Exact images and texts embedding size is not showing in keras/tensorflow-CodePudding

Note: it's not an issue I just want to know the reason.

I am trying to implement keras clip model where the model uses text encoder and vision encoder for text and image embeddings generation. when I try to print the shape of compiled images and texts then it just shows the output shape and not the exact number of images or texts it has pre-processed like (None, 256). while there are about 3000 images and texts in my dataset.

def call(self, features, training=False):
    with tf.device("/gpu:0"):
        caption_embeddings = text_encoder(features["caption"], training=training)
        print(caption_embeddings.shape)
    with tf.device("/gpu:1"):
        image_embeddings = vision_encoder(features["image"], training=training)
        print(image_embeddings.shape)
    return caption_embeddings, image_embeddings

Any tensorflow or keras developer will better understand this question. Full code of my colab file is HERE the original implementation is HERE

CodePudding user response：

call is called before training to build the graph, thus the first dimension is not known.

When you compile your model, you can do something like this:

model.fit(..., run_eagerly=True)

and you will see that print that you expect, however the training will be very slow... instead, you can use tf.print(tf.shape(caption_embeddings)) to do it in graph mode