kernel_initializer: Initializer for thekernelweights matrix. bias_initializer: Initializer for the bias vector. kernel_regularizer: Regularizer function applied to thekernelweights matrix. bias_regularizer: Reg
keras.layers.Conv2D(filters, kernel_size, strides=(1, 1), padding='valid', data_format=None, dilation_rate=(1, 1), activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel...
2. tf.layers.conv2d 这是tensorflow 更高一级的api,和keras.layer类似 conv2d(inputs,#输入的张量filters,#卷积过滤器的数量kernel_size,#卷积窗口的大小strides=(1, 1),#卷积步长padding='valid',#可选,默认为 valid,padding 的模式,有 valid 和 same 两种,大小写不区分。data_format='channels_last',#...
(1)tf.nn.conv2d (2)keras.layers.Conv2D 方式1是函数调用方式,方式2是keras layer方式调用。 一、tf.nn.conv2d 函数说明如下: tf.nn.conv2d(input, filters, strides, padding, data_format='NHWC', dilations=None, name=None) 参数说明:输入:input=[b,h,w,c], filters=[h_f,w_f,c,c_out] ...
2. tf.layers.conv2d 这是tensorflow 更高一级的api,和keras.layer类似 conv2d(inputs, filters, kernel_size, strides=(1, 1), padding='valid', data_format='channels_last', dilation_rate=(1, 1), activation=None, use_bias=True, kernel_initializer=None, ...
Conv2D 代码语言:javascript 代码运行次数:0 运行 AI代码解释 keras.layers.Conv2D(filters,kernel_size,strides=(1,1),padding='valid',data_format=None,dilation_rate=(1,1),activation=None,use_bias=True,kernel_initializer='glorot_uniform',bias_initializer='zeros',kernel_regularizer=None,bias_regularizer...
摘自https://tensorflow.google.cn/api_docs/python/tf/keras/layers Classtf.keras.layers.Conv2D 2D convolution layer (e.g. spatial convolution over images). This layer creates a convolutionkernelthat is convolved with the layer input to produce a tensor of outputs. If use_bias is True, a bias...
deftest_kernel_initializer():#Test with a custom kernel initializermodel = tf.keras.Sequential([ tf.keras.layers.Conv2DTranspose(filters=1, kernel_size=3, kernel_initializer='ones', input_shape=(4, 4, 1)) ]) input_data = np.ones((1,4,4,1),dtype=np.float32)output_data = model(in...
对比tf.nn.conv2d与tf.layers.conv2d，tf.layers.conv2d是更高层次的API，简化了参数设置，如默认kernel_initializer为None，激活函数作为参数直接调用，使得编码更为简洁。tf.layers.max_pooling2d与tf.layers.dense同样提供便利性。在tf.layers中，提供了常见函数，如tf.layers.conv2d与tf.layers.max_...
kerasimportlayersfromtensorflow.kerasimportinitializerslayer=layers.Dense(units=64,kernel_initializer=...