提交 ad979089 编写于 作者: A Abhinav Arora 提交者: kavyasrinet

Polish layer documentation for fill_constant ops (#6808)

上级 f734d0cb
......@@ -66,9 +66,26 @@ def assign(input, output):
def fill_constant(shape, dtype, value, out=None):
"""
This function creates a tensor , with shape as mentioned in the input and
specified dtype and fills this up with a constant value that
comes in the input. It also sets the stop_gradient to be True.
**fill_constant**
This function creates a tensor of specified *shape* and
*dtype*, and initializes this with a constant supplied in *value*.
It also sets *stop_gradient* to True.
Args:
shape(tuple|list|None): Shape of output tensor
dtype(np.dtype|core.DataType|str): Data type of output tensor
value(float): Constant value to initialize the output tensor
out(Variable): Output Variable to initialize
Returns:
Variable: The tensor variable storing the output
Examples:
.. code-block:: python
data = fluid.layers.fill_constant(shape=[1], value=0, dtype='int64')
"""
helper = LayerHelper("fill_constant", **locals())
if out is None:
......@@ -90,6 +107,31 @@ def fill_constant_batch_size_like(input,
value,
input_dim_idx=0,
output_dim_idx=0):
"""
**fill_constant_batch_size_like**
This function creates a tensor of specified *shape*, *dtype* and batch size,
and initializes this with a constant supplied in *value*. The batch size is
obtained from the `input` tensor.
It also sets *stop_gradient* to True.
Args:
input(Variable): Tensor whose dimensions will be used to get batch size
shape(tuple|list|None): Shape of output tensor
dtype(np.dtype|core.DataType|str): Data type of output tensor
value(float): Constant value to initialize the output tensor
input_dim_idx(int): Index of input's batch size dimension
output_dim_idx(int): Index of output's batch size dimension
Returns:
Variable: The tensor variable storing the output
Examples:
.. code-block:: python
data = fluid.layers.fill_constant(shape=[1], value=0, dtype='int64')
"""
helper = LayerHelper("fill_constant_batch_size_like", **locals())
out = helper.create_tmp_variable(dtype=dtype)
helper.append_op(
......
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