def reshape(a, newshape):
"""Reshapes an array.
Args:
a: array_like. Could be an ndarray, a Tensor or any object that can
be converted to a Tensor using `tf.convert_to_tensor`.
newshape: 0-d or 1-d array_like.
Returns:
An ndarray with the contents and dtype of `a` and shape `newshape`.
"""
a = array_creation.asarray(a)
if isinstance(newshape, arrays.ndarray):
newshape = utils.get_shape_from_ndarray(newshape)
return utils.tensor_to_ndarray(tf.reshape(a.data, newshape))
def zeros(shape, dtype=float):
"""Returns an ndarray with the given shape and type filled with zeros.
Args:
shape: A fully defined shape. Could be
- NumPy array or a python scalar, list or tuple of integers,
- TensorFlow tensor/ndarray of integer type and rank <=1.
dtype: Optional, defaults to float. The type of the resulting ndarray.
Could be a python type, a NumPy type or a TensorFlow `DType`.
Returns:
An ndarray.
"""
if dtype:
dtype = utils.to_tf_type(dtype)
if isinstance(shape, arrays.ndarray):
shape = utils.get_shape_from_ndarray(shape)
return utils.tensor_to_ndarray(tf.zeros(shape, dtype=dtype))