[tvm] branch main updated: [Frontend][Keras] Fix Dense with 3d inputs (#7753)

[mb...@apache.org]

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mbrookhart pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git


The following commit(s) were added to refs/heads/main by this push:
     new 26a5e29  [Frontend][Keras] Fix Dense with 3d inputs (#7753)
26a5e29 is described below

commit 26a5e299bedf8beb255baac7e1c4fb0946f4e17b
Author: Trevor Morris <tr...@amazon.com>
AuthorDate: Tue May 4 17:46:26 2021 -0700

    [Frontend][Keras] Fix Dense with 3d inputs (#7753)
    
    * Fix keras rnn dense
    
    * Fix unit test
    
    * Fix unit test
---
 python/tvm/relay/frontend/keras.py          | 2 +-
 tests/python/frontend/keras/test_forward.py | 5 +++++
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/python/tvm/relay/frontend/keras.py b/python/tvm/relay/frontend/keras.py
index eb16bf2..2227e12 100644
--- a/python/tvm/relay/frontend/keras.py
+++ b/python/tvm/relay/frontend/keras.py
@@ -250,7 +250,7 @@ def _convert_dense(inexpr, keras_layer, etab):
             raise tvm.error.OpAttributeInvalid(
                 "Input shape {} is not valid for operator Dense.".format(input_shape)
             )
-        inexpr = _op.squeeze(inexpr, axis=0)
+        inexpr = _op.squeeze(inexpr, axis=[0])
     out = _op.nn.dense(data=inexpr, **params)
     if keras_layer.use_bias:
         bias = etab.new_const(weightList[1])
diff --git a/tests/python/frontend/keras/test_forward.py b/tests/python/frontend/keras/test_forward.py
index c7f734b..e9420a5 100644
--- a/tests/python/frontend/keras/test_forward.py
+++ b/tests/python/frontend/keras/test_forward.py
@@ -198,6 +198,11 @@ class TestKeras:
         x = keras.layers.Dense(10, activation="relu", kernel_initializer="uniform")(x)
         keras_model = keras.models.Model(data, x)
         verify_keras_frontend(keras_model)
+        # RNN dense
+        data = keras.layers.Input(shape=(1, 32))
+        x = keras.layers.Dense(32, activation="relu", kernel_initializer="uniform")(data)
+        keras_model = keras.models.Model(data, x)
+        verify_keras_frontend(keras_model, need_transpose=False)
 
     def test_forward_permute(self, keras):
         data = keras.layers.Input(shape=(2, 3, 4))