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Use tracker context in kernel models demo #992

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Use tracker context in kernel models demo #992

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bd92d3f
use tracker context
isaacdevlugt Nov 30, 2023
720a07c
Merge branch 'master' into kernel-based-models-demo-num-executions
isaacdevlugt May 3, 2024
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17 changes: 11 additions & 6 deletions demonstrations/tutorial_kernel_based_training.py
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Original file line number Diff line number Diff line change
Expand Up @@ -288,10 +288,13 @@ def kernel_matrix(A, B):
# Training the SVM optimizes internal parameters that basically
# weigh kernel functions.
# It is a breeze in scikit-learn, which is designed
# as a high-level machine learning library:
# as a high-level machine learning library (we'll put this in a
# ``qml.Tracker`` context so that we can
# track device executions):
#

svm = SVC(kernel=kernel_matrix).fit(X_train, y_train)
with qml.Tracker(dev_kernel) as tracker:
svm = SVC(kernel=kernel_matrix).fit(X_train, y_train)


######################################################################
Expand All @@ -307,7 +310,7 @@ def kernel_matrix(A, B):
# How many times was the quantum device evaluated?
#

dev_kernel.num_executions
tracker.totals['executions']


######################################################################
Expand Down Expand Up @@ -485,7 +488,9 @@ def quantum_model_predict(X_pred, trained_params, trained_bias):
n_layers = 2
batch_size = 20
steps = 100
trained_params, trained_bias, loss_history = quantum_model_train(n_layers, steps, batch_size)

with qml.Tracker(dev_var) as tracker:
trained_params, trained_bias, loss_history = quantum_model_train(n_layers, steps, batch_size)

pred_test = quantum_model_predict(X_test, trained_params, trained_bias)
print("accuracy on test set:", accuracy_score(pred_test, y_test))
Expand All @@ -506,7 +511,7 @@ def quantum_model_predict(X_pred, trained_params, trained_bias):
# How often was the device executed?
#

dev_var.num_executions
tracker.totals['executions']


######################################################################
Expand Down Expand Up @@ -688,4 +693,4 @@ def model_evals_nn(n_data, n_params, n_steps, split, batch_size):
##############################################################################
# About the author
# ----------------
# .. include:: ../_static/authors/maria_schuld.txt
# .. include:: ../_static/authors/maria_schuld.txt
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