From 07a83a669f7f15ba43e64d41e0dc28f950629ec1 Mon Sep 17 00:00:00 2001 From: Yong Wu Date: Tue, 27 Aug 2019 19:15:51 -0700 Subject: [PATCH] [Bugfix][Keras] axis of softmax (#3834) --- python/tvm/relay/frontend/keras.py | 13 +++++++++++-- tests/python/frontend/keras/test_forward.py | 6 +++++- 2 files changed, 16 insertions(+), 3 deletions(-) diff --git a/python/tvm/relay/frontend/keras.py b/python/tvm/relay/frontend/keras.py index 4d3b976..8be3d22 100644 --- a/python/tvm/relay/frontend/keras.py +++ b/python/tvm/relay/frontend/keras.py @@ -117,7 +117,16 @@ def _convert_advanced_activation(inexpr, keras_layer, etab): act_type = type(keras_layer).__name__ if act_type == 'Softmax': - return _op.nn.softmax(inexpr, axis=1) + axis = keras_layer.axis + dims = len(keras_layer.input_shape) + if isinstance(axis, list): + raise tvm.error.OpAttributeUnImplemented( + 'Softmax with axes {} is not supported.'.format(axis)) + if axis == -1: + axis = 1 + else: + axis = axis + 1 if axis < dims - 1 else 1 + return _op.nn.softmax(inexpr, axis=axis) if act_type == 'ReLU': if keras_layer.max_value: return _op.clip(inexpr, a_min=0., a_max=float(keras_layer.max_value)) @@ -344,7 +353,7 @@ def _convert_pooling(inexpr, keras_layer, etab): pad_l, pad_r = _get_pad_pair(in_w, pool_w, stride_w) params['padding'] = [pad_t, pad_l, pad_b, pad_r] else: - raise tvm.error.OpAttributeUnimplemented( + raise tvm.error.OpAttributeUnImplemented( 'Padding with {} is not supported in operator Pooling.'.format(keras_layer.padding)) if pool_type == 'MaxPooling2D': return _op.nn.max_pool2d(inexpr, **params) diff --git a/tests/python/frontend/keras/test_forward.py b/tests/python/frontend/keras/test_forward.py index f571370..9996bb7 100644 --- a/tests/python/frontend/keras/test_forward.py +++ b/tests/python/frontend/keras/test_forward.py @@ -95,6 +95,11 @@ def test_forward_merge(): def test_forward_activations(): data = keras.layers.Input(shape=(32, 32, 3)) act_funcs = [keras.layers.Activation('softmax'), + keras.layers.Softmax(), + keras.layers.Softmax(axis=-1), + keras.layers.Softmax(axis=1), + keras.layers.Softmax(axis=2), + keras.layers.Softmax(axis=3), keras.layers.Activation('softplus'), keras.layers.Activation('relu'), keras.layers.Activation('softsign'), @@ -103,7 +108,6 @@ def test_forward_activations(): keras.layers.Activation('tanh'), keras.layers.Activation('linear'), keras.layers.Activation('selu'), - keras.layers.Softmax(), keras.layers.ReLU(), keras.layers.ReLU(max_value=6.), keras.layers.LeakyReLU(alpha=0.3), -- 2.7.4