1 files changed, 114 insertions, 0 deletions
diff --git a/runtimes/tests/neural_networks_test/specs/V1_0/svdf_state.mod.py b/runtimes/tests/neural_networks_test/specs/V1_0/svdf_state.mod.py
new file mode 100644
index 000000000..dc3e4f420
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/specs/V1_0/svdf_state.mod.py
@@ -0,0 +1,114 @@
+#
+# Copyright (C) 2017 The Android Open Source Project
+#
+# 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.
+#
+
+batches = 2
+units = 4
+input_size = 3
+memory_size = 10
+
+model = Model()
+
+input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
+weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
+weights_time = Input("weights_time", "TENSOR_FLOAT32", "{%d, %d}" % (units, memory_size))
+bias = Input("bias", "TENSOR_FLOAT32", "{%d}" % (units))
+state_in = Input("state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, memory_size*units))
+rank_param = Int32Scalar("rank_param", 1)
+activation_param = Int32Scalar("activation_param", 0)
+state_out = Output("state_out", "TENSOR_FLOAT32", "{%d, %d}" % (batches, memory_size*units))
+output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (batches, units))
+
+model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
+                        rank_param, activation_param).To([state_out, output])
+
+input0 = {
+    weights_feature: [
+        -0.31930989, -0.36118156, 0.0079667, 0.37613347,
+      0.22197971, 0.12416199, 0.27901134, 0.27557442,
+      0.3905206, -0.36137494, -0.06634006, -0.10640851
+    ],
+    weights_time: [
+        -0.31930989, 0.37613347,  0.27901134,  -0.36137494, -0.36118156,
+      0.22197971,  0.27557442,  -0.06634006, 0.0079667,   0.12416199,
+
+       0.3905206,   -0.10640851, -0.0976817,  0.15294972,  0.39635518,
+      -0.02702999, 0.39296314,  0.15785322,  0.21931258,  0.31053296,
+
+       -0.36916667, 0.38031587,  -0.21580373, 0.27072677,  0.23622236,
+      0.34936687,  0.18174365,  0.35907319,  -0.17493086, 0.324846,
+
+       -0.10781813, 0.27201805,  0.14324132,  -0.23681851, -0.27115166,
+      -0.01580888, -0.14943552, 0.15465137,  0.09784451,  -0.0337657
+    ],
+    bias: [],
+}
+
+input0[input] = [
+  0.14278367,  -1.64410412, -0.75222826,
+  0.14278367,  -1.64410412, -0.75222826,
+]
+input0[state_in]  = [
+  0, 0, 0, 0,
+  0, 0, 0, 0,
+  0.119996, 0, 0, 0,
+  0, 0, 0, 0,
+  0, 0, -0.166701, 0,
+  0, 0, 0, 0,
+  0, 0, 0, 0,
+  -0.44244, 0, 0, 0,
+  0, 0, 0, 0,
+  0, 0, 0.0805206, 0,
+  0, 0, 0, 0,
+  0, 0, 0, 0,
+  0.119996, 0, 0, 0,
+  0, 0, 0, 0,
+  0, 0, -0.166701, 0,
+  0, 0, 0, 0,
+  0, 0, 0, 0,
+  -0.44244, 0, 0, 0,
+  0, 0, 0, 0,
+  0, 0, 0.0805206, 0,
+]
+output0 = {
+    state_out : [
+  0, 0, 0, 0,
+  0, 0, 0, 0.119996,
+  0.542235, 0, 0, 0,
+  0, 0, 0, 0,
+  0, -0.166701, -0.40465, 0,
+  0, 0, 0, 0,
+  0, 0, 0, -0.44244,
+  -0.706995, 0, 0, 0,
+  0, 0, 0, 0,
+  0, 0.0805206, 0.137515, 0,
+  0, 0, 0, 0,
+  0, 0, 0, 0.119996,
+  0.542235, 0, 0, 0,
+  0, 0, 0, 0,
+  0, -0.166701, -0.40465, 0,
+  0, 0, 0, 0,
+  0, 0, 0, -0.44244,
+  -0.706995, 0, 0, 0,
+  0, 0, 0, 0,
+  0, 0.0805206, 0.137515, 0,
+    ],
+    output : [
+  0.068281,    -0.162217,  -0.152268, 0.00323521,
+  0.068281,    -0.162217,  -0.152268, 0.00323521,
+    ]
+}
+
+Example((input0, output0))