我正在使用 tf.GradientTape() 使用 TensorFlow 2.0 训练模型，但我发现模型的准确性为95%如果我使用tf.keras.losses.BinaryCrossentropy，但75%如果我使用 则降级为tf.keras.losses.binary_crossentropy。所以我对这里相同指标的差异感到困惑？
import pandas as pd
import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
from sklearn.model_selection import train_test_split
def read_data():
red_wine = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv", sep=";")
white_wine = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv", sep=";")
red_wine["type"] = 1
white_wine["type"] = 0
wines = red_wine.append(white_wine)
return wines
def get_x_y(df):
x = df.iloc[:, :-1].values.astype(np.float32)
y = df.iloc[:, -1].values.astype(np.int32)
return x, y
def build_model():
inputs = layers.Input(shape=(12,))
dense1 = layers.Dense(12, activation="relu", name="dense1")(inputs)
dense2 …