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Convert softmax lambda to keras layer #107

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Convert softmax lambda to keras layer #107

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9 changes: 2 additions & 7 deletions onnx2keras/activation_layers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -141,14 +141,9 @@ def convert_softmax(node, params, layers, lambda_func, node_name, keras_name):

input_0 = ensure_tf_type(layers[node.input[0]], name="%s_const" % keras_name)

def target_layer(x, axis=params['axis']):
import tensorflow as tf
return tf.nn.softmax(x, axis=axis)

lambda_layer = keras.layers.Lambda(target_layer, name=keras_name)
layers[node_name] = lambda_layer(input_0)
softmax_layer = keras.layers.Softmax(axis=params['axis'], name=keras_name)
layers[node_name] = softmax_layer(input_0)
layers[node_name].set_shape(layers[node_name].shape)
lambda_func[keras_name] = target_layer


def convert_prelu(node, params, layers, lambda_func, node_name, keras_name):
Expand Down