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Fixed stacking of tensors with different dtypes

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-05-22 14:39:26 +02:00
parent 17e9208c21
commit dbf243c731
1 changed files with 1 additions and 2 deletions
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src/twomartens/masterthesis/data.py
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@ -330,7 +330,6 @@ def _load_images_ssd_callback(resized_shape: Sequence[int]) \
loaded images loaded images
""" """
_images = tf.map_fn(lambda path: tf.read_file(path), paths) _images = tf.map_fn(lambda path: tf.read_file(path), paths)
image_labels = tf.stack([_images, labels], axis=1)
def _get_images(image_data: tf.Tensor, def _get_images(image_data: tf.Tensor,
_labels: Sequence[int]) -> Tuple[tf.Tensor, Sequence[int]]: _labels: Sequence[int]) -> Tuple[tf.Tensor, Sequence[int]]:
@ -343,7 +342,7 @@ def _load_images_ssd_callback(resized_shape: Sequence[int]) \
return image_resized, _labels return image_resized, _labels
processed = tf.map_fn(_get_images, image_labels) processed = tf.map_fn(_get_images, (_images, labels))
processed_images = tf.reshape(processed[:, 0], [-1, resized_shape[0], resized_shape[1], 3]) processed_images = tf.reshape(processed[:, 0], [-1, resized_shape[0], resized_shape[1], 3])
return processed_images, processed[:, 1] return processed_images, processed[:, 1]