jikechao opened a new pull request, #15337: URL: https://github.com/apache/tvm/pull/15337
This PR fixes a corner bug in the softmax converter in the Keras frontend. If the input dimension of softmax is 1, TVM will crash unexpectedly. ### Model structure:  ### StackTrace ``` Traceback (most recent call last): File "test.py", line 25, in <module> mod, params = relay.frontend.from_keras(model, shape_dict) File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/keras.py", line 1565, in from_keras _convert_layer(keras_layer, etab) File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/keras.py", line 1519, in _convert_layer layout, File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/keras.py", line 1394, in keras_op_to_relay outs = _convert_map[op_name](inexpr, keras_layer, etab, data_layout) File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/keras.py", line 134, in _convert_advanced_activation dims = len(input_shape) TypeError: object of type 'NoneType' has no len() ``` ### Steps to reproduce ``` import tvm import tvm.relay as relay import numpy as np from tensorflow import keras from tensorflow.keras import layers, models input_shape = (11,) input_data = np.random.random(size=input_shape) dtype = 'float32' x = layers.Input(shape=input_shape[1:], dtype=dtype) layer = keras.layers.Softmax() layer.set_weights(layer.get_weights()) y = layer(x) model = models.Model(x, y) res_keras = model.predict(input_data) print(model.summary()) res_keras2 = model(input_data) shape_dict = {'input_1': input_shape} mod, params = relay.frontend.from_keras(model, shape_dict) print(mod) ``` cc @echuraev @Hzfengsy @leandron -- 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]
