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132 def sqrt(x: T.Tensor) -> T.Tensor: 133 """ 134 Elementwise square root of a tensor. 135 136 Args: 137 x (non-negative): A tensor. 138 139 Returns: 140 tensor(non-negative): Elementwise square root. 141 142 """ 143 return ne.evaluate('sqrt(x)')
387 def sqrt(a): 388 """Calculate the sqrt of input. 389 390 Parameters 391 ---------- 392 a : Tensor 393 The input tensor. 394 395 Returns 396 ------- 397 Tensor 398 The sqrt result. 399 400 """ 401 return _ops.Sqrt(a)
86 def sqrt(x): 87 return T.sqrt(x)
1054 def sqrt(real): 1055 """ 1056 Vector Square Root 1057 """ 1058 1059 return lib.sqrt([real], [])
188 def sqrt(x, name=None): 189 190 """ 191 Computes square root of x element-wise. 192 193 I.e., \\(y = \sqrt{x} = x^{1/2}\\). 194 195 Args: 196 x: A `Tensor`. 197 name: A name for the operation (optional). 198 199 Returns: 200 A `Tensor`. Has the same type as `x`. 201 202 """ 203 204 return ops.Pow(x, power=0.5, name=name)
26 def libmath(n): 27 n = float(n) 28 return math.sqrt(n)
84 @native(name="Sqrt", ret=pfp.fields.Double) 85 def Sqrt(params, ctxt, scope, stream, coord): 86 raise NotImplementedError()
153 def sqrt(x): 154 """ 155 Element-wise square root. 156 :param x: A variable. 157 :return: A variable. 158 """ 159 return Variable.from_jvalue(callZooFunc("float", "sqrt", x))
17 def sqrt(x): 18 def average(a, b): 19 return (a + b) / 2.0 20 21 def is_good_enough(guess): 22 return (abs((guess * guess) - x) < 0.001) 23 24 def improve(guess): 25 return average(guess, x / guess) 26 27 def sqrt_iter(guess): 28 if is_good_enough(guess): 29 return guess 30 else: 31 return sqrt_iter(improve(guess)) 32 33 return sqrt_iter(1.0)
142 def Sqrt(self): 143 return unary(self, 'sqrt(' + str(self._name_no_id()) + ')', (lambda x: math.sqrt(self.value())))