just wanted to say I really enjoyed reading the paper and also exploring the codebase. Many thanks for deeplift!
I've been trying to use deeplift with cifar10 but I've came across a problem:
the model and cifar10 dataset I've been using: https://machinelearningmastery.com/object-recognition-convolutional-neural-networks-keras-deep-learning-library/
I save the trained model with the command below:
model.save('my_cifar_model.h5', save_format='h5')
when I run this command everything seems fine:
import keras saved_model_file = "my_cifar_model.h5" model = keras.models.load_model(saved_model_file) model.summary()
However when I try to create a deeplift reveal cancel model:
`import deeplift from deeplift.layers import NonlinearMxtsMode from deeplift.conversion import kerasapi_conversion as kc
revealcancel_model = kc.convert_model_from_saved_files( h5_file=saved_model_file, nonlinear_mxts_mode=NonlinearMxtsMode.RevealCancel) ` I get this error: TypeError: can only concatenate str (not "KeysViewHDF5") to str What do you think I can do to solve it? Are there any deeplift examples with cifar10?
Thanks!