BROADCAST tensorflow type_error ai_generated true

InvalidArgumentError: Incompatible shapes for broadcasting: [64, 128, 3] vs [64, 128, 4]

ID: tensorflow/tensor-broadcast-shape-error

Also available as: JSON · Markdown · 中文
85%Fix Rate
90%Confidence
1Evidence
2024-01-05First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
tensorflow 2.13.0 active — — —
tensorflow 2.14.0 active — — —
tensorflow 2.15.0 active — — —

Root Cause

Two tensors with incompatible last dimension sizes are being used in an element-wise operation that requires broadcasting.

generic

中文

两个张量的最后一个维度大小不兼容，在进行需要广播的逐元素操作时出错。

Official Documentation

https://www.tensorflow.org/guide/tensor

Workarounds

  1. 90% success Reshape or pad the smaller tensor to match the larger one. For example: `tensor_a = tf.pad(tensor_a, [[0,0], [0,0], [0,1]])` to add an extra channel. 
    Reshape or pad the smaller tensor to match the larger one. For example: `tensor_a = tf.pad(tensor_a, [[0,0], [0,0], [0,1]])` to add an extra channel.

中文步骤

  1. Reshape or pad the smaller tensor to match the larger one. For example: `tensor_a = tf.pad(tensor_a, [[0,0], [0,0], [0,1]])` to add an extra channel.

Dead Ends

Common approaches that don't work:

  1. 90% fail

    Adding dimensions does not fix the last dimension mismatch; it only changes the rank.

  2. 95% fail

    Numpy operations break the computation graph and cannot be used in training.