1 files changed, 64 insertions, 0 deletions
diff --git a/tests/nnapi/specs/V1_2/minimum.mod.py b/tests/nnapi/specs/V1_2/minimum.mod.py
new file mode 100755
index 000000000..76b058612
--- /dev/null
+++ b/tests/nnapi/specs/V1_2/minimum.mod.py
@@ -0,0 +1,64 @@
+#
+# Copyright (C) 2018 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.
+#
+
+def test(name, input0, input1, output0, input0_data, input1_data, output_data):
+  model = Model().Operation("MINIMUM", input0, input1).To(output0)
+
+  quant8 = DataTypeConverter().Identify({
+      input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
+      input1: ["TENSOR_QUANT8_ASYMM", 1.0, 100],
+      output0: ["TENSOR_QUANT8_ASYMM", 2.0, 80],
+  })
+
+  Example({
+      input0: input0_data,
+      input1: input1_data,
+      output0: output_data,
+  }, model=model, name=name).AddVariations("relaxed", "float16", "int32", quant8)
+
+
+test(
+    name="simple",
+    input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
+    input1=Input("input1", "TENSOR_FLOAT32", "{3, 1, 2}"),
+    output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
+    input0_data=[1.0, 0.0, -1.0, 11.0, -2.0, -1.44],
+    input1_data=[-1.0, 0.0, 1.0, 12.0, -3.0, -1.43],
+    output_data=[-1.0, 0.0, -1.0, 11.0, -3.0, -1.44],
+)
+
+test(
+    name="broadcast",
+    input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"),
+    input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
+    output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"),
+    input0_data=[1.0, 0.0, -1.0, -2.0, -1.44, 11.0],
+    input1_data=[0.5, 2.0],
+    output_data=[0.5, 0.0, -1.0, -2.0, -1.44, 2.0],
+)
+
+
+# Test overflow and underflow.
+input0 = Input("input0", "TENSOR_QUANT8_ASYMM", "{2}, 1.0f, 128")
+input1 = Input("input1", "TENSOR_QUANT8_ASYMM", "{2}, 1.0f, 128")
+output0 = Output("output0", "TENSOR_QUANT8_ASYMM", "{2}, 0.5f, 128")
+model = Model().Operation("MINIMUM", input0, input1).To(output0)
+
+Example({
+    input0: [60, 128],
+    input1: [128, 200],
+    output0: [0, 128],
+}, model=model, name="overflow")