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[Bugfix][Relay][Frontend][Keras] Add a assertion to reject a invalid value for attribute units in RNN layers #15334

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Merged
merged 3 commits into from
Jul 20, 2023
+6 −1
Merged

[Bugfix][Relay][Frontend][Keras] Add a assertion to reject a invalid value for attribute units in RNN layers #15334

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ee1511a
capture the invalid value about RNN
jikechao Jul 17, 2023
77c14b9
fix a typo in test case
jikechao Jul 17, 2023
b570401
fix unite in dense
jikechao Jul 17, 2023
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5 changes: 5 additions & 0 deletions python/tvm/relay/frontend/keras.py
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Original file line number Diff line number Diff line change
Expand Up @@ -254,6 +254,8 @@ def _convert_dense(
weightList = keras_layer.get_weights()
weight = etab.new_const(weightList[0].transpose([1, 0]))
params = {"weight": weight, "units": weightList[0].shape[1]}
units = list(weightList[0].shape)[1]
assert units > 0, "The value of units must be a positive integer"
if input_shape is None:
input_shape = keras_layer.input_shape
input_dim = len(input_shape)
Expand Down Expand Up @@ -1008,6 +1010,7 @@ def _convert_lstm(
if keras_layer.go_backwards:
in_data = _op.reverse(in_data, axis=1)
units = list(weightList[0].shape)[1]
assert units > 0, "The value of units must be a positive integer"
time_steps = in_shape[1]
in_data = _op.squeeze(in_data, axis=[0])
in_data = _op.split(in_data, indices_or_sections=time_steps, axis=0)
Expand Down Expand Up @@ -1051,6 +1054,7 @@ def _convert_simple_rnn(
if keras_layer.use_bias:
in_bias = etab.new_const(weightList[2])
units = list(weightList[0].shape)[1]
assert units > 0, "The value of units must be a positive integer"
in_data = _op.nn.batch_flatten(in_data)
ixh = _op.nn.dense(in_data, kernel_weight, units=units)
if keras_layer.use_bias:
Expand Down Expand Up @@ -1080,6 +1084,7 @@ def _convert_gru(
if keras_layer.use_bias:
in_bias = etab.new_const(weightList[2])
units = list(weightList[0].shape)[1]
assert units > 0, "The value of units must be a positive integer"
in_data = _op.nn.batch_flatten(in_data)
matrix_x = _op.nn.dense(in_data, kernel_weight, units=units)
if keras_layer.use_bias:
Expand Down
2 changes: 1 addition & 1 deletion tests/python/frontend/keras/test_forward.py
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Expand Up @@ -244,7 +244,7 @@ def test_forward_activations_except(self, keras_mod):
):
act_funcs = [
keras_mod.layers.LeakyReLU(alpha=None),
keras_mod.layers.LEU(2, 3, 4),
keras_mod.layers.ELU(2, 3, 4),
keras_mod.layers.ReLU(threshold=None),
]
data = keras_mod.layers.Input(shape=(2, 3, 4))
Expand Down