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authorLester Solbakken <lesters@oath.com>2020-06-12 12:16:56 +0200
committerLester Solbakken <lesters@oath.com>2020-06-12 12:16:56 +0200
commit0a886d74d4c9ffde41eef1f7e3c186b60b9f3726 (patch)
treee142b94341563b28a2b4a0e26fe77458749d2ed9 /config-model/src/test/integration
parent8de8ff4f87295d812d4e660f0216953726200c92 (diff)
Import Tensorflow models vis ONNX conversion
Diffstat (limited to 'config-model/src/test/integration')
-rw-r--r--config-model/src/test/integration/onnx/models/mnist_softmax.onnxbin31758 -> 31765 bytes
-rw-r--r--config-model/src/test/integration/onnx/models/small_constants_and_functions.onnxbin0 -> 274 bytes
-rwxr-xr-xconfig-model/src/test/integration/onnx/models/small_constants_and_functions.py51
-rw-r--r--config-model/src/test/integration/tensorflow/models/blog/saved/saved_model.pbtxt14726
-rw-r--r--config-model/src/test/integration/tensorflow/models/blog/saved/variables/variables.data-00000-of-00001bin1579020 -> 0 bytes
-rw-r--r--config-model/src/test/integration/tensorflow/models/blog/saved/variables/variables.indexbin520 -> 0 bytes
-rw-r--r--config-model/src/test/integration/tensorflow/models/mnist/saved/saved_model.pbtxt8830
-rw-r--r--config-model/src/test/integration/tensorflow/models/mnist/saved/variables/variables.data-00000-of-00001bin1066440 -> 0 bytes
-rw-r--r--config-model/src/test/integration/tensorflow/models/mnist/saved/variables/variables.indexbin308 -> 0 bytes
-rw-r--r--config-model/src/test/integration/tensorflow/models/mnist/simple_mnist.py100
-rw-r--r--config-model/src/test/integration/tensorflow/models/mnist_softmax/mnist_sftmax_with_saving.py93
-rw-r--r--config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/saved_model.pbtxt5039
-rw-r--r--config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/variables/variables.data-00000-of-00001bin31400 -> 0 bytes
-rw-r--r--config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/variables/variables.indexbin165 -> 0 bytes
-rw-r--r--config-model/src/test/integration/tensorflow/services.xml6
15 files changed, 51 insertions, 28794 deletions
diff --git a/config-model/src/test/integration/onnx/models/mnist_softmax.onnx b/config-model/src/test/integration/onnx/models/mnist_softmax.onnx
index a86019bf53a..395cd734444 100644
--- a/config-model/src/test/integration/onnx/models/mnist_softmax.onnx
+++ b/config-model/src/test/integration/onnx/models/mnist_softmax.onnx
Binary files differ
diff --git a/config-model/src/test/integration/onnx/models/small_constants_and_functions.onnx b/config-model/src/test/integration/onnx/models/small_constants_and_functions.onnx
new file mode 100644
index 00000000000..0d4bffa5b57
--- /dev/null
+++ b/config-model/src/test/integration/onnx/models/small_constants_and_functions.onnx
Binary files differ
diff --git a/config-model/src/test/integration/onnx/models/small_constants_and_functions.py b/config-model/src/test/integration/onnx/models/small_constants_and_functions.py
new file mode 100755
index 00000000000..7b04b93fee2
--- /dev/null
+++ b/config-model/src/test/integration/onnx/models/small_constants_and_functions.py
@@ -0,0 +1,51 @@
+# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+
+import onnx
+from onnx import helper, TensorProto
+
+input = helper.make_tensor_value_info('input', TensorProto.FLOAT, [3])
+output = helper.make_tensor_value_info('output', TensorProto.FLOAT, [3])
+
+initializers = [
+ helper.make_tensor(
+ name='epsilon', # small constant: no dimensions
+ data_type=TensorProto.FLOAT,
+ dims=(),
+ vals=[1e-6]
+ )
+]
+
+nodes = [
+ onnx.helper.make_node(
+ 'Exp',
+ inputs=['input'],
+ outputs=['exp_output']
+ ),
+ onnx.helper.make_node(
+ 'ReduceSum',
+ inputs=['exp_output'],
+ outputs=['sum_exp_output'],
+ axes=[0]
+ ),
+ onnx.helper.make_node(
+ 'Add',
+ inputs=['sum_exp_output', 'epsilon'],
+ outputs=['add_output']
+ ),
+ onnx.helper.make_node(
+ 'Div',
+ inputs=['exp_output', 'add_output'],
+ outputs=['output']
+ )
+]
+
+graph_def = onnx.helper.make_graph(
+ nodes = nodes,
+ name = 'test',
+ inputs = [input],
+ outputs = [output],
+ initializer = initializers
+)
+model_def = helper.make_model(graph_def, producer_name='small_constants_and_functions.py')
+onnx.checker.check_model(model_def)
+onnx.save(model_def, 'small_constants_and_functions.onnx')
diff --git a/config-model/src/test/integration/tensorflow/models/blog/saved/saved_model.pbtxt b/config-model/src/test/integration/tensorflow/models/blog/saved/saved_model.pbtxt
deleted file mode 100644
index a669e69b709..00000000000
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+++ /dev/null
@@ -1,14726 +0,0 @@
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diff --git a/config-model/src/test/integration/tensorflow/models/mnist/saved/variables/variables.data-00000-of-00001 b/config-model/src/test/integration/tensorflow/models/mnist/saved/variables/variables.data-00000-of-00001
deleted file mode 100644
index ed4af6c0f8c..00000000000
--- a/config-model/src/test/integration/tensorflow/models/mnist/saved/variables/variables.data-00000-of-00001
+++ /dev/null
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diff --git a/config-model/src/test/integration/tensorflow/models/mnist/saved/variables/variables.index b/config-model/src/test/integration/tensorflow/models/mnist/saved/variables/variables.index
deleted file mode 100644
index c877b02b42a..00000000000
--- a/config-model/src/test/integration/tensorflow/models/mnist/saved/variables/variables.index
+++ /dev/null
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diff --git a/config-model/src/test/integration/tensorflow/models/mnist/simple_mnist.py b/config-model/src/test/integration/tensorflow/models/mnist/simple_mnist.py
deleted file mode 100644
index 7494e93fa71..00000000000
--- a/config-model/src/test/integration/tensorflow/models/mnist/simple_mnist.py
+++ /dev/null
@@ -1,100 +0,0 @@
-# Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-
-# Common imports
-import numpy as np
-import tensorflow as tf
-
-from tensorflow.examples.tutorials.mnist import input_data
-from datetime import datetime
-
-now = datetime.utcnow().strftime("%Y%m%d%H%M%S")
-root_logdir = "tf_logs"
-logdir = "{}/run-{}/".format(root_logdir, now)
-
-mnist = input_data.read_data_sets("/tmp/data/")
-X_train = mnist.train.images
-X_test = mnist.test.images
-y_train = mnist.train.labels.astype("int")
-y_test = mnist.test.labels.astype("int")
-
-n_inputs = 28*28 # MNIST
-n_hidden1 = 300
-n_hidden2 = 100
-n_hidden3 = 40
-n_outputs = 10
-
-learning_rate = 0.01
-n_epochs = 20
-batch_size = 50
-
-input = tf.placeholder(tf.float32, shape=(None, n_inputs), name="input")
-y = tf.placeholder(tf.int64, shape=(None), name="y")
-
-
-def neuron_layer(X, n_neurons, name, activation=None):
- with tf.name_scope(name):
- n_inputs = int(X.get_shape()[1])
- stddev = 2 / np.sqrt(n_inputs)
- init = tf.truncated_normal((n_inputs, n_neurons), stddev=stddev)
- W = tf.Variable(init, name="weights")
- b = tf.Variable(tf.zeros([n_neurons]), name="bias")
- Z = tf.matmul(X, W) + b
- if activation is not None:
- return activation(Z)
- else:
- return Z
-
-
-def leaky_relu(z, name=None):
- return tf.maximum(0.01 * z, z, name=name)
-
-def leaky_relu_with_small_constant(z, name=None):
- return tf.maximum(tf.constant(0.01, shape=[1]) * z, z, name=name)
-
-with tf.name_scope("dnn"):
- hidden1 = neuron_layer(input, n_hidden1, name="hidden1", activation=leaky_relu)
- hidden2 = neuron_layer(hidden1, n_hidden2, name="hidden2", activation=leaky_relu_with_small_constant)
- logits = neuron_layer(hidden2, n_outputs, name="outputs") #, activation=tf.nn.sigmoid)
-
-with tf.name_scope("loss"):
- xentropy = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=y, logits=logits)
- loss = tf.reduce_mean(xentropy, name="loss")
-
-with tf.name_scope("train"):
- optimizer = tf.train.GradientDescentOptimizer(learning_rate)
- training_op = optimizer.minimize(loss)
-
-with tf.name_scope("eval"):
- correct = tf.nn.in_top_k(logits, y, 1)
- accuracy = tf.reduce_mean(tf.cast(correct, tf.float32))
-
-init = tf.global_variables_initializer()
-accuracy_summary = tf.summary.scalar('Accuracy', accuracy)
-file_writer = tf.summary.FileWriter(logdir, tf.get_default_graph())
-
-with tf.Session() as sess:
- init.run()
- for epoch in range(n_epochs):
- for iteration in range(mnist.train.num_examples // batch_size):
- X_batch, y_batch = mnist.train.next_batch(batch_size)
- sess.run(training_op, feed_dict={input: X_batch, y: y_batch})
- acc_train = accuracy.eval(feed_dict={input: X_batch, y: y_batch})
- acc_val = accuracy.eval(feed_dict={input: mnist.validation.images,
- y: mnist.validation.labels})
- print(epoch, "Train accuracy:", acc_train, "Val accuracy:", acc_val)
-
- # Save summary for tensorboard
- summary_str = accuracy_summary.eval(feed_dict={input: mnist.validation.images,
- y: mnist.validation.labels})
- file_writer.add_summary(summary_str, epoch)
-
- export_path = "saved"
- print('Exporting trained model to ', export_path)
- builder = tf.saved_model.builder.SavedModelBuilder(export_path)
- signature = tf.saved_model.signature_def_utils.predict_signature_def(inputs = {'x':input}, outputs = {'y':logits})
- builder.add_meta_graph_and_variables(sess,
- [tf.saved_model.tag_constants.SERVING],
- signature_def_map={'serving_default':signature})
- builder.save(as_text=True)
-
-file_writer.close()
diff --git a/config-model/src/test/integration/tensorflow/models/mnist_softmax/mnist_sftmax_with_saving.py b/config-model/src/test/integration/tensorflow/models/mnist_softmax/mnist_sftmax_with_saving.py
deleted file mode 100644
index 3f4f794d2ac..00000000000
--- a/config-model/src/test/integration/tensorflow/models/mnist_softmax/mnist_sftmax_with_saving.py
+++ /dev/null
@@ -1,93 +0,0 @@
-# Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-
-"""A very simple MNIST classifier.
-
-See extensive documentation at
-https://www.tensorflow.org/get_started/mnist/beginners
-"""
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import argparse
-import sys
-
-from tensorflow.examples.tutorials.mnist import input_data
-
-import tensorflow as tf
-
-FLAGS = None
-
-
-def main(_):
- # Import data
- mnist = input_data.read_data_sets(FLAGS.data_dir, one_hot=True)
-
- # Create the model
- x = tf.placeholder(tf.float32, [None, 784])
-
- with tf.name_scope("layer"):
- W = tf.Variable(tf.zeros([784, 10]))
- b = tf.Variable(tf.zeros([10]))
- y = tf.matmul(x, W) + b
-
-
- # Define loss and optimizer
- y_ = tf.placeholder(tf.float32, [None, 10])
-
- # The raw formulation of cross-entropy,
- #
- # tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(tf.nn.softmax(y)),
- # reduction_indices=[1]))
- #
- # can be numerically unstable.
- #
- # So here we use tf.nn.softmax_cross_entropy_with_logits on the raw
- # outputs of 'y', and then average across the batch.
- cross_entropy = tf.reduce_mean(
- tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))
- train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
-
- sess = tf.InteractiveSession()
- tf.global_variables_initializer().run()
- # Train
- for _ in range(1000):
- batch_xs, batch_ys = mnist.train.next_batch(100)
- sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
-
- # Test trained model
- correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
- accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
- print(sess.run(accuracy, feed_dict={x: mnist.test.images,
- y_: mnist.test.labels}))
-
- # Save the model
- export_path = "saved"
- print('Exporting trained model to ', export_path)
- builder = tf.saved_model.builder.SavedModelBuilder(export_path)
- signature = tf.saved_model.signature_def_utils.predict_signature_def(inputs = {'x':x}, outputs = {'y':y})
- builder.add_meta_graph_and_variables(sess,
- [tf.saved_model.tag_constants.SERVING],
- signature_def_map={'serving_default':signature})
- builder.save(as_text=True)
-
-if __name__ == '__main__':
- parser = argparse.ArgumentParser()
- parser.add_argument('--data_dir', type=str, default='/tmp/tensorflow/mnist/input_data',
- help='Directory for storing input data')
- FLAGS, unparsed = parser.parse_known_args()
- tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
diff --git a/config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/saved_model.pbtxt b/config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/saved_model.pbtxt
deleted file mode 100644
index 05b0e4e0f29..00000000000
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+++ /dev/null
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- keep_checkpoint_every_n_hours: 10000.0
- version: V2
- }
- collection_def {
- key: "train_op"
- value {
- node_list {
- value: "GradientDescent"
- }
- }
- }
- collection_def {
- key: "trainable_variables"
- value {
- bytes_list {
- value: "\n\020layer/Variable:0\022\025layer/Variable/Assign\032\025layer/Variable/read:02\rlayer/zeros:0"
- value: "\n\022layer/Variable_1:0\022\027layer/Variable_1/Assign\032\027layer/Variable_1/read:02\017layer/zeros_1:0"
- }
- }
- }
- collection_def {
- key: "variables"
- value {
- bytes_list {
- value: "\n\020layer/Variable:0\022\025layer/Variable/Assign\032\025layer/Variable/read:02\rlayer/zeros:0"
- value: "\n\022layer/Variable_1:0\022\027layer/Variable_1/Assign\032\027layer/Variable_1/read:02\017layer/zeros_1:0"
- }
- }
- }
- signature_def {
- key: "serving_default"
- value {
- inputs {
- key: "x"
- value {
- name: "Placeholder:0"
- dtype: DT_FLOAT
- tensor_shape {
- dim {
- size: -1
- }
- dim {
- size: 784
- }
- }
- }
- }
- outputs {
- key: "y"
- value {
- name: "layer/add:0"
- dtype: DT_FLOAT
- tensor_shape {
- dim {
- size: -1
- }
- dim {
- size: 10
- }
- }
- }
- }
- method_name: "tensorflow/serving/predict"
- }
- }
-}
diff --git a/config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/variables/variables.data-00000-of-00001 b/config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/variables/variables.data-00000-of-00001
deleted file mode 100644
index 826b0280abf..00000000000
--- a/config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/variables/variables.data-00000-of-00001
+++ /dev/null
Binary files differ
diff --git a/config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/variables/variables.index b/config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/variables/variables.index
deleted file mode 100644
index d00fc5b06ed..00000000000
--- a/config-model/src/test/integration/tensorflow/models/mnist_softmax/saved/variables/variables.index
+++ /dev/null
Binary files differ
diff --git a/config-model/src/test/integration/tensorflow/services.xml b/config-model/src/test/integration/tensorflow/services.xml
deleted file mode 100644
index aa1c0223bdf..00000000000
--- a/config-model/src/test/integration/tensorflow/services.xml
+++ /dev/null
@@ -1,6 +0,0 @@
-<!-- Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -->
-<services>
- <container version="1.0">
-
- </container>
-</services>