""" # 调用内部方法 _log_prob 来计算给定单词序列在 N-gram 语言模型下的总对数概率 return self._log_prob(words, N) # 计算 ngram 的平滑对数概率并返回 def _log_ngram_prob(self, ngram): """Return the smoothed log probability of the ngram""" N = len(ngram) sc, T = self._smooth...
The only difference between these functions is that ``array_split`` allows `indices_or_sections` to be an integer that does *not* equally divide the axis. For an array of length l that should be split into n sections, it returns l % n sub-arrays of size l//n + 1 and the rest ...
dv["wrappers"] = [self._wrapper_derived_variables]returndv@propertydefgradients(self):"""A dictionary of the current layer parameter gradients."""# 返回当前层参数梯度的字典returnself._base_layer.gradients@propertydefact_fn(self):"""The activation function for the base layer."""# 返回基础层的...
allclose(a, b[, rtol, atol, equal_nan])Returns True if two arrays are element-wise equal within a tolerance.isclose(a, b[, rtol, atol, equal_nan])Returns a boolean array where two arrays are element-wise equal within a tolerance.array_equal(a1, a2)True if two arrays have the same...
Let us also compare the time it takes for the two methods to shuffle the same array. We will run the two methods on the same array and log the time it takes for them to shuffle it. We will log times for arrays of lengths ranging from 102to 109, with increments of orders of 10. ...
Set difference between two arrays: [ 0 20 60 80]Click me to see the sample solution21. Set Exclusive-Or of ArraysWrite a NumPy program to find the set exclusive-or of two arrays. Set exclusive-or will return sorted, distinct values in only one (not both) of the input arrays....
With np.linspace() and np.arange() you can make arrays of evenly spaced values. The difference between these two functions is that the last value of the three that are passed in the code chunk above designates either the step value for np.linspace() or a number of samples for np.arange...
Let's compare the time it takes to perform a vectorized operation with that of an equivalent loop-based operation. Python for loop importtime start = time.time() array1 = [1,2,3,4,5]foriinrange(len(array1)): array1[i] +=10end = time.time()print("For loop time:", end - sta...
return np.max(prices - cummin(prices)) >>> profit_with_numpy(prices) 44.2487532293278 >>> np.allclose(profit_with_numpy(prices), profit(prices)) True How do these two operations, which have the same theoretical time complexity, compare in actual runtime? First, let’s take a longer sequen...
@cython.exceptval(value=None,*,check=False)specifies the function’s exception return value and exception check semantics as follows:@cython.exceptval(value=None,*,check=False)指定了函数的异常返回值和异常检查语义如下: Python annotations can be used to declare argument types, as shown in the foll...