Python gen_math_ops.sqrt方法代码示例

# 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 sqrt [as 别名]
def sqrt(x, name=None):
  r"""Computes square root of x element-wise.

  I.e., \\(y = \sqrt{x} = x^{1/2}\\).

  Args:
    x: A `Tensor` or `SparseTensor`. Must be one of the following types: `half`,
      `float32`, `float64`, `complex64`, `complex128`.
    name: A name for the operation (optional).

  Returns:
    A `Tensor` or `SparseTensor`, respectively. Has the same type as `x`.
  """
  with ops.name_scope(name, "Sqrt", [x]) as name:
    if isinstance(x, sparse_tensor.SparseTensor):
      x_sqrt = gen_math_ops.sqrt(x.values, name=name)
      return sparse_tensor.SparseTensor(
          indices=x.indices, values=x_sqrt, dense_shape=x.dense_shape)
    else:
      return gen_math_ops.sqrt(x, name=name) 

# 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 sqrt [as 别名]
def sqrt(x, name=None):
  """Computes square root of x element-wise.

  I.e., \\(y = \sqrt{x} = x^{1/2}\\).

  Args:
    x: A `Tensor` or `SparseTensor`. Must be one of the following types: `half`,
      `float32`, `float64`, `complex64`, `complex128`.
    name: A name for the operation (optional).

  Returns:
    A `Tensor` or `SparseTensor`, respectively. Has the same type as `x`.
  """
  with ops.name_scope(name, "Sqrt", [x]) as name:
    if isinstance(x, sparse_tensor.SparseTensor):
      x_sqrt = gen_math_ops.sqrt(x.values, name=name)
      return sparse_tensor.SparseTensor(
          indices=x.indices, values=x_sqrt, dense_shape=x.dense_shape)
    else:
      return gen_math_ops.sqrt(x, name=name) 

# 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 sqrt [as 别名]
def sqrt(x, name=None):
  """Computes square root of x element-wise.

  I.e., \\(y = \sqrt{x} = x^{1/2}\\).

  Args:
    x: A `Tensor` or `SparseTensor`. Must be one of the following types: `half`,
      `float32`, `float64`, `complex64`, `complex128`.
    name: A name for the operation (optional).

  Returns:
    A `Tensor` or `SparseTensor`, respectively. Has the same type as `x`.
  """
  with ops.name_scope(name, "Sqrt", [x]) as name:
    if isinstance(x, sparse_tensor.SparseTensor):
      x_sqrt = gen_math_ops.sqrt(x.values, name=name)
      return sparse_tensor.SparseTensor(
          indices=x.indices, values=x_sqrt, shape=x.shape)
    else:
      return gen_math_ops.sqrt(x, name=name) 

# 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 sqrt [as 别名]
def complex_abs(x, name=None):
  r"""Computes the complex absolute value of a tensor.

  Given a tensor `x` of complex numbers, this operation returns a tensor of type
  `float32` or `float64` that is the absolute value of each element in `x`. All
  elements in `x` must be complex numbers of the form \\(a + bj\\). The
  absolute value is computed as \\( \sqrt{a^2 + b^2}\\).

  For example:

  ```
  # tensor 'x' is [[-2.25 + 4.75j], [-3.25 + 5.75j]]
  tf.complex_abs(x) ==> [5.25594902, 6.60492229]
  ```

  Args:
    x: A `Tensor` of type `complex64` or `complex128`.
    name: A name for the operation (optional).

  Returns:
    A `Tensor` of type `float32` or `float64`.
  """
  return gen_math_ops.complex_abs(x, Tout=x.dtype.real_dtype, name=name) 

# 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 sqrt [as 别名]
def call(self, inputs):
        inputs = ops.convert_to_tensor(inputs, dtype=self.dtype)
        if common_shapes.rank(inputs) is not 2: 
            raise ValueError('`StressIntensityRange` only takes "rank 2" inputs.')

        output = gen_math_ops.mul(self.kernel*inputs[:,1], gen_math_ops.sqrt(np.pi*inputs[:, 0]))
        output = array_ops.reshape(output, (array_ops.shape(output)[0], 1))

        # outputs should be (None, 1), so it is still rank = 2
        return output 

# 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 sqrt [as 别名]
def abs(x, name=None):
  r"""Computes the absolute value of a tensor.

  Given a tensor `x` of complex numbers, this operation returns a tensor of type
  `float32` or `float64` that is the absolute value of each element in `x`. All
  elements in `x` must be complex numbers of the form \\(a + bj\\). The
  absolute value is computed as \\( \sqrt{a^2 + b^2}\\).  For example:
  ```python
  x = tf.constant([[-2.25 + 4.75j], [-3.25 + 5.75j]])
  tf.abs(x)  # [5.25594902, 6.60492229]
  ```

  Args:
    x: A `Tensor` or `SparseTensor` of type `float32`, `float64`, `int32`,
      `int64`, `complex64` or `complex128`.
    name: A name for the operation (optional).

  Returns:
    A `Tensor` or `SparseTensor` the same size and type as `x` with absolute
      values.
    Note, for `complex64` or `complex128' input, the returned `Tensor` will be
      of type `float32` or `float64`, respectively.
  """
  with ops.name_scope(name, "Abs", [x]) as name:
    if isinstance(x, sparse_tensor.SparseTensor):
      if x.values.dtype in (dtypes.complex64, dtypes.complex128):
        x_abs = gen_math_ops._complex_abs(
            x.values, Tout=x.values.dtype.real_dtype, name=name)
        return sparse_tensor.SparseTensor(
            indices=x.indices, values=x_abs, dense_shape=x.dense_shape)
      x_abs = gen_math_ops._abs(x.values, name=name)
      return sparse_tensor.SparseTensor(
          indices=x.indices, values=x_abs, dense_shape=x.dense_shape)
    else:
      x = ops.convert_to_tensor(x, name="x")
      if x.dtype in (dtypes.complex64, dtypes.complex128):
        return gen_math_ops._complex_abs(x, Tout=x.dtype.real_dtype, name=name)
      return gen_math_ops._abs(x, name=name)


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