integrations/tensorflow/e2e/keras/lstm_static_test.py

# Lint as: python3
# Copyright 2019 Google LLC
#
# 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
#
#      https://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.

# This test is the same as keras_lstm_test, but all shapes are static.
# This stresses the TensorList lowering more specifically.

import numpy as np
from pyiree.tf.support import tf_test_utils
from pyiree.tf.support import tf_utils
import tensorflow.compat.v2 as tf

NUM_UNITS = 10
NUM_TIMESTEPS = 24
NUM_BATCH = 7
INPUT_SHAPE = [NUM_BATCH, NUM_TIMESTEPS, NUM_UNITS]


def lstm_module():
  tf_utils.set_random_seed()
  inputs = tf.keras.layers.Input(batch_size=NUM_BATCH, shape=INPUT_SHAPE[1:])
  outputs = tf.keras.layers.LSTM(units=NUM_UNITS, return_sequences=True)(inputs)
  model = tf.keras.Model(inputs, outputs)
  module = tf.Module()
  module.m = model
  module.predict = tf.function(
      input_signature=[tf.TensorSpec(INPUT_SHAPE, tf.float32)])(
          model.call)
  return module


@tf_test_utils.compile_module(lstm_module, exported_names=["predict"])
class LstmTest(tf_test_utils.SavedModelTestCase):

  def test_lstm(self):
    m = self.get_module()
    m.predict(
        tf.constant(
            np.arange(NUM_BATCH * NUM_TIMESTEPS * NUM_UNITS,
                      dtype=np.float32).reshape(
                          [NUM_BATCH, NUM_TIMESTEPS, NUM_UNITS]),
            shape=[NUM_BATCH, NUM_TIMESTEPS,
                   NUM_UNITS])).print().assert_all_close(1e-5, 1e-5)


if __name__ == "__main__":
  if hasattr(tf, "enable_v2_behavior"):
    tf.enable_v2_behavior()
  tf.test.main()