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[Frontend][Relay][Keras] Fix concatenate convert function in axis parsing #15175

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merged 16 commits into from
Jul 1, 2023
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[Frontend][Relay][Keras] Fix concatenate convert function in axis parsing #15175

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3e6c133
fix bug in Concatenate
jikechao Jun 28, 2023
5835920
add test case for concatenate
jikechao Jun 28, 2023
dccabbf
Update test_forward.py
jikechao Jun 28, 2023
68de2e2
Update keras.py
jikechao Jun 28, 2023
eace381
Update keras.py
jikechao Jun 28, 2023
b9ba276
Update keras.py
jikechao Jun 28, 2023
d5e57ae
Update test_forward.py
jikechao Jun 28, 2023
b0550f2
Update keras.py
jikechao Jun 29, 2023
052f36d
Update test_forward.py
jikechao Jun 29, 2023
2474882
Update keras.py
jikechao Jun 29, 2023
1881eb2
Update test_forward.py
jikechao Jun 29, 2023
b792f95
Update test_forward.py
jikechao Jun 29, 2023
f573423
Update test_forward.py
jikechao Jun 30, 2023
3ca62c5
Update keras.py
jikechao Jun 30, 2023
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Update test_forward.py
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Update keras.py
jikechao Jun 30, 2023
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11 changes: 7 additions & 4 deletions python/tvm/relay/frontend/keras.py
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Original file line number Diff line number Diff line change
Expand Up @@ -955,10 +955,13 @@ def _convert_concat(
if input_shape is None:
input_shape = keras_layer.input_shape

if data_layout == "NHWC" or len(input_shape[0]) < 4:
axis = -1
else:
axis = 1
axis = keras_layer.axis
dims = len(input_shape[0])
if data_layout == "NCHW": # need_transpose
if axis == -1:
axis = 1
else:
axis = axis + 1 if axis < dims else 1
return _op.concatenate(_as_list(inexpr), axis=axis)


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19 changes: 19 additions & 0 deletions tests/python/frontend/keras/test_forward.py
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Original file line number Diff line number Diff line change
Expand Up @@ -159,6 +159,24 @@ def test_forward_merge(self, keras_mod):
keras_model = keras_mod.models.Model(data, out)
verify_keras_frontend(keras_model)

def test_forward_concatenate(self, keras_mod):
"""test_forward_concatenate"""
data1 = keras_mod.layers.Input(shape=(1, 2, 2))
data2 = keras_mod.layers.Input(shape=(1, 1, 2))
merge_func = keras_mod.layers.Concatenate(axis=2)
out = merge_func([data1, data2])
keras_model = keras_mod.models.Model([data1, data2], out)
verify_keras_frontend(keras_model, layout="NHWC")
verify_keras_frontend(keras_model, layout="NCHW")
# test default axis (e.g., -1)
data1 = keras_mod.layers.Input(shape=(1, 2, 2))
data2 = keras_mod.layers.Input(shape=(1, 2, 3))
merge_func = keras_mod.layers.Concatenate()
out = merge_func([data1, data2])
keras_model = keras_mod.models.Model([data1, data2], out)
verify_keras_frontend(keras_model, layout="NHWC")
verify_keras_frontend(keras_model, layout="NCHW")

def test_forward_merge_dot(self, keras_mod):
"""test_forward_merge_dot"""
data1 = keras_mod.layers.Input(shape=(2, 2))
Expand Down Expand Up @@ -793,6 +811,7 @@ def test_forward_time_distributed(self, keras_mod):
if __name__ == "__main__":
for k in [keras, tf_keras]:
sut = TestKeras()
sut.test_forward_concatenate(keras_mod=k)
sut.test_forward_merge_dot(keras_mod=k)
sut.test_forward_merge(keras_mod=k)
sut.test_forward_activations(keras_mod=k)
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