Skip to content

fix: Support for training a multi-input model using a dataset. #1263

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 3 commits into from
Jul 2, 2024
Merged

fix: Support for training a multi-input model using a dataset. #1263

Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
5142ad6
test: Added an `evaluate` method call to a unit test for a multi-inpu…
ASolomatin Jun 30, 2024
f8b7bde
test: Added a unit test of training a multi-input model using a dataset.
ASolomatin Jun 30, 2024
93dda17
fix: Added support for training a multi-input model using a dataset.
ASolomatin Jun 30, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Next Next commit
test: Added an evaluate method call to a unit test for a multi-inpu… 
…t model.
  • Loading branch information
@ASolomatin
ASolomatin committed Jul 1, 2024
commit 5142ad658cf9233abd2c9fe727c2daeea84a88f6
7 changes: 7 additions & 0 deletions test/TensorFlowNET.Keras.UnitTest/MultiInputModelTest.cs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,13 @@ public void LeNetModel()
var x = new NDArray[] { x1, x2 };
model.fit(x, dataset.Train.Labels, batch_size: 8, epochs: 3);

x1 = x1["0:8"];
x2 = x1;

x = new NDArray[] { x1, x2 };
var y = dataset.Train.Labels["0:8"];
(model as Engine.Model).evaluate(x, y);

x1 = np.ones((1, 28, 28, 1), TF_DataType.TF_FLOAT);
x2 = np.zeros((1, 28, 28, 1), TF_DataType.TF_FLOAT);
var pred = model.predict((x1, x2));
Expand Down