Error in exporting Texture 1. Error running callback: Traceback (most recent call last): File "labs::Driver/flipbook_textures::1.0/export_all", line 1, in <module> File "labs::Driver/flipbook_textures::1.0, PythonModule", line 1320, in exportAll File "labs::Driver/flipbook_textures::1.0, PythonModule", line 1311, in exportAll File "labs::Driver/flipbook_textures::1.0, PythonModule", line 1301, in exportTexture File "labs::Driver/flipbook_textures::1.0, PythonModule", line 1294, in exportTexture File "C:\PROGRA~1/SIDEEF~1/HOUDIN~1.303/houdini/python3.9libs\houpythonportion\ui.py", line 1112, in decorator return func(*args, **kwargs) File "C:\PROGRA~1/SIDEEF~1/HOUDIN~1.303/houdini/python3.9libs\hou.py", line 74137, in render return _hou.RopNode_render(self, *args, **kwargs) hou.OperationFailed: The attempted operation failed. Error: Cook error in input: OUT_TEX1.

这个错误信息表明在导出纹理时出现了烹饪错误。这通常意味着无法处理某个输入参数或节点之间存在某些问题。以下是一些可能的原因：

1. 输入参数错误。请确保节点的输入参数正确设置，如输入文件路径、纹理名称等。

2. 纹理文件损坏。请检查你正在尝试导出的纹理文件，确保它没有损坏或无效。

3. 节点设置错误。请确保节点的设置正确，如文件格式、文件命名规则等。

4. 输出目录无效。请确保节点的输出目录存在并且有写入权限。

5. 节点之间存在问题。请确保节点之间的连接正确，并且没有缺失或错误的连接。

如果你仍然无法解决问题，请检查 Houdini 的日志文件，以便查找更多有关导出失败的错误信息。另外，尝试以不同的方式导出纹理，以查看是否存在特定于某种方法的问题。

相关问题

ProxyError: Conda cannot proceed due to an error in your proxy configuration.

When you encounter a "ProxyError: Conda cannot proceed due to an error in your proxy configuration" message, it means that there is an issue with the proxy settings in your Conda configuration. Conda uses the proxy settings to connect to the internet and download packages. To resolve this issue, you can try the following steps:

1. Check your proxy settings: Verify that the proxy settings in your Conda configuration are correct. You can do this by running the following command in your terminal:

   conda config --show | grep proxy

Make sure that the proxy settings displayed are accurate and match your network configuration.

2. Update proxy settings: If you need to update your proxy settings, you can use the following commands to set the proxy configuration for Conda:

   conda config --set proxy_servers.http <proxy_url>
   conda config --set proxy_servers.https <proxy_url>

Replace `<proxy_url>` with the URL of your proxy server.

3. Remove proxy settings: If you don't require a proxy or want to remove the existing proxy settings, you can use the following commands:

   conda config --remove-key proxy_servers.http
   conda config --remove-key proxy_servers.https

4. Set environment variables: In some cases, you may need to set environment variables for your proxy configuration. You can do this by exporting the `HTTP_PROXY` and `HTTPS_PROXY` variables in your terminal:

   export HTTP_PROXY=<proxy_url>
   export HTTPS_PROXY=<proxy_url>

Replace `<proxy_url>` with the URL of your proxy server.

5. Retry Conda operations: After updating or removing the proxy settings, try running your Conda commands again. The ProxyError should no longer occur if the proxy configuration is resolved.

If these steps don't resolve the issue, you may need to consult your network administrator or IT support for further assistance with your proxy configuration.

报错RuntimeError: Exporting/importing meta graphs is not supported when eager execution is enabled. No graph exists when eager execution is enabled.

这个错误通常是由于你的TensorFlow版本启用了Eager Execution（即立即执行模式），而在Eager Execution模式下，无法导出/导入Meta Graph。

解决这个问题的方法之一是禁用Eager Execution。你可以使用以下代码在TensorFlow 2.0中禁用Eager Execution：

import tensorflow as tf
tf.compat.v1.disable_eager_execution()

如果你正在使用TensorFlow 1.x，则可以按照以下方式禁用Eager Execution：

import tensorflow as tf
tf.compat.v1.disable_eager_execution()

如果你需要使用Eager Execution，但又需要导出/导入Meta Graph，则可以使用`tf.compat.v1.Session()`来创建一个不启用Eager Execution的会话。例如，你可以按照以下方式导出Meta Graph：

import tensorflow as tf

# 构建计算图
x = tf.placeholder(tf.float32, shape=[None, 784], name='x')
y = tf.placeholder(tf.float32, shape=[None, 10], name='y')
W = tf.Variable(tf.zeros([784, 10]), name='W')
b = tf.Variable(tf.zeros([10]), name='b')
logits = tf.matmul(x, W) + b
loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=logits, labels=y))
train_op = tf.train.GradientDescentOptimizer(0.5).minimize(loss)

# 创建会话并导出Meta Graph
with tf.compat.v1.Session() as sess:
    sess.run(tf.compat.v1.global_variables_initializer())
    saver = tf.compat.v1.train.Saver()
    saver.save(sess, 'my-model', global_step=0, write_meta_graph=True)

在这个示例中，我们使用`tf.compat.v1.Session()`创建了一个不启用Eager Execution的会话，并使用`saver.save()`方法导出了Meta Graph，使得我们可以在其他地方导入该图。