Comments (6)
I was able to fix this issue (so far) by having free_gpu() simply return without doing K.clear_session().
from deepswarm.
Hmm that's interesting I just ran the test with newest version in Google Colab and it works without any errors. Could you please provide following details:
- Operating system
- TensorFlow version
- Training sample code
from deepswarm.
- Windows 7 x64
- 1.13.1
dataset = Dataset(training_examples=x_train, training_labels=y_train, testing_examples=x_train, testing_labels=y_train)
backend = TFKerasBackend(dataset=dataset, optimizer=tf.keras.optimizers.Adam(1e-4))
deepswarm = DeepSwarm(backend=backend)
topology = deepswarm.find_topology()
trained_topology = deepswarm.train_topology(topology, 50)
the yaml
DeepSwarm:
save_folder:
metrics: accuracy
max_depth: 15
reuse_patience: 1
aco:
pheromone:
start: 0.1
decay: 0.1
evaporation: 0.1
verbose: False
greediness: 0.5
ant_count: 16
backend:
epochs: 15
batch_size: 16
patience: 5
loss: binary_crossentropy
verbose: True
spatial_nodes: [InputNode, Conv2DNode, DropoutSpatialNode, BatchNormalizationNode, Pool2DNode]
flat_nodes: [FlattenNode, DenseNode, DropoutFlatNode, BatchNormalizationFlatNode]
Nodes:
InputNode:
type: Input
attributes:
shape: [!!python/tuple [256, 256, 1]]
transitions:
Conv2DNode: 1.0
Conv2DNode:
type: Conv2D
attributes:
filter_count: [32, 64, 128]
kernel_size: [1, 3, 5]
activation: [ReLU]
transitions:
Conv2DNode: 0.8
Pool2DNode: 1.2
FlattenNode: 1.0
DropoutSpatialNode: 1.1
BatchNormalizationNode: 1.2
DropoutSpatialNode:
type: Dropout
attributes:
rate: [0.1, 0.3]
transitions:
Conv2DNode: 1.1
Pool2DNode: 1.0
FlattenNode: 1.0
BatchNormalizationNode: 1.1
BatchNormalizationNode:
type: BatchNormalization
attributes: {}
transitions:
Conv2DNode: 1.1
Pool2DNode: 1.1
DropoutSpatialNode: 1.0
FlattenNode: 1.0
Pool2DNode:
type: Pool2D
attributes:
pool_type: [max, average]
pool_size: [2]
stride: [2, 3]
transitions:
Conv2DNode: 1.1
FlattenNode: 1.0
BatchNormalizationNode: 1.1
FlattenNode:
type: Flatten
attributes: {}
transitions:
DenseNode: 1.0
OutputNode: 0.8
BatchNormalizationFlatNode: 0.9
DenseNode:
type: Dense
attributes:
output_size: [64, 128]
activation: [ReLU, Sigmoid]
transitions:
DenseNode: 0.8
DropoutFlatNode: 1.2
BatchNormalizationFlatNode: 1.2
OutputNode: 1.0
DropoutFlatNode:
type: Dropout
attributes:
rate: [0.1, 0.3]
transitions:
DenseNode: 1.0
BatchNormalizationFlatNode: 1.0
OutputNode: 0.9
BatchNormalizationFlatNode:
type: BatchNormalization
attributes: {}
transitions:
DenseNode: 1.1
DropoutFlatNode: 1.1
OutputNode: 0.9
OutputNode:
type: Output
attributes:
output_size: [1]
activation: [Sigmoid]
transitions: {}
from deepswarm.
Thank you, I located the issue and will update you once it has been fixed.
from deepswarm.
Sure. Also, if you update all your open(WindowPath) calls to open(str(WindowPath)) you should be python 3.5 compatible. open() and Pathlib are only seamless in 3.6.
from deepswarm.
Issue is now fixed in version 0.0.7. Regarding the Python version, thank you for the suggestion, but when developing the library decision was made to aim for Python 3.6, without any backward compatibility (as this allows easier development). At the moment I don't really see any problem with using 3.6 as the default version.
from deepswarm.
Related Issues (10)
- Readme should indicate this work only in python 3.6 and greater HOT 2
- Pytorch implementation HOT 1
- learning rate HOT 2
- builtins.NotImplementedError: numpy() is only available when eager execution is enabled. HOT 4
- Out of memory when saving object HOT 9
- [feature request] Add new evaluate_model function which can return a more generalized metric HOT 3
- Is "SPMT" spearmint? HOT 1
- 1D Option? HOT 1
- ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject HOT 12
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from deepswarm.