Question

我创建了一个前馈神经网络，但是尽管更改了参数的数据类型，但它仍给出类型错误。我对keras和机器学习真的很陌生，因此，我希望能提供详细的帮助。我在下面附上代码片段和错误日志。代码-

    num_of_features = X_train.shape[1]

    nb_classes = Y_train.shape[1]
    def baseline_model():
    def branch2(x):

    x = Dense(np.floor(num_of_features*50), activation='sigmoid')(x)
    x = Dropout(0.75)(x)

    x = Dense(np.floor(num_of_features*20), activation='sigmoid')(x)
    x = Dropout(0.5)(x)

    x = Dense(np.floor(num_of_features), activation='sigmoid')(x)
    x = Dropout(0.1)(x)
    return x

    main_input = Input(shape=(num_of_features,), name='main_input')

    x = main_input
    x = branch2(x)
    main_output = Dense(nb_classes, activation='softmax')(x)
    model = Model(input=main_input, output=main_output)
    model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy', 'categorical_crossentropy'])
    return model

    model = baseline_model()

错误-

Traceback (most recent call last):
File "h2_fit_neural.py", line 143, in <module>
model = baseline_model()
File "h2_fit_neural.py", line 137, in baseline_model
x = branch2(x)
File "h2_fit_neural.py", line 124, in branch2
x = Dense(np.floor(num_of_features*50), activation='sigmoid')(x)
File "/home/shashank/tensorflow/lib/python3.6/site-packages/keras/engine/base_layer.py", line 432, in __call__
self.build(input_shapes[0])
File "/home/shashank/tensorflow/lib/python3.6/site-packages/keras/layers/core.py", line 872, in build
constraint=self.kernel_constraint)
File "/home/shashank/tensorflow/lib/python3.6/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/shashank/tensorflow/lib/python3.6/site-packages/keras/engine/base_layer.py", line 249, in add_weight
weight = K.variable(initializer(shape),
File "/home/shashank/tensorflow/lib/python3.6/site-packages/keras/initializers.py", line 218, in __call__
dtype=dtype, seed=self.seed)
File "/home/shashank/tensorflow/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 4077, in random_uniform
dtype=dtype, seed=seed)
File "/home/shashank/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/random_ops.py", line 242, in random_uniform
rnd = gen_random_ops.random_uniform(shape, dtype, seed=seed1, seed2=seed2)
File "/home/shashank/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/gen_random_ops.py", line 674, in random_uniform
name=name)
File "/home/shashank/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 609, in _apply_op_helper
param_name=input_name)
File "/home/shashank/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 60, in _SatisfiesTypeConstraint
", ".join(dtypes.as_dtype(x).name for x in allowed_list)))
TypeError: Value passed to parameter 'shape' has DataType float32 not in list of allowed values: int32, int64

Answer 1

为什么在密集层中使用np.floor作为形状？这将产生一个浮点数，您需要在那里一个整数。删除np.floor应该可以解决您的问题。

形状属性中的神经网络密集层错误

1 个答案: