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The 2d x_value generation works for the generation of train_data, but not for test_data (still 1d).
The text was updated successfully, but these errors were encountered:
The issue is coming from the Colab notebook, since the data generation is designed for 1d regression. In particular, it arises from:
def generate_curves(self): num_context = tf.random_uniform(shape=[], minval=3, maxval=self._max_num_context, dtype=tf.int32) if self._testing: num_target = 400 num_total_points = num_target x_values = tf.tile( tf.expand_dims(tf.range(-2., 2., 1. / 100, dtype=tf.float32), axis=0), [self._batch_size, 1]) x_values = tf.expand_dims(x_values, axis=-1)
For 2d regression (MNIST) adaptions are necessary. For the encoder we have to make sure that it's accepting dynamic inputs in terms of dimensionality.
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l8git
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The 2d x_value generation works for the generation of train_data, but not for test_data (still 1d).
The text was updated successfully, but these errors were encountered: