"Adagrad": train.AdagradOptimizer,
"Adam": train.AdamOptimizer,
"Ftrl": train.FtrlOptimizer,
- "Momentum": lambda lr: train.MomentumOptimizer(lr, momentum=0.9),
+ "Momentum": lambda learning_rate: train.MomentumOptimizer(learning_rate, momentum=0.9), # pylint: disable=line-too-long
"RMSProp": train.RMSPropOptimizer,
"SGD": train.GradientDescentOptimizer,
}
optimizers = [
"SGD", gradient_descent.GradientDescentOptimizer,
gradient_descent.GradientDescentOptimizer(learning_rate=0.1),
- lambda lr: gradient_descent.GradientDescentOptimizer(learning_rate=lr)
+ lambda lr: gradient_descent.GradientDescentOptimizer(learning_rate=lr),
+ "Momentum"
]
for optimizer in optimizers:
with ops.Graph().as_default() as g: