import tensorflow as tf def data_generator(): dataset = np.array(range(5)) for d in dataset: #print(d) yield d dataset = tf.data.Dataset.from_generator(data_generator, (tf.int32), (tf.TensorShape([]))) dataset = dataset.repeat(3) #3==epoch dataset = dataset.batch(4) #4==bat...
def gen(): for i in itertools.count(1): yield (i, [1] * i) ds = tf.data.Dataset.from_generator( gen, (tf.int64, tf.int64), (tf.TensorShape([]), tf.TensorShape([None]))) for value in ds.take(2): print value # (1, array([1])) # (2, array([1, 1])) 生产函数ge...
tf.data.Dataset generator 并行 对generator()中的复杂逻辑,我们对其进行简化,即仅在生成器中做一些下标取值的类型操作,将generator()中处理部分使用py_function包裹(wrapped) ,然后调用map处理。 deffunc(i):i=i.numpy()# Decoding from the EagerTensor objectx,y=your_processing_function(training_set[i])ret...
dataset = tf.data.Dataset.from_generator(make_generator, tf.string, tf.TensorShape([None,None,No...
batch_size= 2data=tf.data.Dataset.from_generator( gen, #指定通过gen构建Dataset (tf.float32, tf.int32), #指定数据类型 (tf.TensorShape([224, 224, 3]),tf.TensorShape([]))) #指定shape data=data.batch(batch_size) #设置batchsize
从我的问题来说，我的yield返回的是tensor类型，而接收端需要的是ndarry类型，所以才会提示“could not ...
创建Dataset由其生成元素的元素generator。 函数形式:from_generator(generator,output_types,output_shapes=None,args=None) 参数generator:一个可调用对象,它返回支持该iter()协议的对象 。如果args未指定,generator则不得参数; 否则它必须采取与有值一样多的参数args。
According to the docs, tf.data.Dataset has a static method called from_generator(), constructing a dataset from a given iterable. I performed the following actions: 1) downloaded a text file from a link 2) parsed the file using a TextLineDataset (called raw_lines), then limited the size...
As best as I can tell, it is the internals of thetf.data.Dataset.from_generator()call that is trying to directly usetf.dtypes.as_dtype()in parsing itsoutput_signatureargument, when that argument is a dictionary that contains a(key, value)pair with a value that istf.RaggedTensorSpec(tf...
from_generator(), 由于迭代器的特性,这是一种最节省内存的办法来创建dataset。当你要生成一个非常大的数据集的时候,这是个非常有效的方法。因为它是逐渐从硬盘读取数据并映射到内存。 fromdatasetsimportDatasetdefgen():yield{"pokemon":"bulbasaur","type":"grass"}yield{"pokemon":"squirtle","type":"water"...