1 files changed, 0 insertions, 146 deletions
diff --git a/tests/nnapi/specs/skip/V1_2/conv2d_dilation.mod.py b/tests/nnapi/specs/skip/V1_2/conv2d_dilation.mod.py
deleted file mode 100644
index e30e5ede8..000000000
--- a/tests/nnapi/specs/skip/V1_2/conv2d_dilation.mod.py
+++ /dev/null
@@ -1,146 +0,0 @@
-#
-# 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.
-#
-
-layout = BoolScalar("layout", False) # NHWC
-
-# TEST 1: dilation set to 1 (default)
-i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 1}")
-f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25])
-b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0])
-o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 1}")
-Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout, 1, 1).To(o1)
-
-# Additional data type
-quant8 = DataTypeConverter().Identify({
-    i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
-    f1: ("TENSOR_QUANT8_ASYMM", 0.125, 0),
-    b1: ("TENSOR_INT32", 0.0625, 0),
-    o1: ("TENSOR_QUANT8_ASYMM", 0.125, 0)
-})
-
-# Instantiate an example
-example = Example({
-    i1: [1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0],
-    o1: [.875, .875, .875, .875]
-}).AddNchw(i1, o1, layout).AddInput(f1, b1).AddVariations("relaxed", quant8, "float16")
-
-
-# TEST 2: dilation set to 3
-i2 = Input("op1", "TENSOR_FLOAT32", "{1, 9, 9, 1}")
-f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 2, 3, 4, 5, 6, 7, 8, 9])
-b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0])
-o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}")
-Model().Operation("CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 0, layout, 3, 3).To(o2)
-
-# Additional data type
-quant8 = DataTypeConverter().Identify({
-    i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
-    f2: ("TENSOR_QUANT8_ASYMM", 0.125, 0),
-    b2: ("TENSOR_INT32", 0.0625, 0),
-    o2: ("TENSOR_QUANT8_ASYMM", 0.125, 0)
-})
-
-# Instantiate an example
-example = Example({
-    i2: [0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 1, 1, 1, 0, 0, 0,
-         0, 0, 0, 1, 1, 1, 0, 0, 0,
-         0, 0, 0, 1, 1, 1, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0],
-    o2: [5, 5, 5, 5, 5, 5, 5, 5, 5]
-}).AddNchw(i2, o2, layout).AddInput(f2, b2).AddVariations("relaxed", quant8, "float16")
-
-# TEST 3: same as test 1 but with implicit VALID padding
-i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 1}")
-f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25])
-b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0])
-o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 1}")
-Model().Operation("CONV_2D", i1, f1, b1, 2, 1, 1, 0, layout, 1, 1).To(o1)
-
-# Additional data type
-quant8 = DataTypeConverter().Identify({
-    i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
-    f1: ("TENSOR_QUANT8_ASYMM", 0.125, 0),
-    b1: ("TENSOR_INT32", 0.0625, 0),
-    o1: ("TENSOR_QUANT8_ASYMM", 0.125, 0)
-})
-
-# Instantiate an example
-example = Example({
-    i1: [1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0],
-    o1: [.875, .875, .875, .875]
-}, name="valid_padding").AddNchw(i1, o1, layout).AddInput(f1, b1).AddVariations("relaxed", quant8, "float16")
-
-
-# TEST 4: same as test 2 but with implicit VALID padding
-i2 = Input("op1", "TENSOR_FLOAT32", "{1, 9, 9, 1}")
-f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 2, 3, 4, 5, 6, 7, 8, 9])
-b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0])
-o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}")
-Model().Operation("CONV_2D", i2, f2, b2, 2, 1, 1, 0, layout, 3, 3).To(o2)
-
-# Additional data type
-quant8 = DataTypeConverter().Identify({
-    i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
-    f2: ("TENSOR_QUANT8_ASYMM", 0.125, 0),
-    b2: ("TENSOR_INT32", 0.0625, 0),
-    o2: ("TENSOR_QUANT8_ASYMM", 0.125, 0)
-})
-
-# Instantiate an example
-example = Example({
-    i2: [0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 1, 1, 1, 0, 0, 0,
-         0, 0, 0, 1, 1, 1, 0, 0, 0,
-         0, 0, 0, 1, 1, 1, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0, 0, 0, 0],
-    o2: [5, 5, 5, 5, 5, 5, 5, 5, 5]
-}, name="valid_padding").AddNchw(i2, o2, layout).AddInput(f2, b2).AddVariations("relaxed", quant8, "float16")
-
-
-# TEST 5: dilation set to 3, SAME padding
-i3 = Input("op1", "TENSOR_FLOAT32", "{1, 6, 6, 1}")
-f3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4])
-b3 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0])
-o3 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}")
-Model().Operation("CONV_2D", i3, f3, b3, 1, 2, 2, 0, layout, 3, 3).To(o3)
-
-# Additional data type
-quant8 = DataTypeConverter().Identify({
-    i3: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
-    f3: ("TENSOR_QUANT8_ASYMM", 0.125, 0),
-    b3: ("TENSOR_INT32", 0.0625, 0),
-    o3: ("TENSOR_QUANT8_ASYMM", 0.125, 0)
-})
-
-# Instantiate an example
-example = Example({
-    i3: [0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0,
-         0, 0, 4, 3, 0, 0,
-         0, 0, 2, 1, 0, 0,
-         0, 0, 0, 0, 0, 0,
-         0, 0, 0, 0, 0, 0],
-    o3: [16, 0, 9, 0, 0, 0, 4, 0, 1]
-}).AddNchw(i3, o3, layout).AddInput(f3, b3).AddVariations("relaxed", quant8, "float16")