sayakpaul opened a new issue #9819: URL: https://github.com/apache/tvm/issues/9819
I am trying to compile the following model using [this guide](https://tvm.apache.org/docs/how_to/compile_models/from_keras.html): ```py import tensorflow as tf import tensorflow_hub as hub hub_url = "gs://cloud-tpu-checkpoints/efficientnet/v2/hub/efficientnetv2-b2/feature-vector" efficientv2_b2 = tf.keras.Sequential( [ tf.keras.layers.InputLayer(input_shape=(260, 260, 3)), hub.KerasLayer(hub_url, trainable=False), tf.keras.layers.Dense(5, activation="softmax"), ] ) ``` Compilation code: ```py from tvm import te import tvm import tvm.relay as relay shape_dict = {"input_1": (1, 3, 260, 260)} mod, params = relay.frontend.from_keras(efficientv2_b2, shape_dict) target = "cpu" dev = tvm.cpu(0) with tvm.transform.PassContext(opt_level=0): model = relay.build_module.create_executor("graph", mod, dev, target, params).evaluate() ``` It leads to complaining Hub layers are not being supported by TVM. Is there a workaround? ### Expected behavior The compilation would be complete without fail. ### Actual behavior It leads to complaining Hub layers are not being supported by TVM. ### Environment I built TVM with NNPack following the guide: https://tvm.apache.org/docs/install/from_source.html. I am using Debian 10 on a GCP machine (`n1-standard-8`). TensorFlow version is 2.7.0. ### Steps to reproduce Have already provided it. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
