Add droput and its derivative in Keras converter (#126)

* Add droput and its derivative in Keras model.

* code polishing.

Author: wenbingl

onnxmltools/convert/keras/__init__.py

@@ -4,4 +4,4 @@
 # license information.
 # --------------------------------------------------------------------------
 
-from .convert import convert
+from .convert import convert

onnxmltools/convert/keras/operator_converters/Dropout.py

@@ -0,0 +1,19 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+from keras.layers import Dropout, SpatialDropout1D, SpatialDropout2D, SpatialDropout3D
+
+from ...common._apply_operation import apply_identity
+from ...common._registration import register_converter
+
+
+def convert_keras_drop(scope, operator, container):
+    apply_identity(scope, operator.inputs[0].full_name, operator.outputs[0].full_name, container)
+
+register_converter(Dropout, convert_keras_drop)
+register_converter(SpatialDropout1D, convert_keras_drop)
+register_converter(SpatialDropout2D, convert_keras_drop)
+register_converter(SpatialDropout3D, convert_keras_drop)

onnxmltools/convert/keras/operator_converters/__init__.py

@@ -14,6 +14,7 @@
 from . import Crop
 from . import Dense
 from . import Dot
+from . import Dropout
 from . import Embed
 from . import Flatten
 from . import GRU
@@ -26,4 +27,3 @@
 from . import SimpleRNN
 from . import Upsample
 from . import ZeroPad
-

onnxmltools/convert/keras/shape_calculators/Lazy.py

@@ -84,3 +84,9 @@ def calculate_lazy_output_shapes(operator):
 
 # RepeatVector
 register_shape_calculator(keras.layers.RepeatVector, calculate_lazy_output_shapes)
+
+# Dropout
+register_shape_calculator(keras.layers.Dropout, calculate_lazy_output_shapes)
+register_shape_calculator(keras.layers.SpatialDropout1D, calculate_lazy_output_shapes)
+register_shape_calculator(keras.layers.SpatialDropout2D, calculate_lazy_output_shapes)
+register_shape_calculator(keras.layers.SpatialDropout3D, calculate_lazy_output_shapes)

tests/end2end/test_single_operator_with_cntk_backend.py

@@ -14,7 +14,7 @@
 from keras.models import Sequential, Model
 from keras.layers import Input, Dense, Conv2D, MaxPooling2D, AveragePooling2D, Conv2DTranspose, \
     Dot, Embedding, BatchNormalization, GRU, Activation, PReLU, LeakyReLU, ThresholdedReLU, Maximum, \
-    Add, Average, Multiply, Concatenate, UpSampling2D, Flatten, RepeatVector, Reshape
+    Add, Average, Multiply, Concatenate, UpSampling2D, Flatten, RepeatVector, Reshape, Dropout
 from keras.initializers import RandomUniform
 
 np.random.seed(0)
@@ -163,7 +163,7 @@ def test_dense(self):
 
         input = Input(shape=(C,))
         result = Dense(D)(input)
-        keras_model = Model(input=input, output=result)
+        keras_model = Model(inputs=input, outputs=result)
         keras_model.compile(optimizer='adagrad', loss='mse')
 
         coreml_model = coremltools.converters.keras.convert(keras_model)
@@ -174,6 +174,19 @@ def test_dense(self):
 
         self.assertTrue(np.allclose(y_reference, y_produced))
 
+    def test_dense_with_dropout(self):
+        N, C, D = 2, 3, 2
+        x = _create_tensor(N, C)
+
+        input = Input(shape=(C,))
+        hidden = Dense(D, activation='relu')(input)
+        result = Dropout(0.2)(hidden)
+
+        keras_model = Model(inputs=input, outputs=result)
+        keras_model.compile(optimizer='sgd', loss='mse')
+
+        self._test_one_to_one_operator_core_keras(keras_model, x)
+
     def test_conv_4d(self):
         N, C, H, W = 1, 2, 4, 3
         x = _create_tensor(N, C, H, W)