Tensorflow 2.3: AttributeError: 'Tensor' 对象没有属性 'numpy'

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问题描述

限时送ChatGPT账号..

我想加载从这里借来的文本文件，其中每一行代表一个json 字符串如下:

I wanted to load the text file borrowed from here, where each line represent a json string like following:

{"overall": 2.0, "verified": true, "reviewTime": "02 4, 2014", "reviewerID": "A1M117A53LEI8", "asin": "7508492919", "reviewerName": "Sharon Williams", "reviewText": "DON'T CARE FOR IT.  GAVE IT AS A GIFT AND THEY WERE OKAY WITH IT.  JUST NOT WHAT I EXPECTED.", "summary": "CASE", "unixReviewTime": 1391472000}

我想使用 tensorflow 从数据集中仅提取 reviewText 和 overall 特征，但面临以下错误.

I would like to extract only reviewText and overall feature from the dataset using tensorflow but facing following error.

AttributeError: in user code:

    <ipython-input-4-419019a35c5e>:9 None  *
        line_dataset = line_dataset.map(lambda row: transform(row))
    <ipython-input-4-419019a35c5e>:2 transform  *
        str_example = example.numpy().decode("utf-8")

    AttributeError: 'Tensor' object has no attribute 'numpy'

我的代码片段如下所示:

My code snippet looks like following:

def transform(example):
    str_example = example.numpy().decode("utf-8")
    json_example = json.loads(str_example)
    overall = json_example.get('overall', None)
    text = json_example.get('reviewText', None)
    return (overall, text)

line_dataset = tf.data.TextLineDataset(filenames = [file_path])
line_dataset = line_dataset.map(lambda row: transform(row))
for example in line_dataset.take(5):
    print(example)

我使用的是 tensorflow 2.3.0.

I am using tensorflow 2.3.0.

推荐答案

数据集的输入管道总是被追踪到一个图形中(就像你使用了 @tf.function) 以使其更快，这意味着您不能使用 .numpy().但是，您可以使用 tf.numpy_function 来访问数据作为图中的 NumPy 数组:

The input pipeline of a dataset is always traced into a graph (as if you used @tf.function) to make it faster, which means, among other things, that you cannot use .numpy(). You can however use tf.numpy_function to access the data as a NumPy array within the graph:

def transform(example):
    # example will now by a NumPy array
    str_example = example.decode("utf-8")
    json_example = json.loads(str_example)
    overall = json_example.get('overall', None)
    text = json_example.get('reviewText', None)
    return (overall, text)

line_dataset = tf.data.TextLineDataset(filenames = [file_path])
line_dataset = line_dataset.map(
    lambda row: tf.numpy_function(transform, row, (tf.float32, tf.string)))
for example in line_dataset.take(5):
    print(example)

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