diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_2.cpp b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_2.cpp
index 8481b4d..872fc0b 100644
--- a/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_2.cpp
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_2.cpp
@@ -44,21 +44,6 @@
 // in frameworks/ml/nn/runtime/tests/generated/
 #include "vts/V1_2/all_generated_V1_2_vts_tests.cpp"
 
-// Generated from spec/strided_slice_invalid_output_dims.mod.py.
-// TODO(b/132155416): Make this part of all_generated_V1_2_vts_tests.cpp.
-namespace strided_slice_invalid_output_dims {
-#include "generated/strided_slice_invalid_output_dims.example.cpp"
-#include "generated/strided_slice_invalid_output_dims.model.cpp"
-}  // namespace strided_slice_invalid_output_dims
-
-// TODO(b/132155416): Make this part of all_generated_V1_2_vts_tests.cpp.
-TEST_F(ValidationTest, strided_slice_invalid_output_dims) {
-    const Model model = strided_slice_invalid_output_dims::createTestModel();
-    const std::vector<Request> requests =
-            createRequests(strided_slice_invalid_output_dims::get_examples());
-    validateFailure(model, requests);
-}
-
 }  // namespace functional
 }  // namespace vts
 }  // namespace V1_2
diff --git a/neuralnetworks/1.2/vts/functional/generated/strided_slice_invalid_output_dims.example.cpp b/neuralnetworks/1.2/vts/functional/generated/strided_slice_invalid_output_dims.example.cpp
deleted file mode 100644
index 0640833..0000000
--- a/neuralnetworks/1.2/vts/functional/generated/strided_slice_invalid_output_dims.example.cpp
+++ /dev/null
@@ -1,116 +0,0 @@
-// clang-format off
-// Generated file (from: strided_slice_invalid_output_dims.mod.py). Do not edit
-std::vector<MixedTypedExample>& get_examples() {
-static std::vector<MixedTypedExample> examples = {
-// Begin of an example
-{
-.operands = {
-//Input(s)
-{ // See tools/test_generator/include/TestHarness.h:MixedTyped
-  // int -> Dimensions map
-  .operandDimensions = {{0, {2, 3}}},
-  // int -> FLOAT32 map
-  .float32Operands = {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}}},
-  // int -> INT32 map
-  .int32Operands = {},
-  // int -> QUANT8_ASYMM map
-  .quant8AsymmOperands = {},
-  // int -> QUANT16_SYMM map
-  .quant16SymmOperands = {},
-  // int -> FLOAT16 map
-  .float16Operands = {},
-  // int -> BOOL8 map
-  .bool8Operands = {},
-  // int -> QUANT8_SYMM_PER_CHANNEL map
-  .quant8ChannelOperands = {},
-  // int -> QUANT16_ASYMM map
-  .quant16AsymmOperands = {},
-  // int -> QUANT8_SYMM map
-  .quant8SymmOperands = {},
-},
-//Output(s)
-{ // See tools/test_generator/include/TestHarness.h:MixedTyped
-  // int -> Dimensions map
-  .operandDimensions = {{0, {3}}},
-  // int -> FLOAT32 map
-  .float32Operands = {{0, {1.0f, 2.0f, 3.0f}}},
-  // int -> INT32 map
-  .int32Operands = {},
-  // int -> QUANT8_ASYMM map
-  .quant8AsymmOperands = {},
-  // int -> QUANT16_SYMM map
-  .quant16SymmOperands = {},
-  // int -> FLOAT16 map
-  .float16Operands = {},
-  // int -> BOOL8 map
-  .bool8Operands = {},
-  // int -> QUANT8_SYMM_PER_CHANNEL map
-  .quant8ChannelOperands = {},
-  // int -> QUANT16_ASYMM map
-  .quant16AsymmOperands = {},
-  // int -> QUANT8_SYMM map
-  .quant8SymmOperands = {},
-}
-},
-}, // End of an example
-};
-return examples;
-};
-
-std::vector<MixedTypedExample>& get_examples_dynamic_output_shape() {
-static std::vector<MixedTypedExample> examples_dynamic_output_shape = {
-// Begin of an example
-{
-.operands = {
-//Input(s)
-{ // See tools/test_generator/include/TestHarness.h:MixedTyped
-  // int -> Dimensions map
-  .operandDimensions = {{0, {2, 3}}},
-  // int -> FLOAT32 map
-  .float32Operands = {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}}},
-  // int -> INT32 map
-  .int32Operands = {},
-  // int -> QUANT8_ASYMM map
-  .quant8AsymmOperands = {},
-  // int -> QUANT16_SYMM map
-  .quant16SymmOperands = {},
-  // int -> FLOAT16 map
-  .float16Operands = {},
-  // int -> BOOL8 map
-  .bool8Operands = {},
-  // int -> QUANT8_SYMM_PER_CHANNEL map
-  .quant8ChannelOperands = {},
-  // int -> QUANT16_ASYMM map
-  .quant16AsymmOperands = {},
-  // int -> QUANT8_SYMM map
-  .quant8SymmOperands = {},
-},
-//Output(s)
-{ // See tools/test_generator/include/TestHarness.h:MixedTyped
-  // int -> Dimensions map
-  .operandDimensions = {{0, {3}}},
-  // int -> FLOAT32 map
-  .float32Operands = {{0, {1.0f, 2.0f, 3.0f}}},
-  // int -> INT32 map
-  .int32Operands = {},
-  // int -> QUANT8_ASYMM map
-  .quant8AsymmOperands = {},
-  // int -> QUANT16_SYMM map
-  .quant16SymmOperands = {},
-  // int -> FLOAT16 map
-  .float16Operands = {},
-  // int -> BOOL8 map
-  .bool8Operands = {},
-  // int -> QUANT8_SYMM_PER_CHANNEL map
-  .quant8ChannelOperands = {},
-  // int -> QUANT16_ASYMM map
-  .quant16AsymmOperands = {},
-  // int -> QUANT8_SYMM map
-  .quant8SymmOperands = {},
-}
-},
-}, // End of an example
-};
-return examples_dynamic_output_shape;
-};
-
diff --git a/neuralnetworks/1.2/vts/functional/generated/strided_slice_invalid_output_dims.model.cpp b/neuralnetworks/1.2/vts/functional/generated/strided_slice_invalid_output_dims.model.cpp
deleted file mode 100644
index 106655a..0000000
--- a/neuralnetworks/1.2/vts/functional/generated/strided_slice_invalid_output_dims.model.cpp
+++ /dev/null
@@ -1,216 +0,0 @@
-// clang-format off
-// Generated file (from: strided_slice_invalid_output_dims.mod.py). Do not edit
-// Create the model
-Model createTestModel() {
-    const std::vector<Operand> operands = {
-        {
-            .type = OperandType::TENSOR_FLOAT32,
-            .dimensions = {2, 3},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::MODEL_INPUT,
-            .location = {.poolIndex = 0, .offset = 0, .length = 0},
-        },
-        {
-            .type = OperandType::TENSOR_INT32,
-            .dimensions = {2},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 0, .length = 8},
-        },
-        {
-            .type = OperandType::TENSOR_INT32,
-            .dimensions = {2},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 8, .length = 8},
-        },
-        {
-            .type = OperandType::TENSOR_INT32,
-            .dimensions = {2},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 16, .length = 8},
-        },
-        {
-            .type = OperandType::INT32,
-            .dimensions = {},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 24, .length = 4},
-        },
-        {
-            .type = OperandType::INT32,
-            .dimensions = {},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 28, .length = 4},
-        },
-        {
-            .type = OperandType::INT32,
-            .dimensions = {},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 32, .length = 4},
-        },
-        {
-            .type = OperandType::TENSOR_FLOAT32,
-            .dimensions = {3},
-            .numberOfConsumers = 0,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::MODEL_OUTPUT,
-            .location = {.poolIndex = 0, .offset = 0, .length = 0},
-        }
-    };
-
-    const std::vector<Operation> operations = {
-        {
-            .type = OperationType::STRIDED_SLICE,
-            .inputs = {0, 1, 2, 3, 4, 5, 6},
-            .outputs = {7},
-        }
-    };
-
-    const std::vector<uint32_t> inputIndexes = {0};
-    const std::vector<uint32_t> outputIndexes = {7};
-    std::vector<uint8_t> operandValues = {
-      0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
-    };
-    const std::vector<hidl_memory> pools = {};
-
-    return {
-        .operands = operands,
-        .operations = operations,
-        .inputIndexes = inputIndexes,
-        .outputIndexes = outputIndexes,
-        .operandValues = operandValues,
-        .pools = pools,
-    };
-}
-
-inline bool is_ignored(int i) {
-  static std::set<int> ignore = {};
-  return ignore.find(i) != ignore.end();
-}
-
-// Create the model
-Model createTestModel_dynamic_output_shape() {
-    const std::vector<Operand> operands = {
-        {
-            .type = OperandType::TENSOR_FLOAT32,
-            .dimensions = {2, 3},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::MODEL_INPUT,
-            .location = {.poolIndex = 0, .offset = 0, .length = 0},
-        },
-        {
-            .type = OperandType::TENSOR_INT32,
-            .dimensions = {2},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 0, .length = 8},
-        },
-        {
-            .type = OperandType::TENSOR_INT32,
-            .dimensions = {2},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 8, .length = 8},
-        },
-        {
-            .type = OperandType::TENSOR_INT32,
-            .dimensions = {2},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 16, .length = 8},
-        },
-        {
-            .type = OperandType::INT32,
-            .dimensions = {},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 24, .length = 4},
-        },
-        {
-            .type = OperandType::INT32,
-            .dimensions = {},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 28, .length = 4},
-        },
-        {
-            .type = OperandType::INT32,
-            .dimensions = {},
-            .numberOfConsumers = 1,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::CONSTANT_COPY,
-            .location = {.poolIndex = 0, .offset = 32, .length = 4},
-        },
-        {
-            .type = OperandType::TENSOR_FLOAT32,
-            .dimensions = {0},
-            .numberOfConsumers = 0,
-            .scale = 0.0f,
-            .zeroPoint = 0,
-            .lifetime = OperandLifeTime::MODEL_OUTPUT,
-            .location = {.poolIndex = 0, .offset = 0, .length = 0},
-        }
-    };
-
-    const std::vector<Operation> operations = {
-        {
-            .type = OperationType::STRIDED_SLICE,
-            .inputs = {0, 1, 2, 3, 4, 5, 6},
-            .outputs = {7},
-        }
-    };
-
-    const std::vector<uint32_t> inputIndexes = {0};
-    const std::vector<uint32_t> outputIndexes = {7};
-    std::vector<uint8_t> operandValues = {
-      0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
-    };
-    const std::vector<hidl_memory> pools = {};
-
-    return {
-        .operands = operands,
-        .operations = operations,
-        .inputIndexes = inputIndexes,
-        .outputIndexes = outputIndexes,
-        .operandValues = operandValues,
-        .pools = pools,
-    };
-}
-
-inline bool is_ignored_dynamic_output_shape(int i) {
-  static std::set<int> ignore = {};
-  return ignore.find(i) != ignore.end();
-}
-
diff --git a/neuralnetworks/1.2/vts/functional/spec/strided_slice_invalid_output_dims.mod.py b/neuralnetworks/1.2/vts/functional/spec/strided_slice_invalid_output_dims.mod.py
deleted file mode 100644
index e8d30f3..0000000
--- a/neuralnetworks/1.2/vts/functional/spec/strided_slice_invalid_output_dims.mod.py
+++ /dev/null
@@ -1,43 +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.
-#
-
-# This test makes sure that executing STRIDED_SLICE results in a failure when
-# the output dimensions do not match shrinkAxisMask.
-#
-# The test generator does not support generating tests resulting in execution
-# failure, so the gTest part of this test has been written by hand.
-# TODO(b/132155416): Move this under frameworks/ml/nn/runtime/test/specs/V1_2.
-#
-# Based on strided_slice_float_11.mod.py.
-
-model = Model()
-i1 = Input("input", "TENSOR_FLOAT32", "{2, 3}")
-begins = Parameter("begins", "TENSOR_INT32", "{2}", [0, 0])
-# The value "2" below makes the test invalid. See http://b/79856511#comment2.
-ends = Parameter("ends", "TENSOR_INT32", "{2}", [2, 3])
-strides = Parameter("strides", "TENSOR_INT32", "{2}", [1, 1])
-beginMask = Int32Scalar("beginMask", 0)
-endMask = Int32Scalar("endMask", 0)
-shrinkAxisMask = Int32Scalar("shrinkAxisMask", 1)
-
-output = Output("output", "TENSOR_FLOAT32", "{3}")
-
-model = model.Operation("STRIDED_SLICE", i1, begins, ends, strides, beginMask, endMask, shrinkAxisMask).To(output)
-
-Example({
-    i1: [1, 2, 3, 4, 5, 6],
-    output: [1, 2, 3],
-})