B )`B@sdZddlmZddlmZddlmZddlmZddlmZddlmZddl m Z dd l m Z dd l m Z dd lmZdd lmZed Gddde jZdS)zBuilt-in linear model classes.)absolute_import)division)print_function) activations) initializers) regularizers) base_layer)training)core)nn) keras_exportzkeras.experimental.LinearModelcsHeZdZdZdfdd Zdd Zd d Zd d ZedddZ Z S) LinearModelaLinear Model for regression and classification problems. This model approximates the following function: $$y = \beta + \sum_{i=1}^{N} w_{i} * x_{i}$$ where $$\beta$$ is the bias and $$w_{i}$$ is the weight for each feature. Example: ```python model = LinearModel() model.compile(optimizer='sgd', loss='mse') model.fit(x, y, epochs=epochs) ``` This model accepts sparse float inputs as well: Example: ```python model = LinearModel() opt = tf.keras.optimizers.Adam() loss_fn = tf.keras.losses.MeanSquaredError() with tf.GradientTape() as tape: output = model(sparse_input) loss = tf.reduce_mean(loss_fn(target, output)) grads = tape.gradient(loss, model.weights) opt.apply_gradients(zip(grads, model.weights)) ``` NTzerosc  sp||_t||_||_t||_t||_t||_ t||_ t t |j f|tjdddS)aCreate a Linear Model. Args: units: Positive integer, output dimension without the batch size. activation: Activation function to use. If you don't specify anything, no activation is applied. use_bias: whether to calculate the bias/intercept for this model. If set to False, no bias/intercept will be used in calculations, e.g., the data is already centered. kernel_initializer: Initializer for the `kernel` weights matrices. bias_initializer: Initializer for the bias vector. kernel_regularizer: regularizer for kernel vectors. bias_regularizer: regularizer for bias vector. **kwargs: The keyword arguments that are passed on to BaseLayer.__init__. ZLinearTN)unitsrget activationuse_biasrkernel_initializerbias_initializerrkernel_regularizerbias_regularizersuperr __init__rZ_keras_model_gaugeZget_cellset) selfrrrrrrrkwargs) __class__U/home/dcms/DCMS/lib/python3.7/site-packages/tensorflow/python/keras/premade/linear.pyr?s     zLinearModel.__init__cCsg|_t|ttfrJxZ|D]*}tj|jd|j|j|d}|j |qWn&tj|jd|j|j|d}|j ||j r|j d|j|j |j |jdd|_nd|_dS)NF)rrrr input_shapebiasT)shapeZ initializerZ regularizerdtypeZ trainable) dense_layers isinstancetuplelistr ZDenserrrappendrZ add_weightrrr#r!)rr r"layerrrrbuildbs4   zLinearModel.buildcCst|ttfs|g}t|t|jkr@tdt|jt|d}x6t||jD]&\}}||}|dkrp|}qR||7}qRW|jrt ||j }|j dk r| |S|S)Nz%Expected {} inputs, but got {} inputs) r%r&r'lenr$ ValueErrorformatziprr Zbias_addr!r)rinputsresultinpr)outputrrrcalls    zLinearModel.callc Csh|jt|j|jt|jt|jt|j t|j d}t j |}tt|t|S)N)rrrrrrr)rr serializerrrrrrrrrZLayer get_configdictr'items)rconfigZ base_configrrrr5s     zLinearModel.get_configcCs ~|f|S)Nr)clsr8Zcustom_objectsrrr from_configszLinearModel.from_config)rNTrrNN)N) __name__ __module__ __qualname____doc__rr*r3r5 classmethodr: __classcell__rr)rrr s r N)r> __future__rrrZtensorflow.python.kerasrrrZtensorflow.python.keras.enginerr Ztensorflow.python.keras.layersr Ztensorflow.python.opsr Z tensorflow.python.util.tf_exportr ZModelr rrrrs