tf.keras.layers.Conv2D( filters, kernel_size, strides=(1, 1), padding='valid', data_format=None, dilation_rate=(1, 1), groups=1, activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, **kwargs)
tf.raw_ops.Conv2D(
input, filter, strides, padding, use_cudnn_on_gpu=True, explicit_paddings=[],
data_format='NHWC', dilations=[1, 1, 1, 1], name=None
)