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Described in PR: #2510
versions:
flax: 0.6.1
jax: 0.3.16
jaxlib: 0.3.14
Dropout with rate 1. means not to update related layers. So when validate model, dropout with rate 1. must return output calculated by initialized weights not zero matrix. Pytorch's dropout layer works like I said.
OR at least limit rate range in [0, 1) like Tensorflow.
ValueError: Exception encountered when calling layer "dropout_13" (type Dropout).
`rate` must be a scalar tensor or a float in the range [0, 1). Received: rate=1.0
Call arguments received:
• inputs=tf.Tensor(shape=(16,), dtype=float32)
• training=True
And i dont know why PR build test failed even though i've passed flax's test codes.
Error: Can't use 'tar -xzf' extract archive file: /home/runner/work/_actions/_temp_4a010cdc-4ad5-41a6-8a48-8cc4c4f73390/b725b957-48cd-4024-b802-dbe141e836db.tar.gz. return code: 2.
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