1 files changed, 0 insertions, 143 deletions
diff --git a/tests/nnapi/specs/skip/V1_2/dequantize_v1_2.mod.py b/tests/nnapi/specs/skip/V1_2/dequantize_v1_2.mod.py
deleted file mode 100644
index 81e3515cd..000000000
--- a/tests/nnapi/specs/skip/V1_2/dequantize_v1_2.mod.py
+++ /dev/null
@@ -1,143 +0,0 @@
-#
-# Copyright (C) 2019 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, output0, input0_data, output0_data):
-  model = Model().Operation("DEQUANTIZE", input0).To(output0)
-  example = Example({
-      input0: input0_data,
-      output0: output0_data,
-  },
-                    model=model,
-                    name=name).AddVariations("relaxed", "float16")
-
-
-test(
-    name="1d_quant8_asymm",
-    input0=Input("input0", "TENSOR_QUANT8_ASYMM", "{10}, 0.5, 127"),
-    output0=Output("output0", "TENSOR_FLOAT32", "{10}"),
-    input0_data=[0, 1, 2, 3, 4, 251, 252, 253, 254, 255],
-    output0_data=[-63.5, -63, -62.5, -62, -61.5, 62, 62.5, 63, 63.5, 64],
-)
-
-test(
-    name="2d_quant8_asymm",
-    input0=Input("input0", "TENSOR_QUANT8_ASYMM", "{2, 5}, 0.5, 127"),
-    output0=Output("output0", "TENSOR_FLOAT32", "{2, 5}"),
-    input0_data=[0, 1, 2, 3, 4, 251, 252, 253, 254, 255],
-    output0_data=[-63.5, -63, -62.5, -62, -61.5, 62, 62.5, 63, 63.5, 64],
-)
-
-test(
-    name="3d_quant8_symm",
-    input0=Input("input0", "TENSOR_QUANT8_SYMM", "{2, 2, 2}, 0.5, 0"),
-    output0=Output("output0", "TENSOR_FLOAT32", "{2, 2, 2}"),
-    input0_data=[-128, -127, -126, -125, 124, 125, 126, 127],
-    output0_data=[-64, -63.5, -63, -62.5, 62, 62.5, 63, 63.5],
-)
-
-test(
-    name="4d_quant8_symm",
-    input0=Input("input0", "TENSOR_QUANT8_SYMM", "{2, 1, 2, 2}, 0.5, 0"),
-    output0=Output("output0", "TENSOR_FLOAT32", "{2, 1, 2, 2}"),
-    input0_data=[-128, -127, -126, -125, 124, 125, 126, 127],
-    output0_data=[-64, -63.5, -63, -62.5, 62, 62.5, 63, 63.5],
-)
-
-test(
-    name="3d_per_channel_first_dim",
-    input0=Input(
-        "input0", ("TENSOR_QUANT8_SYMM_PER_CHANNEL", [2, 3, 4], 0, 0),
-        extraParams=SymmPerChannelQuantParams(channelDim=0, scales=[2., 0.5])),
-    output0=Output("output0", "TENSOR_FLOAT32", "{2, 3, 4}"),
-    input0_data=[
-        -128, -127, -126, -125, -124, -123, -122, -121, -120, -119, -118, -117,
-        116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127
-    ],
-    output0_data=[
-        -256, -254, -252, -250, -248, -246, -244, -242, -240, -238, -236, -234,
-        58., 58.5, 59., 59.5, 60., 60.5, 61., 61.5, 62., 62.5, 63., 63.5
-    ],
-)
-
-test(
-    name="3d_per_channel_second_dim",
-    input0=Input(
-        "input0", ("TENSOR_QUANT8_SYMM_PER_CHANNEL", [2, 3, 4], 0, 0),
-        extraParams=SymmPerChannelQuantParams(
-            channelDim=1, scales=[2., 1., 0.5])),
-    output0=Output("output0", "TENSOR_FLOAT32", "{2, 3, 4}"),
-    input0_data=[
-        -128, -127, -126, -125, -124, -123, -122, -121, -120, -119, -118, -117,
-        116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127
-    ],
-    output0_data=[
-        -256., -254., -252., -250., -124., -123., -122., -121., -60., -59.5,
-        -59., -58.5, 232., 234., 236., 238., 120., 121., 122., 123., 62., 62.5,
-        63., 63.5
-    ],
-)
-
-# DEQUANTIZE from TENSOR_QUANT8_ASYMM to TENSOR_FLOAT32 is introduced in V1_0.
-Example.SetVersion("V1_0", "dequantize_v1_2_1d_quant8_asymm", "dequantize_v1_2_2d_quant8_asymm")
-
-# FLOAT16
-model = Model()
-i1 = Input("op1",  "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 1.f, 0")
-i2 = Output("op2", "TENSOR_FLOAT16", "{1, 2, 2, 1}")
-model = model.Operation("DEQUANTIZE", i1).To(i2)
-
-# Example 1. Input in operand 0,
-input0 = {i1: # input 0
-          [0, 32, 128, 255]}
-
-output0 = {i2: # output 0
-           [0.0, 32.0, 128.0, 255.0]}
-
-# Instantiate an example
-Example((input0, output0))
-
-
-# Zero-sized input
-
-# Use BOX_WITH_NMS_LIMIT op to generate a zero-sized internal tensor for box cooridnates.
-p1 = Parameter("scores", "TENSOR_QUANT8_ASYMM", "{1, 2}, 0.1f, 128", [137, 129]) # scores
-p2 = Parameter("roi", "TENSOR_QUANT16_ASYMM", "{1, 8}, 0.125f, 0", [8, 8, 80, 80, 0, 0, 80, 80]) # roi
-o1 = Output("scoresOut", "TENSOR_QUANT8_ASYMM", "{0}, 0.1f, 128") # scores out
-o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out
-tmp1 = Internal("roiOut", "TENSOR_QUANT16_ASYMM", "{0, 4}, 0.125f, 0") # roi out
-tmp2 = Internal("batchSplitOut", "TENSOR_INT32", "{0}") # batch split out
-model = Model("zero_sized").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
-
-# Use ROI_ALIGN op to convert into zero-sized feature map.
-layout = BoolScalar("layout", False) # NHWC
-i1 = Input("in", "TENSOR_QUANT8_ASYMM", "{1, 1, 1, 1}, 0.1f, 128")
-zero_sized = Internal("featureMap", "TENSOR_QUANT8_ASYMM", "{0, 2, 2, 1}, 0.1f, 128")
-model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
-
-# DEQUANTIZE op with numBatches = 0.
-o3 = Output("out", "TENSOR_FLOAT32", "{0, 2, 2, 1}") # out
-model = model.Operation("DEQUANTIZE", zero_sized).To(o3)
-
-float16 = DataTypeConverter().Identify({o3: ("TENSOR_FLOAT16",)})
-
-# Create test case with dummy values.
-Example({
-    i1: [1],
-    o1: [0],
-    o2: [0],
-    o3: [0],
-}).AddVariations("relaxed", float16)