# 支持功能

## Keras 模型导入: 支持的功能

鲜为人知的事实：DL4J的创始人，Skymind，在我们的团队中拥有前五名的Keras贡献者中的两个，使其成为继Keras的创始人Francois Chollet之后对Keras的最大贡献者。 虽然并非DL4J中的每个概念在Keras中都有等效的概念，反之亦然，但是许多关键概念可以匹配。将Keras模型导入DL4J是在我们的[deeplearning4j-modelimport](https://github.com/deeplearning4j/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras) 模块中完成的。下面是当前支持的特性的综合列表。

* 层 
* 损失
* 激活函数
* 初始化器
* 正则化器 
* 约束
* 度量
* 优化器

### 层

将模型映射到DL4J层是在模型导入的层子模块中完成的。该项目的结构随意地反映了Keras的结构。

#### 核心层

* ✅ [Dense](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasDense.java)
* ✅ [Activation](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasActivation.java)
* ✅ [Dropout](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasDropout.java)
* ✅ [Flatten](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasFlatten.java)
* ✅ [Reshape](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasReshape.java)
* ✅ [Merge](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasMerge.java)
* ✅ [Permute](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasPermute.java)
* ✅ [RepeatVector](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasRepeatVector.java)
* ✅ [Lambda](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasLambda.java)
* ❌ ActivityRegularization
* ✅ [Masking](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasMasking.java)
* ✅ [SpatialDropout1D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasSpatialDropout.java)
* ✅ [SpatialDropout2D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasSpatialDropout.java)
* ✅ [SpatialDropout3D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/core/KerasSpatialDropout.java)

#### 卷积层

* ✅ [Conv1D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasConvolution1D.java)
* ✅ [Conv2D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasConvolution2D.java)
* ✅ [Conv3D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasConvolution3D.java)
* ✅ [AtrousConvolution1D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasAtrousConvolution1D.java)
* ✅ [AtrousConvolution2D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasAtrousConvolution1D.java)
* ❌ SeparableConv1D
* ✅ [SeparableConv2D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasSeparableConvolution2D.java)
* ✅ [Conv2DTranspose](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasDeconvolution2D.java)
* ❌ Conv3DTranspose
* ✅ [Cropping1D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasCropping1D.java)
* ✅ [Cropping2D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasCropping2D.java)
* ✅ [Cropping3D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasCropping3D.java)
* ✅ [UpSampling1D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasUpsampling1D.java)
* ✅ [UpSampling2D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasUpsampling2D.java)
* ✅ [UpSampling3D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasUpsampling2D.java)
* ✅ [ZeroPadding1D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasZeroPadding1D.java)
* ✅ [ZeroPadding2D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasZeroPadding2D.java)
* ✅ [ZeroPadding3D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/convolutional/KerasZeroPadding3D.java)

#### 池化层

* ✅ [MaxPooling1D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasPooling1D.java)
* ✅ [MaxPooling2D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasPooling2D.java)
* ✅ [MaxPooling3D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasPooling3D.java)
* ✅ [AveragePooling1D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasPooling1D.java)
* ✅ [AveragePooling2D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasPooling2D.java)
* ✅ [AveragePooling3D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasPooling3D.java)
* ✅ [GlobalMaxPooling1D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasGlobalPooling.java)
* ✅ [GlobalMaxPooling2D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasGlobalPooling.java)
* ✅ [GlobalMaxPooling3D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasGlobalPooling.java)
* ✅ [GlobalAveragePooling1D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasGlobalPooling.java)
* ✅ [GlobalAveragePooling2D](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasGlobalPooling.java)
* ✅ [GlobalAveragePooling](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/pooling/KerasGlobalPooling.java)

#### 本地连接层

* ✅ [LocallyConnected1D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/local/KerasLocallyConnected1D.java)
* ✅ [LocallyConnected2D](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/local/KerasLocallyConnected2D.java)

#### 循环层

* ✅ [SimpleRNN](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/recurrent/KerasSimpleRnn.java)
* ❌ GRU
* ✅ [LSTM](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/recurrent/KerasLSTM.java)
* ❌ ConvLSTM2D

#### 嵌入层

* ✅ [Embedding](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/embeddings/KerasEmbedding.java)

#### 合并层

* ✅ Add / add
* ✅ Multiply / multiply
* ✅ Subtract / subtract
* ✅ Average / average
* ✅ Maximum / maximum
* ✅ Concatenate / concatenate
* ❌ Dot / dot

#### 高级激活层

* ✅ [LeakyReLU](https://github.com/eclipse/deeplearning4j/tree/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/advanced/activations/KerasLeakyReLU.java)
* ✅ [PReLU](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/advanced/activations/KerasPReLU.java)
* ✅ ELU
* ✅ [ThresholdedReLU](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/advanced/activations/KerasThresholdedReLU.java)

#### 归一化层

* ✅ [BatchNormalization](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/normalization/KerasBatchNormalization.java)

## 噪声层

* ✅ [GaussianNoise](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/noise/KerasGaussianNoise.java)
* ✅ [GaussianDropout](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/noise/KerasGaussianDropout.java)
* ✅ [AlphaDropout](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/noise/KerasAlphaDropout.java)

### 层包装器

* ❌ TimeDistributed
* ✅ [Bidirectional](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/wrappers/KerasBidirectional.java)

## 失损

* ✅ mean\_squared\_error
* ✅ mean\_absolute\_error
* ✅ mean\_absolute\_percentage\_error
* ✅ mean\_squared\_logarithmic\_error
* ✅ squared\_hinge
* ✅ hinge
* ✅ categorical\_hinge
* ❌ logcosh
* ✅ categorical\_crossentropy
* ✅ sparse\_categorical\_crossentropy
* ✅ binary\_crossentropy
* ✅ kullback\_leibler\_divergence
* ✅ poisson
* ✅ cosine\_proximity

## 活激

* ✅ softmax
* ✅ elu
* ✅ selu
* ✅ softplus
* ✅ softsign
* ✅ relu
* ✅ tanh
* ✅ sigmoid
* ✅ hard\_sigmoid
* ✅ linear

## 初始化器

* ✅ Zeros
* ✅ Ones
* ✅ Constant
* ✅ RandomNormal
* ✅ RandomUniform
* ✅ TruncatedNormal
* ✅ VarianceScaling
* ✅ Orthogonal
* ✅ Identity
* ✅ lecun\_uniform
* ✅ lecun\_normal
* ✅ glorot\_normal
* ✅ glorot\_uniform
* ✅ he\_normal
* ✅ he\_uniform

## 正则化器

* ✅ l1
* ✅ l2
* ✅ l1\_l2

## 约束

* ✅ max\_norm
* ✅ non\_neg
* ✅ unit\_norm
* ✅ min\_max\_norm

## 优化器

* ✅ SGD
* ✅ RMSprop
* ✅ Adagrad
* ✅ Adadelta
* ✅ Adam
* ✅ Adamax
* ✅ Nadam
* ❌ TFOptimizer


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://deeplearning4j.konduit.ai/zhong-wen-v1.0.0/keras-dao-ru/zhi-chi-gong-neng.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.