本文整理汇总了Python中tensorflow.python.ops.gen_math_ops._conj方法的典型用法代码示例。如果您正苦于以下问题：Python gen_math_ops._conj方法的具体用法？Python gen_math_ops._conj怎么用？Python gen_math_ops._conj使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类tensorflow.python.ops.gen_math_ops的用法示例。
在下文中一共展示了gen_math_ops._conj方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: conj
# 需要导入模块: from tensorflow.python.ops import gen_math_ops [as 别名]
# 或者: from tensorflow.python.ops.gen_math_ops import _conj [as 别名]
def conj(x, name=None):
r"""Returns the complex conjugate of a complex number.
Given a tensor `input` of complex numbers, this operation returns a tensor of
complex numbers that are the complex conjugate of each element in `input`. The
complex numbers in `input` must be of the form \\(a + bj\\), where *a* is the
real part and *b* is the imaginary part.
The complex conjugate returned by this operation is of the form \\(a - bj\\).
For example:
# tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j]
tf.conj(input) ==> [-2.25 - 4.75j, 3.25 - 5.75j]
If `x` is real, it is returned unchanged.
Args:
x: `Tensor` to conjugate. Must have numeric type.
name: A name for the operation (optional).
Returns:
A `Tensor` that is the conjugate of `x` (with the same type).
Raises:
TypeError: If `x` is not a numeric tensor.
"""
with ops.name_scope(name, "Conj", [x]) as name:
x = ops.convert_to_tensor(x, name="x")
if x.dtype.is_complex:
return gen_math_ops._conj(x, name=name)
elif x.dtype.is_floating or x.dtype.is_integer:
return x
else:
raise TypeError("Expected numeric tensor, got dtype %r" % x.dtype) 示例2: conj
# 需要导入模块: from tensorflow.python.ops import gen_math_ops [as 别名]
# 或者: from tensorflow.python.ops.gen_math_ops import _conj [as 别名]
def conj(x, name=None):
r"""Returns the complex conjugate of a complex number.
Given a tensor `input` of complex numbers, this operation returns a tensor of
complex numbers that are the complex conjugate of each element in `input`. The
complex numbers in `input` must be of the form \\(a + bj\\), where *a* is the
real part and *b* is the imaginary part.
The complex conjugate returned by this operation is of the form \\(a - bj\\).
For example:
# tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j]
tf.conj(input) ==> [-2.25 - 4.75j, 3.25 - 5.75j]
If `x` is real, it is returned unchanged.
Args:
x: `Tensor` to conjugate. Must have numeric or variant type.
name: A name for the operation (optional).
Returns:
A `Tensor` that is the conjugate of `x` (with the same type).
Raises:
TypeError: If `x` is not a numeric tensor.
"""
if isinstance(x, ops.Tensor):
dt = x.dtype
if dt.is_floating or dt.is_integer:
return x
with ops.name_scope(name, "Conj", [x]) as name:
x = ops.convert_to_tensor(x, name="x")
if x.dtype.is_complex or x.dtype == dtypes.variant:
return gen_math_ops._conj(x, name=name)
elif x.dtype.is_floating or x.dtype.is_integer:
return x
else:
raise TypeError(
"Expected numeric or variant tensor, got dtype %r" % x.dtype) 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:42，代码来源:math_ops.py