diff options
Diffstat (limited to 'tensorflow/python/ops/clip_ops.py')
| -rw-r--r-- | tensorflow/python/ops/clip_ops.py | 36 |
1 files changed, 18 insertions, 18 deletions
diff --git a/tensorflow/python/ops/clip_ops.py b/tensorflow/python/ops/clip_ops.py index 85bbe38272..65e05626f0 100644 --- a/tensorflow/python/ops/clip_ops.py +++ b/tensorflow/python/ops/clip_ops.py @@ -40,13 +40,13 @@ def clip_by_value(t, clip_value_min, clip_value_max, greater than `clip_value_max` are set to `clip_value_max`. Args: - t: An `Output`. - clip_value_min: A 0-D (scalar) `Output`. The minimum value to clip by. - clip_value_max: A 0-D (scalar) `Output`. The maximum value to clip by. + t: A `Tensor`. + clip_value_min: A 0-D (scalar) `Tensor`. The minimum value to clip by. + clip_value_max: A 0-D (scalar) `Tensor`. The maximum value to clip by. name: A name for the operation (optional). Returns: - A clipped `Output`. + A clipped `Tensor`. """ with ops.name_scope(name, "clip_by_value", [t, clip_value_min, clip_value_max]) as name: @@ -82,15 +82,15 @@ def clip_by_norm(t, clip_norm, axes=None, name=None): an optimizer. Args: - t: An `Output`. - clip_norm: A 0-D (scalar) `Output` > 0. A maximum clipping value. - axes: A 1-D (vector) `Output` of type int32 containing the dimensions + t: A `Tensor`. + clip_norm: A 0-D (scalar) `Tensor` > 0. A maximum clipping value. + axes: A 1-D (vector) `Tensor` of type int32 containing the dimensions to use for computing the L2-norm. If `None` (the default), uses all dimensions. name: A name for the operation (optional). Returns: - A clipped `Output`. + A clipped `Tensor`. """ with ops.name_scope(name, "clip_by_norm", [t, clip_norm]) as name: t = ops.convert_to_tensor(t, name="t") @@ -116,11 +116,11 @@ def global_norm(t_list, name=None): Any entries in `t_list` that are of type None are ignored. Args: - t_list: A tuple or list of mixed `Output`s, `IndexedSlices`, or None. + t_list: A tuple or list of mixed `Tensors`, `IndexedSlices`, or None. name: A name for the operation (optional). Returns: - A 0-D (scalar) `Output` of type `float`. + A 0-D (scalar) `Tensor` of type `float`. Raises: TypeError: If `t_list` is not a sequence. @@ -181,15 +181,15 @@ def clip_by_global_norm(t_list, clip_norm, use_norm=None, name=None): ready before the clipping operation can be performed. Args: - t_list: A tuple or list of mixed `Output`s, `IndexedSlices`, or None. - clip_norm: A 0-D (scalar) `Output` > 0. The clipping ratio. - use_norm: A 0-D (scalar) `Output` of type `float` (optional). The global + t_list: A tuple or list of mixed `Tensors`, `IndexedSlices`, or None. + clip_norm: A 0-D (scalar) `Tensor` > 0. The clipping ratio. + use_norm: A 0-D (scalar) `Tensor` of type `float` (optional). The global norm to use. If not provided, `global_norm()` is used to compute the norm. name: A name for the operation (optional). Returns: - list_clipped: A list of `Output`s of the same type as `list_t`. - global_norm: A 0-D (scalar) `Output` representing the global norm. + list_clipped: A list of `Tensors` of the same type as `list_t`. + global_norm: A 0-D (scalar) `Tensor` representing the global norm. Raises: TypeError: If `t_list` is not a sequence. @@ -251,12 +251,12 @@ def clip_by_average_norm(t, clip_norm, name=None): an optimizer. Args: - t: An `Output`. - clip_norm: A 0-D (scalar) `Output` > 0. A maximum clipping value. + t: A `Tensor`. + clip_norm: A 0-D (scalar) `Tensor` > 0. A maximum clipping value. name: A name for the operation (optional). Returns: - A clipped `Output`. + A clipped `Tensor`. """ with ops.name_scope(name, "clip_by_average_norm", [t, clip_norm]) as name: t = ops.convert_to_tensor(t, name="t") |