Add canonical test conv2d model data and generation script.

This model will be used in upcoming unit tests to verify model memory allocation. It does not provide any relevant classification - just simply builds a model that would be suitable for an embedded device.

PiperOrigin-RevId: 314408208
Change-Id: Id081f93f1b2864c2671ae7b27fe994bdf5acbfc1

tensorflow/lite/micro/testing/BUILD

@@ -48,3 +48,26 @@ cc_library(
         "//tensorflow/lite/micro:micro_time",
     ],
 )
+
+cc_library(
+    name = "test_conv_model",
+    srcs = [
+        "test_conv_model.cc",
+    ],
+    hdrs = [
+        "test_conv_model.h",
+    ],
+)
+
+py_binary(
+    name = "generate_test_models",
+    srcs = ["generate_test_models.py"],
+    python_version = "PY3",
+    srcs_version = "PY3ONLY",
+    tags = ["noubsan"],  # TODO(b/144512025): Fix raw_to_bitmap_test to fix ubsan failure.
+    deps = [
+        "//tensorflow:tensorflow_py",
+        "//third_party/py/numpy",
+        "@absl_py//absl:app",
+    ],
+)

tensorflow/lite/micro/testing/generate_test_models.py

@@ -0,0 +1,81 @@
+# Copyright 2020 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.
+# ==============================================================================
+"""Python utility script to generate unit test model data."""
+
+# Steps to regenerate model test data:
+# TODO(b/158011574): Do these steps in the script here instead of manually.
+# 1.) Run this script
+# 2.) Hexdump the model into a .h/.cc file:
+#       xxd -i /tmp/tf_micro_conv_test_model.tflite > /tmp/temp.cc
+# 3.) Copy/replace contents of temp.cc into desired header/source files (e.g.
+#     test_conv_model.h/.cc
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from absl import app
+import numpy as np
+import tensorflow.compat.v2 as tf
+
+
+def generate_conv_model():
+  """Creates a basic Keras model and converts to tflite.
+
+  This model does not make any relevant classifications. It only exists to
+  generate a model that is designed to run on embedded devices.
+  """
+  input_shape = (16, 16, 1)
+
+  model = tf.keras.models.Sequential()
+  model.add(
+      tf.keras.layers.Conv2D(16, 3, activation="relu", input_shape=input_shape))
+  model.add(tf.keras.layers.Conv2D(32, 3, activation="relu"))
+  model.add(tf.keras.layers.MaxPooling2D(2))
+  model.add(tf.keras.layers.Flatten())
+  model.add(tf.keras.layers.Dense(10))
+  model.compile(
+      optimizer="adam", loss="categorical_crossentropy", metrics=["accuracy"])
+  model.summary()
+
+  # Test with random data
+  data_x = np.random.rand(12, 16, 16, 1)
+  data_y = np.random.randint(2, size=(12, 10))
+  model.fit(data_x, data_y, epochs=5)
+
+  def representative_dataset_gen():
+    for _ in range(12):
+      yield [np.random.rand(16, 16).reshape(1, 16, 16, 1).astype(np.float32)]
+
+  # Now convert to a TFLite model with full int8 quantization:
+  converter = tf.lite.TFLiteConverter.from_keras_model(model)
+  converter.optimizations = [tf.lite.Optimize.DEFAULT]
+  converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
+  converter.experimental_new_converter = True
+  converter.inference_input_type = tf.int8
+  converter.inference_output_type = tf.int8
+  converter.representative_dataset = representative_dataset_gen
+
+  tflite_model = converter.convert()
+  open("/tmp/tf_micro_conv_test_model.int8.tflite", "wb").write(tflite_model)
+
+
+def main(argv):
+  del argv  # Unused for now
+  generate_conv_model()
+
+
+if __name__ == "__main__":
+  app.run(main)

tensorflow/lite/micro/testing/test_conv_model.h

@@ -0,0 +1,23 @@
+/* Copyright 2020 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.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_MICRO_TESTING_TEST_CONV_MODEL_H_
+#define TENSORFLOW_LITE_MICRO_TESTING_TEST_CONV_MODEL_H_
+
+// See generate_test_models.py for updating the contents of this model:
+extern const unsigned char kTestConvModelData[];
+extern const unsigned int kTestConvModelDataSize;
+
+#endif  // TENSORFLOW_LITE_MICRO_TESTING_TEST_CONV_MODEL_H_