Question

我的问题与here相同，但是无法使其解决方案有效。

每次运行：

import tensorflow as tf

import tensorflow_datasets as tfds


class ExampleAugmentation:
    def __init__(self, logdir: str, max_images: int, name: str):
        self.file_writer = tf.summary.create_file_writer(logdir)
        self.max_images: int = max_images
        self.name: str = name
        self._counter: int = 0

    def __call__(self, image, label):
        augmented_image = tf.image.random_flip_left_right(
            tf.image.random_flip_up_down(image)
        )
        with self.file_writer.as_default():
            tf.summary.image(
                self.name,
                augmented_image,
                step=self._counter,
                max_outputs=self.max_images,
            )

        self._counter += 1
        return augmented_image, label


# Global settings

BATCH_SIZE = 32
DATASET_SIZE = 60000
EPOCHS = 5

LOG_DIR = "/logs/images"
AUGMENTATION = ExampleAugmentation(LOG_DIR, max_images=4, name="Images")

# Dataset

dataset = tfds.load("mnist", as_supervised=True, split=tfds.Split.TRAIN)

dataset = (
    dataset.map(
        lambda image, label: (
            tf.image.convert_image_dtype(image, dtype=tf.float32),
            label,
        )
    )
    .batch(BATCH_SIZE)
    .map(AUGMENTATION)
    .repeat(EPOCHS)
)

# Model and training

model = tf.keras.models.Sequential(
    [
        tf.keras.layers.Flatten(input_shape=(28, 28, 1)),
        tf.keras.layers.Dense(128, activation="relu"),
        tf.keras.layers.Dropout(0.2),
        tf.keras.layers.Dense(10, activation="softmax"),
    ]
)

model.compile(
    optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"]
)
model.fit(
    dataset,
    epochs=EPOCHS,
    steps_per_epoch=DATASET_SIZE // BATCH_SIZE,
    callbacks=[tf.keras.callbacks.TensorBoard(log_dir=LOG_DIR)],
)

我得到：

线程1：致命错误：在隐式展开一个可选值时意外发现nil

CustomCell：

    func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
    let cell = commentTableViewCell()

    print("called T")
    if arrayOfComments.count != 0 {
        do {
            let url = URL(string: (arrayOfComments[indexPath.row].user.profileImageUrlString)!)
            let imageData = try Data(contentsOf: url!)
            let image = UIImage(data: imageData)

            cell.dateOfComment.text = "testText"//crash here
        } catch {
            print(error, ": Failed in do block converting image")
        }
    }

    return cell
}

Answer 1

设置您的单元格的标识符并替换

var myOutput = "is a string.";

使用

let cell = commentTableViewCell() // this loads the cell class without attached IB outlets

也是这个

let cell = tableView.dequeueReusableCell(withIdentifier:"cellId", for: indexPath) as! commentTableViewCell

使用SDWebImage

阻止主线程

对于let imageData = try Data(contentsOf: url!)中的Xib单元格

viewDidLoad

你必须有

commentTableViewCell.swift

commentTableViewCell.xib

对于原型单元格

只需在没有注册的情况下设置标识符，因为在这种情况下会自动完成

CustomTableViewCell产量没有？

1 个答案: