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Python math_ops.erfc方法代碼示例

本文整理匯總了Python中tensorflow.python.ops.math_ops.erfc方法的典型用法代碼示例。如果您正苦於以下問題:Python math_ops.erfc方法的具體用法?Python math_ops.erfc怎麽用?Python math_ops.erfc使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在tensorflow.python.ops.math_ops的用法示例。


在下文中一共展示了math_ops.erfc方法的5個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: ndtr

# 需要導入模塊: from tensorflow.python.ops import math_ops [as 別名]
# 或者: from tensorflow.python.ops.math_ops import erfc [as 別名]
def ndtr(x, name="ndtr"):
  """Normal distribution function.

  Returns the area under the Gaussian probability density function, integrated
  from minus infinity to x:

  ```
                    1       / x
     ndtr(x)  = ----------  |    exp(-0.5 t**2) dt
                sqrt(2 pi)  /-inf

              = 0.5 (1 + erf(x / sqrt(2)))
              = 0.5 erfc(x / sqrt(2))
  ```

  Args:
    x: `Tensor` of type `float32`, `float64`.
    name: Python string. A name for the operation (default="ndtr").

  Returns:
    ndtr: `Tensor` with `dtype=x.dtype`.

  Raises:
    TypeError: if `x` is not floating-type.
  """

  with ops.name_scope(name, values=[x]):
    x = ops.convert_to_tensor(x, name="x")
    if x.dtype.as_numpy_dtype not in [np.float32, np.float64]:
      raise TypeError(
          "x.dtype=%s is not handled, see docstring for supported types."
          % x.dtype)
    return _ndtr(x) 
開發者ID:ryfeus,項目名稱:lambda-packs,代碼行數:35,代碼來源:special_math.py

示例2: _ndtr

# 需要導入模塊: from tensorflow.python.ops import math_ops [as 別名]
# 或者: from tensorflow.python.ops.math_ops import erfc [as 別名]
def _ndtr(x):
  """Implements ndtr core logic."""
  half_sqrt_2 = constant_op.constant(
      0.5 * math.sqrt(2.), dtype=x.dtype, name="half_sqrt_2")
  w = x * half_sqrt_2
  z = math_ops.abs(w)
  y = array_ops.where(math_ops.less(z, half_sqrt_2),
                      1. + math_ops.erf(w),
                      array_ops.where(math_ops.greater(w, 0.),
                                      2. - math_ops.erfc(z),
                                      math_ops.erfc(z)))
  return 0.5 * y 
開發者ID:ryfeus,項目名稱:lambda-packs,代碼行數:14,代碼來源:special_math.py

示例3: setUp

# 需要導入模塊: from tensorflow.python.ops import math_ops [as 別名]
# 或者: from tensorflow.python.ops.math_ops import erfc [as 別名]
def setUp(self):
    super(CoreUnaryOpsTest, self).setUp()

    self.ops = [
        ('abs', operator.abs, math_ops.abs, core.abs_function),
        ('neg', operator.neg, math_ops.negative, core.neg),
        # TODO(shoyer): add unary + to core TensorFlow
        ('pos', None, None, None),
        ('sign', None, math_ops.sign, core.sign),
        ('reciprocal', None, math_ops.reciprocal, core.reciprocal),
        ('square', None, math_ops.square, core.square),
        ('round', None, math_ops.round, core.round_function),
        ('sqrt', None, math_ops.sqrt, core.sqrt),
        ('rsqrt', None, math_ops.rsqrt, core.rsqrt),
        ('log', None, math_ops.log, core.log),
        ('exp', None, math_ops.exp, core.exp),
        ('log', None, math_ops.log, core.log),
        ('ceil', None, math_ops.ceil, core.ceil),
        ('floor', None, math_ops.floor, core.floor),
        ('cos', None, math_ops.cos, core.cos),
        ('sin', None, math_ops.sin, core.sin),
        ('tan', None, math_ops.tan, core.tan),
        ('acos', None, math_ops.acos, core.acos),
        ('asin', None, math_ops.asin, core.asin),
        ('atan', None, math_ops.atan, core.atan),
        ('lgamma', None, math_ops.lgamma, core.lgamma),
        ('digamma', None, math_ops.digamma, core.digamma),
        ('erf', None, math_ops.erf, core.erf),
        ('erfc', None, math_ops.erfc, core.erfc),
        ('lgamma', None, math_ops.lgamma, core.lgamma),
    ]
    total_size = np.prod([v.size for v in self.original_lt.axes.values()])
    self.test_lt = core.LabeledTensor(
        math_ops.cast(self.original_lt, dtypes.float32) / total_size,
        self.original_lt.axes) 
開發者ID:abhisuri97,項目名稱:auto-alt-text-lambda-api,代碼行數:37,代碼來源:core_test.py

示例4: ndtr

# 需要導入模塊: from tensorflow.python.ops import math_ops [as 別名]
# 或者: from tensorflow.python.ops.math_ops import erfc [as 別名]
def ndtr(x, name="ndtr"):
  """Normal distribution function.

  Returns the area under the Gaussian probability density function, integrated
  from minus infinity to x:

  ```
                    1       / x
     ndtr(x)  = ----------  |    exp(-0.5 t^2) dt
                sqrt(2 pi)  /-inf

              = 0.5 (1 + erf(x / sqrt(2)))
              = 0.5 erfc(x / sqrt(2))
  ```

  Args:
    x: `Tensor` of type `float32`, `float64`.
    name: Python string. A name for the operation (default="ndtr").

  Returns:
    ndtr: `Tensor` with `dtype=x.dtype`.

  Raises:
    TypeError: if `x` is not floating-type.
  """

  with ops.name_scope(name, values=[x]):
    x = ops.convert_to_tensor(x, name="x")
    if x.dtype.as_numpy_dtype not in [np.float32, np.float64]:
      raise TypeError(
          "x.dtype=%s is not handled, see docstring for supported types."
          % x.dtype)
    return _ndtr(x) 
開發者ID:abhisuri97,項目名稱:auto-alt-text-lambda-api,代碼行數:35,代碼來源:special_math.py

示例5: _ndtr

# 需要導入模塊: from tensorflow.python.ops import math_ops [as 別名]
# 或者: from tensorflow.python.ops.math_ops import erfc [as 別名]
def _ndtr(x):
  """Implements ndtr core logic."""
  half_sqrt_2 = constant_op.constant(
      0.5 * math.sqrt(2.), dtype=x.dtype, name="half_sqrt_2")
  w = x * half_sqrt_2
  z = math_ops.abs(w)
  y = math_ops.select(math_ops.less(z, half_sqrt_2),
                      1. + math_ops.erf(w),
                      math_ops.select(math_ops.greater(w, 0.),
                                      2. - math_ops.erfc(z),
                                      math_ops.erfc(z)))
  return 0.5 * y 
開發者ID:tobegit3hub,項目名稱:deep_image_model,代碼行數:14,代碼來源:special_math.py


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