File size: 2,727 Bytes
233f6d4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | """ Unused for the moment, I believe. """
import tensorflow as tf
def get_shape(tensor):
"""Returns the tensor's shape.
Each shape element is either:
- an `int`, when static shape values are available, or
- a `tf.Tensor`, when the shape is dynamic.
Args:
tensor: A `tf.Tensor` to get the shape of.
Returns:
The `list` which contains the tensor's shape.
"""
shape_list = tensor.shape.as_list()
if all(s is not None for s in shape_list):
return shape_list
shape_tensor = tf.shape(tensor)
return [shape_tensor[i] if s is None else s for i, s in
enumerate(shape_list)]
def repeat(tensor, repeats, axis=0):
"""Repeats a `tf.Tensor`'s elements along an axis by custom amounts.
Equivalent to Numpy's `np.repeat`.
`tensor and `repeats` must have the same numbers of elements along `axis`.
Args:
tensor: A `tf.Tensor` to repeat.
repeats: A 1D sequence of the number of repeats per element.
axis: An axis to repeat along. Defaults to 0.
name: (string, optional) A name for the operation.
Returns:
The `tf.Tensor` with repeated values.
"""
cumsum = tf.cumsum(repeats)
range_ = tf.range(cumsum[-1])
indicator_matrix = tf.cast(tf.expand_dims(range_, 1) >= cumsum, tf.int32)
indices = tf.reduce_sum(indicator_matrix, reduction_indices=1)
shifted_tensor = _axis_to_inside(tensor, axis)
repeated_shifted_tensor = tf.gather(shifted_tensor, indices)
repeated_tensor = _inside_to_axis(repeated_shifted_tensor, axis)
shape = tensor.shape.as_list()
shape[axis] = None
repeated_tensor.set_shape(shape)
return repeated_tensor
def _axis_to_inside(tensor, axis):
"""Shifts a given axis of a tensor to be the innermost axis.
Args:
tensor: A `tf.Tensor` to shift.
axis: An `int` or `tf.Tensor` that indicates which axis to shift.
Returns:
The shifted tensor.
"""
axis = tf.convert_to_tensor(axis)
rank = tf.rank(tensor)
range0 = tf.range(0, limit=axis)
range1 = tf.range(tf.add(axis, 1), limit=rank)
perm = tf.concat([[axis], range0, range1], 0)
return tf.transpose(tensor, perm=perm)
def _inside_to_axis(tensor, axis):
"""Shifts the innermost axis of a tensor to some other axis.
Args:
tensor: A `tf.Tensor` to shift.
axis: An `int` or `tf.Tensor` that indicates which axis to shift.
Returns:
The shifted tensor.
"""
axis = tf.convert_to_tensor(axis)
rank = tf.rank(tensor)
range0 = tf.range(1, limit=axis + 1)
range1 = tf.range(tf.add(axis, 1), limit=rank)
perm = tf.concat([range0, [0], range1], 0)
return tf.transpose(tensor, perm=perm)
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