def zeros(shape, dtype=None):
"""Initialize a tensor with zeros.
If dtype is *None*, use *config.floatX*.
Parameters
----------
shape : sequence of int
The shape of Tensor.
dtype : str, optional
The data type of Tensor.
Returns
-------
Tensor
The initialized tensor.
"""
if dtype is None: dtype = _cfg.floatX
return _ops.Fill(shape=shape, value=0, dtype=dtype)
def ones_like(model, dtype=None, **kwargs):
"""Initialize a tensor with ones, refer the shape of another tensor.
The values can be access only after the run of graph.
If dtype is ``None``, use ``config.floatX``.
Parameters
----------
model : Tensor
The tensor to refer shape.
dtype : str
The data type of Tensor.
Returns
-------
Tensor
The initialized tensor.
"""
if dtype is None: dtype = config.floatX
else:
raise TypeError("Unsupported data type: {}".format(dtype))
return ops.Fill(shape=ops.Shape(model), value=1)
def ones(shape, dtype=dtypes.float32, name=None):
return ops.Fill(shape, value=1.0, name=name)
def zeros(shape, dtype=dtypes.float32, name=None):
return ops.Fill(shape, value=0.0, name=name)
def __call__(self, shape, dtype=None, **kwargs):
if dtype is None: dtype = self.dtype
return _ops.Fill(shape, value=self.value, dtype=dtype.name)
def __call__(self, shape, dtype=None):
if dtype is None: dtype = self.dtype
return ops.Fill(shape, value=self.value)
