我对 TensorFlow 2.0 很陌生。
我为 Cyclic GAN 写了一段代码如下（我提取的代码仅用于构建生成器神经网络）：
def instance_norm(x, epsilon=1e-5):
scale = tf.Variable(initial_value=np.random.normal(1., 0.02, x.shape[-1:]),
trainable=True,
name='SCALE',
dtype=tf.float32)
offset = tf.Variable(initial_value=np.zeros(x.shape[-1:]),
trainable=True,
name='OFFSET',
dtype=tf.float32)
mean, variance = tf.nn.moments(x, axes=[1, 2], keepdims=True)
inv = tf.math.rsqrt(variance + epsilon)
normalized = (x - mean) * inv
return scale * normalized + offset
def build_generator(options, name='Generator'):
initializer = tf.random_normal_initializer(0., 0.02)
inputs = Input(shape=(options.time_step,
options.pitch_range,
options.output_nc))
x = inputs
# (batch * 64 * 84 * 1)
x = layers.Lambda(padding,
name='PADDING_1')(x)
# (batch * …我想知道如何在纸浆、Python 上逐步添加 GLPK 求解器。我已经安装了python（v=3.6.5）、pulp（v=1.6.8）。
我执行时得到的结果如下pulp.pulpTestAll()。
Testing zero subtraction
Testing inconsistant lp solution
Testing continuous LP solution
Testing maximize continuous LP solution
Testing unbounded continuous LP solution
Testing Long Names
Testing repeated Names
Testing zero constraint
Testing zero objective
Testing LpVariable (not LpAffineExpression) objective
Testing Long lines in LP
Testing LpAffineExpression divide
Testing MIP solution
Testing MIP solution with floats in objective
Testing MIP relaxation
Testing feasibility problem (no objective)
Testing an infeasible problem
Testing an integer infeasible problem …