Google I/O returns May 18-20! Reserve space and build your schedule Register now


Computes model_matrix @ model_coefficients + offset.

model_matrix (Batch of) float-like, matrix-shaped Tensor where each row represents a sample's features.
model_coefficients (Batch of) vector-shaped Tensor representing the model coefficients, one for each column in model_matrix. Must have same dtype as model_matrix.
offset Optional Tensor representing constant shift applied to predicted_linear_response. Must broadcast to response. Default value: None (i.e., tf.zeros_like(predicted_linear_response)).
name Python str used as name prefix to ops created by this function. Default value: None (i.e., "compute_predicted_linear_response").

predicted_linear_response response-shaped Tensor representing linear predictions based on new model_coefficients, i.e., tf.linalg.matvec(model_matrix, model_coefficients) + offset.