lancedb/python/python/lancedb/table.py Lines 1798 to 1822 in 04e1f1e def _execute_query( self, query: Query, batch_size: Optional[int] = None ) -> pa.RecordBatchReader: ds = self.to_lance() nearest = None if len(query.vector) > 0: nearest = { "column": query....
# 需要导入模块: from lucene import IndexSearcher [as 别名]# 或者: from lucene.IndexSearcher importexplain[as 别名]deftestSimple(self):classSimpleSimilarity(PythonSimilarity):deflengthNorm(_self, field, numTerms):return1.0defqueryNorm(_self, sumOfSquaredWeights):return1.0deftf(_self, freq):return...
Python Copy %%writefile score.py import json import numpy as np import pandas as pd import os import pickle from sklearn.externals import joblib from sklearn.linear_model import LogisticRegression from azureml.core.model import Model def init(): global original_model global scoring_model # ret...
示例1: ElasticRetrieval ▲点赞 9▼ # 需要导入模块: from elasticsearch import Elasticsearch [as 别名]# 或者: from elasticsearch.Elasticsearch importexplain[as 别名]#...这里部分代码省略...lucene_query=""fortokeninstructured_query:# TODO proper computing of the boost formula. Different methods?## ...
def f(x): if x == 0: return 0 return x + f(x - 1) print(f(3)) The ‘f(x’ in line 4 is confusing me. Because I’m not to sure if that puts it through the
def __init__(self, radius): self.radius = radius # Method for the calculating area def area(self): return Circle.pi * self.radius ** 2 3. Creating Objects Once we’ve defined a class in Python, we can create objects of that class using the class name followed by parentheses. Creati...
下面是一个实际例子,通过"explain"字段解析一个Python函数的功能: ```python def calculate_square(numbers): """ Calculate the square of each number in the given list. Args: numbers (list): A list of numbers. Returns: list: A list of squares. """ squares = [number ** 2 for number in ...
If num = 8 how would the process go? num = int(input()) def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2) for i in range(num): print(fibonacci(i)) pythonrecursionfibonacciprogrammingsequencefunctional ...
(f)# explain how the input to the 7th layer of the model explains the top two classesdefmap2layer(x,layer):feed_dict=dict(zip([model.layers[0].input], [preprocess_input(x.copy())]))returnK.get_session().run(model.layers[layer].input,feed_dict)e=shap.GradientExplainer( (model....
defexplain_query(self):result=list(self.execute_sql())# Some backends return 1 item tuples with strings, and others return# tuples with integers and strings. Flatten them out into strings.format_=self.query.explain_info.formatoutput_formatter=json.dumpsifformat_andformat_.lower()=="json"else...