diff options
Diffstat (limited to 'externals/nnapi_test_generator/tests')
34 files changed, 0 insertions, 1245 deletions
diff --git a/externals/nnapi_test_generator/tests/P_conv/conv_1_h3_w2_SAME.mod.py b/externals/nnapi_test_generator/tests/P_conv/conv_1_h3_w2_SAME.mod.py deleted file mode 100644 index 8e93749e2..000000000 --- a/externals/nnapi_test_generator/tests/P_conv/conv_1_h3_w2_SAME.mod.py +++ /dev/null @@ -1,11 +0,0 @@ -i4 = Int32Scalar("b4", 1) -i5 = Int32Scalar("b5", 1) -i6 = Int32Scalar("b6", 1) -i7 = Int32Scalar("b7", 0) -i2 = Input("op2", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # input 0 -i3 = Output("op3", "TENSOR_FLOAT32", "{1, 8, 8, 1}") # output 0 -i0 = Parameter("op0", "TENSOR_FLOAT32", "{1, 3, 2, 3}", [-0.966213, -0.467474, -0.82203, -0.579455, 0.0278809, -0.79946, -0.684259, 0.563238, 0.37289, 0.738216, 0.386045, -0.917775, 0.184325, -0.270568, 0.82236, 0.0973683, -0.941308, -0.144706]) # parameters -i1 = Parameter("op1", "TENSOR_FLOAT32", "{1}", [0]) # parameters -model = Model() -model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3) - diff --git a/externals/nnapi_test_generator/tests/P_conv/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_conv/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_conv/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_conv/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_conv/stdout.txt.expect deleted file mode 100644 index 47d92b6b8..000000000 --- a/externals/nnapi_test_generator/tests/P_conv/stdout.txt.expect +++ /dev/null @@ -1,41 +0,0 @@ -// Generated file (from: conv_1_h3_w2_SAME.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type0(Type::INT32, {}); - OperandType type3(Type::TENSOR_FLOAT32, {1, 3, 2, 3}); - OperandType type2(Type::TENSOR_FLOAT32, {1, 8, 8, 1}); - OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); - OperandType type4(Type::TENSOR_FLOAT32, {1}); - // Phase 1, operands - auto b4 = model->addOperand(&type0); - auto b5 = model->addOperand(&type0); - auto b6 = model->addOperand(&type0); - auto b7 = model->addOperand(&type0); - auto op2 = model->addOperand(&type1); - auto op3 = model->addOperand(&type2); - auto op0 = model->addOperand(&type3); - auto op1 = model->addOperand(&type4); - // Phase 2, operations - static int32_t b4_init[] = {1}; - model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); - static int32_t b5_init[] = {1}; - model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); - static int32_t b6_init[] = {1}; - model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); - static int32_t b7_init[] = {0}; - model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); - static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f, -0.579455f, 0.0278809f, -0.79946f, -0.684259f, 0.563238f, 0.37289f, 0.738216f, 0.386045f, -0.917775f, 0.184325f, -0.270568f, 0.82236f, 0.0973683f, -0.941308f, -0.144706f}; - model->setOperandValue(op0, op0_init, sizeof(float) * 18); - static float op1_init[] = {0.0f}; - model->setOperandValue(op1, op1_init, sizeof(float) * 1); - model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {op2}, - {op3}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} diff --git a/externals/nnapi_test_generator/tests/P_depthwise_conv/depthwise_conv.bin.mod.py b/externals/nnapi_test_generator/tests/P_depthwise_conv/depthwise_conv.bin.mod.py deleted file mode 100644 index 8738ee01b..000000000 --- a/externals/nnapi_test_generator/tests/P_depthwise_conv/depthwise_conv.bin.mod.py +++ /dev/null @@ -1,11 +0,0 @@ -model = Model() -i4 = Int32Scalar("b4", 1) -i5 = Int32Scalar("b5", 1) -i6 = Int32Scalar("b6", 1) -i7 = Int32Scalar("b7", 1) -i8 = Int32Scalar("b8", 0) -i2 = Input("op2", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # input 0 -i3 = Output("op3", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # output 0 -i0 = Parameter("op0", "TENSOR_FLOAT32", "{1, 1, 1, 3}", [-0.966213, -0.467474, -0.82203]) # parameters -i1 = Parameter("op1", "TENSOR_FLOAT32", "{3}", [0, 0, 0]) # parameters -model = model.DepthWiseConv(i2, i0, i1, i4, i5, i6, i7, i8).To(i3) diff --git a/externals/nnapi_test_generator/tests/P_depthwise_conv/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_depthwise_conv/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_depthwise_conv/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_depthwise_conv/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_depthwise_conv/stdout.txt.expect deleted file mode 100644 index 9a22cc3e3..000000000 --- a/externals/nnapi_test_generator/tests/P_depthwise_conv/stdout.txt.expect +++ /dev/null @@ -1,43 +0,0 @@ -// Generated file (from: depthwise_conv.bin.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type0(Type::INT32, {}); - OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3}); - OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); - OperandType type3(Type::TENSOR_FLOAT32, {3}); - // Phase 1, operands - auto b4 = model->addOperand(&type0); - auto b5 = model->addOperand(&type0); - auto b6 = model->addOperand(&type0); - auto b7 = model->addOperand(&type0); - auto b8 = model->addOperand(&type0); - auto op2 = model->addOperand(&type1); - auto op3 = model->addOperand(&type1); - auto op0 = model->addOperand(&type2); - auto op1 = model->addOperand(&type3); - // Phase 2, operations - static int32_t b4_init[] = {1}; - model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); - static int32_t b5_init[] = {1}; - model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); - static int32_t b6_init[] = {1}; - model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); - static int32_t b7_init[] = {1}; - model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); - static int32_t b8_init[] = {0}; - model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1); - static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f}; - model->setOperandValue(op0, op0_init, sizeof(float) * 3); - static float op1_init[] = {0.0f, 0.0f, 0.0f}; - model->setOperandValue(op1, op1_init, sizeof(float) * 3); - model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {op2}, - {op3}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} diff --git a/externals/nnapi_test_generator/tests/P_explicit/explicit_add.mod.py b/externals/nnapi_test_generator/tests/P_explicit/explicit_add.mod.py deleted file mode 100644 index b1c8f99a4..000000000 --- a/externals/nnapi_test_generator/tests/P_explicit/explicit_add.mod.py +++ /dev/null @@ -1,7 +0,0 @@ -i1 = Input("op1", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # input 0 -i2 = Output("op2", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # output 0 -i0 = Internal("op0", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # intermediate result -model = Model() -model = model.RawAdd(i1, i1).To(i0) -model = model.RawAdd(i0, i1).To(i2) - diff --git a/externals/nnapi_test_generator/tests/P_explicit/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_explicit/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_explicit/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_explicit/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_explicit/stdout.txt.expect deleted file mode 100644 index 1221b7bda..000000000 --- a/externals/nnapi_test_generator/tests/P_explicit/stdout.txt.expect +++ /dev/null @@ -1,21 +0,0 @@ -// Generated file (from: explicit_add.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type0(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); - // Phase 1, operands - auto op1 = model->addOperand(&type0); - auto op2 = model->addOperand(&type0); - auto op0 = model->addOperand(&type0); - // Phase 2, operations - model->addOperation(ANEURALNETWORKS_ADD, {op1, op1}, {op0}); - model->addOperation(ANEURALNETWORKS_ADD, {op0, op1}, {op2}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {op1}, - {op2}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} diff --git a/externals/nnapi_test_generator/tests/P_float/addfloat.mod.py b/externals/nnapi_test_generator/tests/P_float/addfloat.mod.py deleted file mode 100644 index f0e4f0430..000000000 --- a/externals/nnapi_test_generator/tests/P_float/addfloat.mod.py +++ /dev/null @@ -1,8 +0,0 @@ -# model -i1 = Input("operand1","TENSOR_FLOAT32", "{3,4}") -i2 = Input("operand2","TENSOR_FLOAT32", "{3,4}") -i3 = Input("operand3","TENSOR_FLOAT32", "{3,4}") -o = Output("operand4","TENSOR_FLOAT32", "{3,4}") - -Model().Add(i1, i2).Add(i3).Out(o) - diff --git a/externals/nnapi_test_generator/tests/P_float/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_float/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_float/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_float/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_float/stdout.txt.expect deleted file mode 100644 index eb8cc146b..000000000 --- a/externals/nnapi_test_generator/tests/P_float/stdout.txt.expect +++ /dev/null @@ -1,23 +0,0 @@ -// Generated file (from: addfloat.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type0(Type::TENSOR_FLOAT32, {3,4}); - // Phase 1, operands - auto operand1 = model->addOperand(&type0); - auto operand2 = model->addOperand(&type0); - auto operand3 = model->addOperand(&type0); - auto operand4 = model->addOperand(&type0); - auto tmp4 = model->addOperand(&type0); - // Phase 2, operations - model->addOperation(ANEURALNETWORKS_ADD, {operand1, operand2}, {tmp4}); - model->addOperation(ANEURALNETWORKS_ADD, {operand3, tmp4}, {operand4}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {operand1, operand2, operand3}, - {operand4}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} diff --git a/externals/nnapi_test_generator/tests/P_full/addfloat.mod.py b/externals/nnapi_test_generator/tests/P_full/addfloat.mod.py deleted file mode 100644 index dbe7701a1..000000000 --- a/externals/nnapi_test_generator/tests/P_full/addfloat.mod.py +++ /dev/null @@ -1,22 +0,0 @@ -# model -model = Model() -i1 = Input("op1", "TENSOR_FLOAT32", "{2}") # a vector of 2 float32s -i2 = Input("op2", "TENSOR_FLOAT32", "{2}") # another vector of 2 float32s -b0 = Int32Scalar("b0", 0) # an int32_t scalar bias -i3 = Output("op3", "TENSOR_FLOAT32", "{2}") -model = model.Operation("ADD", i1, i2, b0).To(i3) - -# Example 1. Input in operand 0, -input0 = {i1: # input 0 - [1.0, 2.0], - i2: # input 1 - [3.0, 4.0]} - -output0 = {i3: # output 0 - [4.0, 6.0]} - -# Instantiate an example -Example((input0, output0)) - - - diff --git a/externals/nnapi_test_generator/tests/P_full/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_full/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_full/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_full/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_full/stdout.txt.expect deleted file mode 100644 index e3d2af3fa..000000000 --- a/externals/nnapi_test_generator/tests/P_full/stdout.txt.expect +++ /dev/null @@ -1,46 +0,0 @@ -// Generated file (from: addfloat.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type1(Type::INT32, {}); - OperandType type0(Type::TENSOR_FLOAT32, {2}); - // Phase 1, operands - auto op1 = model->addOperand(&type0); - auto op2 = model->addOperand(&type0); - auto b0 = model->addOperand(&type1); - auto op3 = model->addOperand(&type0); - // Phase 2, operations - static int32_t b0_init[] = {0}; - model->setOperandValue(b0, b0_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_ADD, {op1, op2, b0}, {op3}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {op1, op2}, - {op3}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} -// Generated file (from: addfloat.mod.py). Do not edit -// Begin of an example -{ -//Input(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {{0, {1.0f, 2.0f}}, {1, {3.0f, 4.0f}}}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {} -}, -//Output(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {{0, {4.0f, 6.0f}}}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {} -} -}, // End of an example diff --git a/externals/nnapi_test_generator/tests/P_lstm/lstm.mod.py b/externals/nnapi_test_generator/tests/P_lstm/lstm.mod.py deleted file mode 100644 index cb1bf6010..000000000 --- a/externals/nnapi_test_generator/tests/P_lstm/lstm.mod.py +++ /dev/null @@ -1,161 +0,0 @@ -# -# 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. -# - -# LSTM Test: No Cifg, No Peephole, No Projection, and No Clipping. - -model = Model() - -n_batch = 1 -n_input = 2 -# n_cell and n_output have the same size when there is no projection. -n_cell = 4 -n_output = 4 - -input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input)) - -input_to_input_weights = Input("input_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_input)) -input_to_forget_weights = Input("input_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_input)) -input_to_cell_weights = Input("input_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_input)) -input_to_output_weights = Input("input_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_input)) - -recurrent_to_input_weights = Input("recurrent_to_intput_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output)) -recurrent_to_forget_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output)) -recurrent_to_cell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output)) -recurrent_to_output_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output)) - -cell_to_input_weights = Input("cell_to_input_weights", "TENSOR_FLOAT32", "{0}") -cell_to_forget_weights = Input("cell_to_forget_weights", "TENSOR_FLOAT32", "{0}") -cell_to_output_weights = Input("cell_to_output_weights", "TENSOR_FLOAT32", "{0}") - -input_gate_bias = Input("input_gate_bias", "TENSOR_FLOAT32", "{%d}"%(n_cell)) -forget_gate_bias = Input("forget_gate_bias", "TENSOR_FLOAT32", "{%d}"%(n_cell)) -cell_gate_bias = Input("cell_gate_bias", "TENSOR_FLOAT32", "{%d}"%(n_cell)) -output_gate_bias = Input("output_gate_bias", "TENSOR_FLOAT32", "{%d}"%(n_cell)) - -projection_weights = Input("projection_weights", "TENSOR_FLOAT32", "{0,0}") -projection_bias = Input("projection_bias", "TENSOR_FLOAT32", "{0}") - -output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) -cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) - -activation_param = Input("activation_param", "TENSOR_INT32", "{1}") -cell_clip_param = Input("cell_clip_param", "TENSOR_FLOAT32", "{1}") -proj_clip_param = Input("proj_clip_param", "TENSOR_FLOAT32", "{1}") - -scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell * 4))) -output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) -cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell)) -output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output)) - -model = model.Operation("LSTM", - input, - - input_to_input_weights, - input_to_forget_weights, - input_to_cell_weights, - input_to_output_weights, - - recurrent_to_input_weights, - recurrent_to_forget_weights, - recurrent_to_cell_weights, - recurrent_to_output_weights, - - cell_to_input_weights, - cell_to_forget_weights, - cell_to_output_weights, - - input_gate_bias, - forget_gate_bias, - cell_gate_bias, - output_gate_bias, - - projection_weights, - projection_bias, - - output_state_in, - cell_state_in, - - activation_param, - cell_clip_param, - proj_clip_param -).To([scratch_buffer, output_state_out, cell_state_out, output]) - -# Example 1. Input in operand 0, -input0 = {input_to_input_weights: [-0.45018822, -0.02338299, -0.0870589, -0.34550029, 0.04266912, -0.15680569, -0.34856534, 0.43890524], - input_to_forget_weights: [0.09701663, 0.20334584, -0.50592935, -0.31343272, -0.40032279, 0.44781327, 0.01387155, -0.35593212], - input_to_cell_weights: [-0.50013041, 0.1370284, 0.11810488, 0.2013163, -0.20583314, 0.44344562, 0.22077113, -0.29909778], - input_to_output_weights: [-0.25065863, -0.28290087, 0.04613829, 0.40525138, 0.44272184, 0.03897077, -0.1556896, 0.19487578], - - input_gate_bias: [0.,0.,0.,0.], - forget_gate_bias: [1.,1.,1.,1.], - cell_gate_bias: [0.,0.,0.,0.], - output_gate_bias: [0.,0.,0.,0.], - - recurrent_to_input_weights: [ - -0.0063535, -0.2042388, 0.31454784, -0.35746509, 0.28902304, 0.08183324, - -0.16555229, 0.02286911, -0.13566875, 0.03034258, 0.48091322, - -0.12528998, 0.24077177, -0.51332325, -0.33502164, 0.10629296], - - recurrent_to_cell_weights: [ - -0.3407414, 0.24443203, -0.2078532, 0.26320225, 0.05695659, -0.00123841, - -0.4744786, -0.35869038, -0.06418842, -0.13502428, -0.501764, 0.22830659, - -0.46367589, 0.26016325, -0.03894562, -0.16368064], - - recurrent_to_forget_weights: [ - -0.48684245, -0.06655136, 0.42224967, 0.2112639, 0.27654213, 0.20864892, - -0.07646349, 0.45877004, 0.00141793, -0.14609534, 0.36447752, 0.09196436, - 0.28053468, 0.01560611, -0.20127171, -0.01140004], - - recurrent_to_output_weights: [ - 0.43385774, -0.17194885, 0.2718237, 0.09215671, 0.24107647, -0.39835793, - 0.18212086, 0.01301402, 0.48572797, -0.50656658, 0.20047462, -0.20607421, - -0.51818722, -0.15390486, 0.0468148, 0.39922136], - - cell_to_input_weights: [], - cell_to_forget_weights: [], - cell_to_output_weights: [], - - projection_weights: [], - projection_bias: [], - - activation_param: [4], # Tanh - cell_clip_param: [0.], - proj_clip_param: [0.], -} - -# Instantiate examples -# TODO: Add more examples after fixing the reference issue -test_inputs = [ - [2., 3.], -# [3., 4.],[1., 1.] -] -golden_outputs = [ - [-0.02973187, 0.1229473, 0.20885126, -0.15358765,], -# [-0.03716109, 0.12507336, 0.41193449, -0.20860538], -# [-0.15053082, 0.09120187, 0.24278517, -0.12222792] -] - -for (input_tensor, output_tensor) in zip(test_inputs, golden_outputs): - output0 = { - scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ], - cell_state_out: [ 0 for x in range(n_batch * n_cell) ], - output_state_out: [ 0 for x in range(n_batch * n_output) ], - output: output_tensor - } - input0[input] = input_tensor - input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ] - input0[cell_state_in] = [ 0 for _ in range(n_batch * n_cell) ] - Example((input0, output0)) diff --git a/externals/nnapi_test_generator/tests/P_lstm/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_lstm/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_lstm/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_lstm/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_lstm/stdout.txt.expect deleted file mode 100644 index 2ba320d77..000000000 --- a/externals/nnapi_test_generator/tests/P_lstm/stdout.txt.expect +++ /dev/null @@ -1,75 +0,0 @@ -// Generated file (from: lstm.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type5(Type::TENSOR_FLOAT32, {0,0}); - OperandType type3(Type::TENSOR_FLOAT32, {0}); - OperandType type9(Type::TENSOR_FLOAT32, {1, 16}); - OperandType type0(Type::TENSOR_FLOAT32, {1, 2}); - OperandType type6(Type::TENSOR_FLOAT32, {1, 4}); - OperandType type8(Type::TENSOR_FLOAT32, {1}); - OperandType type1(Type::TENSOR_FLOAT32, {4, 2}); - OperandType type2(Type::TENSOR_FLOAT32, {4, 4}); - OperandType type4(Type::TENSOR_FLOAT32, {4}); - OperandType type7(Type::TENSOR_INT32, {1}); - // Phase 1, operands - auto input = model->addOperand(&type0); - auto input_to_input_weights = model->addOperand(&type1); - auto input_to_forget_weights = model->addOperand(&type1); - auto input_to_cell_weights = model->addOperand(&type1); - auto input_to_output_weights = model->addOperand(&type1); - auto recurrent_to_intput_weights = model->addOperand(&type2); - auto recurrent_to_forget_weights = model->addOperand(&type2); - auto recurrent_to_cell_weights = model->addOperand(&type2); - auto recurrent_to_output_weights = model->addOperand(&type2); - auto cell_to_input_weights = model->addOperand(&type3); - auto cell_to_forget_weights = model->addOperand(&type3); - auto cell_to_output_weights = model->addOperand(&type3); - auto input_gate_bias = model->addOperand(&type4); - auto forget_gate_bias = model->addOperand(&type4); - auto cell_gate_bias = model->addOperand(&type4); - auto output_gate_bias = model->addOperand(&type4); - auto projection_weights = model->addOperand(&type5); - auto projection_bias = model->addOperand(&type3); - auto output_state_in = model->addOperand(&type6); - auto cell_state_in = model->addOperand(&type6); - auto activation_param = model->addOperand(&type7); - auto cell_clip_param = model->addOperand(&type8); - auto proj_clip_param = model->addOperand(&type8); - auto scratch_buffer = model->addOperand(&type9); - auto output_state_out = model->addOperand(&type6); - auto cell_state_out = model->addOperand(&type6); - auto output = model->addOperand(&type6); - // Phase 2, operations - model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, - {scratch_buffer, output_state_out, cell_state_out, output}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {1, 2, 0}; - return ignore.find(i) != ignore.end(); -} -// Generated file (from: lstm.mod.py). Do not edit -// Begin of an example -{ -//Input(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {{0, {2.0f, 3.0f}}, {1, {-0.45018822f, -0.02338299f, -0.0870589f, -0.34550029f, 0.04266912f, -0.15680569f, -0.34856534f, 0.43890524f}}, {2, {0.09701663f, 0.20334584f, -0.50592935f, -0.31343272f, -0.40032279f, 0.44781327f, 0.01387155f, -0.35593212f}}, {3, {-0.50013041f, 0.1370284f, 0.11810488f, 0.2013163f, -0.20583314f, 0.44344562f, 0.22077113f, -0.29909778f}}, {4, {-0.25065863f, -0.28290087f, 0.04613829f, 0.40525138f, 0.44272184f, 0.03897077f, -0.1556896f, 0.19487578f}}, {5, {-0.0063535f, -0.2042388f, 0.31454784f, -0.35746509f, 0.28902304f, 0.08183324f, -0.16555229f, 0.02286911f, -0.13566875f, 0.03034258f, 0.48091322f, -0.12528998f, 0.24077177f, -0.51332325f, -0.33502164f, 0.10629296f}}, {6, {-0.48684245f, -0.06655136f, 0.42224967f, 0.2112639f, 0.27654213f, 0.20864892f, -0.07646349f, 0.45877004f, 0.00141793f, -0.14609534f, 0.36447752f, 0.09196436f, 0.28053468f, 0.01560611f, -0.20127171f, -0.01140004f}}, {7, {-0.3407414f, 0.24443203f, -0.2078532f, 0.26320225f, 0.05695659f, -0.00123841f, -0.4744786f, -0.35869038f, -0.06418842f, -0.13502428f, -0.501764f, 0.22830659f, -0.46367589f, 0.26016325f, -0.03894562f, -0.16368064f}}, {8, {0.43385774f, -0.17194885f, 0.2718237f, 0.09215671f, 0.24107647f, -0.39835793f, 0.18212086f, 0.01301402f, 0.48572797f, -0.50656658f, 0.20047462f, -0.20607421f, -0.51818722f, -0.15390486f, 0.0468148f, 0.39922136f}}, {9, {}}, {10, {}}, {11, {}}, {12, {0.0f, 0.0f, 0.0f, 0.0f}}, {13, {1.0f, 1.0f, 1.0f, 1.0f}}, {14, {0.0f, 0.0f, 0.0f, 0.0f}}, {15, {0.0f, 0.0f, 0.0f, 0.0f}}, {16, {}}, {17, {}}, {18, {0, 0, 0, 0}}, {19, {0, 0, 0, 0}}, {21, {0.0f}}, {22, {0.0f}}}, - // int -> INT32 map - {{20, {4}}}, - // int -> QUANT8_ASYMM map - {} -}, -//Output(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {{1, {0, 0, 0, 0}}, {2, {0, 0, 0, 0}}, {3, {-0.02973187f, 0.1229473f, 0.20885126f, -0.15358765f}}, {0, {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {} -} -}, // End of an example diff --git a/externals/nnapi_test_generator/tests/P_quantized_avgpool/averpoolfloat.mod.py b/externals/nnapi_test_generator/tests/P_quantized_avgpool/averpoolfloat.mod.py deleted file mode 100644 index 17d6e0a4f..000000000 --- a/externals/nnapi_test_generator/tests/P_quantized_avgpool/averpoolfloat.mod.py +++ /dev/null @@ -1,20 +0,0 @@ -# model -model = Model() -i1 = Input("op1", "TENSOR_QUANT8_ASYMM", "0.0f, 127.5f, {1, 2, 2, 1}") -cons1 = Int32Scalar("cons1", 1) -act = Int32Scalar("act", 0) -o = Output("op3", "TENSOR_QUANT8_ASYMM", "0.0f, 127.5f, {1, 2, 2, 1}") -model = model.Operation("AVERAGE_POOL", i1, cons1, cons1, cons1, cons1, cons1, act).To(o) - -# Example 1. Input in operand 0, -input0 = {i1: # input 0 - [1, 2, 3, 4]} - -output0 = {o: # output 0 - [1, 2, 3, 4]} - -# Instantiate an example -Example((input0, output0)) - - - diff --git a/externals/nnapi_test_generator/tests/P_quantized_avgpool/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_quantized_avgpool/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_quantized_avgpool/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_quantized_avgpool/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_quantized_avgpool/stdout.txt.expect deleted file mode 100644 index b4632d34d..000000000 --- a/externals/nnapi_test_generator/tests/P_quantized_avgpool/stdout.txt.expect +++ /dev/null @@ -1,48 +0,0 @@ -// Generated file (from: averpoolfloat.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type1(Type::INT32, {}); - OperandType type0(Type::TENSOR_QUANT8_ASYMM, 0.0f, 127.5f, {1, 2, 2, 1}); - // Phase 1, operands - auto op1 = model->addOperand(&type0); - auto cons1 = model->addOperand(&type1); - auto act = model->addOperand(&type1); - auto op3 = model->addOperand(&type0); - // Phase 2, operations - static int32_t cons1_init[] = {1}; - model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); - static int32_t act_init[] = {0}; - model->setOperandValue(act, act_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_AVERAGE_POOL, {op1, cons1, cons1, cons1, cons1, cons1, act}, {op3}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {op1}, - {op3}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} -// Generated file (from: averpoolfloat.mod.py). Do not edit -// Begin of an example -{ -//Input(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {{0, {1, 2, 3, 4}}} -}, -//Output(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {{0, {1, 2, 3, 4}}} -} -}, // End of an example diff --git a/externals/nnapi_test_generator/tests/P_quantized_conv/quantized.mod.py b/externals/nnapi_test_generator/tests/P_quantized_conv/quantized.mod.py deleted file mode 100644 index 7ef623513..000000000 --- a/externals/nnapi_test_generator/tests/P_quantized_conv/quantized.mod.py +++ /dev/null @@ -1,11 +0,0 @@ -i4 = Int32Scalar("b4", 2) -i5 = Int32Scalar("b5", 2) -i6 = Int32Scalar("b6", 2) -i7 = Int32Scalar("b7", 0) -i2 = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}") # input 0 -i3 = Output("op3", "TENSOR_QUANT8_ASYMM", "{1, 1, 1, 1}") # output 0 -i0 = Parameter("op0", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}", [1, 1, 1, 1]) # parameters -i1 = Parameter("op1", "TENSOR_INT32", "{1}", [0]) # parameters -model = Model() -model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3) - diff --git a/externals/nnapi_test_generator/tests/P_quantized_conv/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_quantized_conv/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_quantized_conv/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_quantized_conv/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_quantized_conv/stdout.txt.expect deleted file mode 100644 index 6b28bdd54..000000000 --- a/externals/nnapi_test_generator/tests/P_quantized_conv/stdout.txt.expect +++ /dev/null @@ -1,40 +0,0 @@ -// Generated file (from: quantized.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type0(Type::INT32, {}); - OperandType type3(Type::TENSOR_INT32, {1}); - OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 1}); - OperandType type1(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 1}); - // Phase 1, operands - auto b4 = model->addOperand(&type0); - auto b5 = model->addOperand(&type0); - auto b6 = model->addOperand(&type0); - auto b7 = model->addOperand(&type0); - auto op2 = model->addOperand(&type1); - auto op3 = model->addOperand(&type2); - auto op0 = model->addOperand(&type1); - auto op1 = model->addOperand(&type3); - // Phase 2, operations - static int32_t b4_init[] = {2}; - model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); - static int32_t b5_init[] = {2}; - model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); - static int32_t b6_init[] = {2}; - model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); - static int32_t b7_init[] = {0}; - model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); - static uint8_t op0_init[] = {1, 1, 1, 1}; - model->setOperandValue(op0, op0_init, sizeof(uint8_t) * 4); - static int32_t op1_init[] = {0}; - model->setOperandValue(op1, op1_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {op2}, - {op3}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} diff --git a/externals/nnapi_test_generator/tests/P_vts_full/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_vts_full/stderr.txt.expect deleted file mode 100644 index 3decb4c1c..000000000 --- a/externals/nnapi_test_generator/tests/P_vts_full/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output VTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_vts_full/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_vts_full/stdout.txt.expect deleted file mode 100644 index 14cd4f99d..000000000 --- a/externals/nnapi_test_generator/tests/P_vts_full/stdout.txt.expect +++ /dev/null @@ -1,93 +0,0 @@ -// Generated code. Do not edit -// Create the model -Model createTestModel() { - const std::vector<Operand> operands = { - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {1, 2, 2, 1}, - .numberOfConsumers = 1, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::MODEL_INPUT, - .location = {.poolIndex = 0, .offset = 0, .length = 0}, - }, - { - .type = OperandType::INT32, - .dimensions = {}, - .numberOfConsumers = 1, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::CONSTANT_COPY, - .location = {.poolIndex = 0, .offset = 0, .length = 4}, - }, - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {1, 2, 2, 1}, - .numberOfConsumers = 1, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::CONSTANT_COPY, - .location = {.poolIndex = 0, .offset = 4, .length = 16}, - }, - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {1, 2, 2, 1}, - .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::ADD, - .inputs = {0, 2, 1}, - .outputs = {3}, - } - }; - - const std::vector<uint32_t> inputIndexes = {0}; - const std::vector<uint32_t> outputIndexes = {3}; - std::vector<uint8_t> operandValues = { - 0, 0, 0, 0, 0, 0, 160, 64, 0, 0, 192, 64, 0, 0, 224, 64, 0, 0, 0, 65 - }; - const std::vector<hidl_memory> pools = {}; - - return { - .operands = operands, - .operations = operations, - .inputIndexes = inputIndexes, - .outputIndexes = outputIndexes, - .operandValues = operandValues, - .pools = pools, - }; -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} -// Generated file (from: vts_full.mod.py). Do not edit -// Begin of an example -{ -//Input(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {} -}, -//Output(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {{0, {6.0f, 8.0f, 10.0f, 12.0f}}}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {} -} -}, // End of an example diff --git a/externals/nnapi_test_generator/tests/P_vts_full/vts_full.mod.py b/externals/nnapi_test_generator/tests/P_vts_full/vts_full.mod.py deleted file mode 100644 index 4ad3b2e4b..000000000 --- a/externals/nnapi_test_generator/tests/P_vts_full/vts_full.mod.py +++ /dev/null @@ -1,19 +0,0 @@ -# Force VTS mode -Configuration.vts = True -# model -model = Model() -i0 = Input("operand0","TENSOR_FLOAT32", "{1, 2, 2, 1}") -b0 = Int32Scalar("b0", 0) -p0 = Parameter("p0", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [5.0, 6.0, 7.0, 8.0]) -o = Output("out","TENSOR_FLOAT32", "{1, 2, 2, 1}") - -model.Operation("ADD", i0, p0, b0).To(o) - -input0 = {i0: # input 0 - [1.0, 2.0, 3.0, 4.0]} - -output0 = {o: # output 0 - [6.0, 8.0, 10.0, 12.0]} - -# Instantiate an example -Example((input0, output0)) diff --git a/externals/nnapi_test_generator/tests/P_vts_operands/addfloat.mod.py b/externals/nnapi_test_generator/tests/P_vts_operands/addfloat.mod.py deleted file mode 100644 index 976cb35ec..000000000 --- a/externals/nnapi_test_generator/tests/P_vts_operands/addfloat.mod.py +++ /dev/null @@ -1,12 +0,0 @@ -# Force VTS mode -Configuration.vts = True -# model -i1 = Input("operand1","TENSOR_FLOAT32", "{3,4}") -i2 = Input("operand2","TENSOR_FLOAT32", "{3,4}") -i3 = Input("operand3","TENSOR_FLOAT32", "{3,4}") -Parameter("p1", "TENSOR_QUANT8_ASYMM", "{1, 2, 3}", [1, 2, 3, 4, 5, 6]) -Parameter("p2", "TENSOR_FLOAT32", "{}", [42.0]) -o = Output("operand4","TENSOR_FLOAT32", "{3,4}") - -Model().Add(i1, i2).Add(i3).Out(o) - diff --git a/externals/nnapi_test_generator/tests/P_vts_operands/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_vts_operands/stderr.txt.expect deleted file mode 100644 index 3decb4c1c..000000000 --- a/externals/nnapi_test_generator/tests/P_vts_operands/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output VTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_vts_operands/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_vts_operands/stdout.txt.expect deleted file mode 100644 index 2e74d1fc0..000000000 --- a/externals/nnapi_test_generator/tests/P_vts_operands/stdout.txt.expect +++ /dev/null @@ -1,103 +0,0 @@ -// Generated code. Do not edit -// Create the model -Model createTestModel() { - const std::vector<Operand> operands = { - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {3,4}, - .numberOfConsumers = 1, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::MODEL_INPUT, - .location = {.poolIndex = 0, .offset = 0, .length = 0}, - }, - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {3,4}, - .numberOfConsumers = 1, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::MODEL_INPUT, - .location = {.poolIndex = 0, .offset = 0, .length = 0}, - }, - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {3,4}, - .numberOfConsumers = 1, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::MODEL_INPUT, - .location = {.poolIndex = 0, .offset = 0, .length = 0}, - }, - { - .type = OperandType::TENSOR_QUANT8_ASYMM, - .dimensions = {1, 2, 3}, - .numberOfConsumers = 0, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::CONSTANT_COPY, - .location = {.poolIndex = 0, .offset = 0, .length = 6}, - }, - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {}, - .numberOfConsumers = 0, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::CONSTANT_COPY, - .location = {.poolIndex = 0, .offset = 6, .length = 4}, - }, - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {3,4}, - .numberOfConsumers = 0, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::MODEL_OUTPUT, - .location = {.poolIndex = 0, .offset = 0, .length = 0}, - }, - { - .type = OperandType::TENSOR_FLOAT32, - .dimensions = {3,4}, - .numberOfConsumers = 1, - .scale = 0.0f, - .zeroPoint = 0, - .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, - .location = {.poolIndex = 0, .offset = 0, .length = 0}, - } - }; - - const std::vector<Operation> operations = { - { - .type = OperationType::ADD, - .inputs = {0, 1}, - .outputs = {6}, - }, - { - .type = OperationType::ADD, - .inputs = {2, 6}, - .outputs = {5}, - } - }; - - const std::vector<uint32_t> inputIndexes = {0, 1, 2}; - const std::vector<uint32_t> outputIndexes = {5}; - std::vector<uint8_t> operandValues = { - 1, 2, 3, 4, 5, 6, 0, 0, 40, 66 - }; - const std::vector<hidl_memory> pools = {}; - - return { - .operands = operands, - .operations = operations, - .inputIndexes = inputIndexes, - .outputIndexes = outputIndexes, - .operandValues = operandValues, - .pools = pools, - }; -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} diff --git a/externals/nnapi_test_generator/tests/P_weird/stderr.txt.expect b/externals/nnapi_test_generator/tests/P_weird/stderr.txt.expect deleted file mode 100644 index c5a6e36b9..000000000 --- a/externals/nnapi_test_generator/tests/P_weird/stderr.txt.expect +++ /dev/null @@ -1,2 +0,0 @@ -Output CTS model: - -Output example:- diff --git a/externals/nnapi_test_generator/tests/P_weird/stdout.txt.expect b/externals/nnapi_test_generator/tests/P_weird/stdout.txt.expect deleted file mode 100644 index fa67d68ac..000000000 --- a/externals/nnapi_test_generator/tests/P_weird/stdout.txt.expect +++ /dev/null @@ -1,51 +0,0 @@ -// Generated file (from: weird_add.mod.py). Do not edit -void CreateModel(Model *model) { - OperandType type1(Type::INT32, {}); - OperandType type0(Type::TENSOR_FLOAT32, {2}); - // Phase 1, operands - auto op1 = model->addOperand(&type0); - auto op2 = model->addOperand(&type0); - auto b0 = model->addOperand(&type1); - auto tmp = model->addOperand(&type0); - auto tmp2 = model->addOperand(&type0); - auto op3 = model->addOperand(&type0); - auto op4 = model->addOperand(&type0); - // Phase 2, operations - static int32_t b0_init[] = {0}; - model->setOperandValue(b0, b0_init, sizeof(int32_t) * 1); - model->addOperation(ANEURALNETWORKS_ADD, {op1, op2, b0}, {tmp}); - model->addOperation(ANEURALNETWORKS_ADD, {tmp, op2, b0}, {tmp2}); - model->addOperation(ANEURALNETWORKS_ADD, {tmp2, op4, b0}, {op3}); - // Phase 3, inputs and outputs - model->identifyInputsAndOutputs( - {op1, op2, op4}, - {op3}); - assert(model->isValid()); -} - -bool is_ignored(int i) { - static std::set<int> ignore = {}; - return ignore.find(i) != ignore.end(); -} -// Generated file (from: weird_add.mod.py). Do not edit -// Begin of an example -{ -//Input(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {{0, {1.0f, 2.0f}}, {1, {3.0f, 4.0f}}, {2, {5.0f, 6.0f}}}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {} -}, -//Output(s) -{ // See tools/test_generator/include/TestHarness.h:MixedTyped - // int -> FLOAT32 map - {{0, {9.0f, 12.0f}}}, - // int -> INT32 map - {}, - // int -> QUANT8_ASYMM map - {} -} -}, // End of an example diff --git a/externals/nnapi_test_generator/tests/P_weird/weird_add.mod.py b/externals/nnapi_test_generator/tests/P_weird/weird_add.mod.py deleted file mode 100644 index a230267a4..000000000 --- a/externals/nnapi_test_generator/tests/P_weird/weird_add.mod.py +++ /dev/null @@ -1,29 +0,0 @@ -# model -model = Model() -i1 = Input("op1", "TENSOR_FLOAT32", "{2}") # a vector of 2 float32s -i2 = Input("op2", "TENSOR_FLOAT32", "{2}") # another vector of 2 float32s -b0 = Int32Scalar("b0", 0) # an int32_t scalar bias -tmp = Internal("tmp", "TENSOR_FLOAT32", "{2}") -tmp2 = Internal("tmp2", "TENSOR_FLOAT32", "{2}") -o3 = Output("op3", "TENSOR_FLOAT32", "{2}") -i4 = Input("op4", "TENSOR_FLOAT32", "{2}") # another vector of 2 float32s -model = model.Operation("ADD", i1, i2, b0).To(tmp) -model = model.Operation("ADD", tmp, i2, b0).To(tmp2) -model = model.Operation("ADD", tmp2, i4, b0).To(o3) - -# Example 1. Input in operand 0, -input0 = {i1: # input 0 - [1.0, 2.0], - i2: # input 1 - [3.0, 4.0], - i4: # input 4 - [5.0, 6.0]} - -output0 = {o3: # output 0 - [9.0, 12.0]} - -# Instantiate an example -Example((input0, output0)) - - - diff --git a/externals/nnapi_test_generator/tests/test.py b/externals/nnapi_test_generator/tests/test.py deleted file mode 100755 index c987cf680..000000000 --- a/externals/nnapi_test_generator/tests/test.py +++ /dev/null @@ -1,328 +0,0 @@ -#!/usr/bin/python3 - -# Copyright 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. - - -"""NN Model Test Compiler Test. - -Runs subdirectories of tests for the test generator/compiler. -""" - -import filecmp -import glob -import os -import re -import shutil -import subprocess -import sys -import unittest - - -__author__ = 'Android' - - -DOTTED_LINE = '................' - -class OrigFile: - OrigDir = None - -class TestGeneratorTests(unittest.TestCase): - """Class to contain all the unittest test cases. - - Tests will be dynamically added to this class as methods. - No static tests, so this class is initially empty. - - """ - pass - - -def GenerateTests(dir_name): - """Creates a test method that can be added as method to GenerateTests.""" - cwd = os.getcwd() - def Test(self): - os.chdir(cwd) - ExecTest(dir_name, self) - return Test - - -def AddUnitTests(test_dirs): - """Adds a test to Tests for each directory in test_dirs.""" - - for t in test_dirs: - # Must start with 'test_' according to unittest - test_name = 'test_%s' % t - test = GenerateTests(t) - # Add test as method to TestGeneratorTests with test_name as method name - setattr(TestGeneratorTests, test_name, test) - - -class Options(object): - verbose = 0 - cleanup = 1 - update_cts = 0 - zero_return = 0 - - -def CompareFiles(actual, expect): - """Compares actual and expect for equality.""" - if not os.path.isfile(actual): - if Options.verbose: - print ('Could not find %s' % actual) - return False - if not os.path.isfile(expect): - if Options.verbose: - print ('Could not find %s' % expect) - return False - - return filecmp.cmp(actual, expect, False) - - -def CopyIfDifferent(src, dst): - """Updates dst if it is different from src.""" - if not CompareFiles(src, dst): - if Options.verbose: - print ('Copying from %s to %s' % (src, dst)) - shutil.copyfile(src, dst) - - -def GetCommandLineArgs(filename): - """Extracts command line arguments from first comment line in a file.""" - f = open(filename, 'r') - line = f.readline() - f.close() - if line[0] == '/' and line[1] == '/': - return line[2:].strip() - else: - return '' - - -def ReadFileToStr(filename): - """Returns contents of file as a str.""" - with open(filename, 'r') as f: - return f.read() - - -def ReportIfDifferFromExpected(tests, name, file1, file2): - """Fails tests if file1 and file2 differ.""" - if not CompareFiles(file1, file2): - if Options.verbose: - err_message = ('%s is different:\n' - 'expected:\n%s\n%s%s\n\n' - 'actual:\n%s\n%s%s\n') % ( - name, - DOTTED_LINE, ReadFileToStr(file1), DOTTED_LINE, - DOTTED_LINE, ReadFileToStr(file2), DOTTED_LINE) - else: - err_message = '%s is different' % name - tests.fail(err_message) - - -def GetRSFiles(): - """Returns a list of files in cwd with extension '.rs' or '.fs'.""" - rs_files = glob.glob('*.mod.py') - rs_files.sort() - return rs_files - - -def GetOutDir(): - return os.path.abspath(os.path.join(OrigFile.OrigDir, "../")) - - -# Declare/define cache variable for GetOutDir to cache results -# This way we only need to call subprocesses once to get the directory -GetOutDir.cache = None - - -def CreateCmd(run_vts): - """Creates the test command to run for the current test.""" - cmd_string = ('%s/%s_generator.py' - ) % (GetOutDir(), "test" if not run_vts else "vts") - base_args = cmd_string.split() - rs_files = GetRSFiles() - - # Extra command line arguments can be placed as // comments at the start of - # any .rs file. We automatically bundle up all of these extra args and invoke - # llvm-rs-cc with them. - extra_args_str = '' - for rs_file in rs_files: - extra_args_str += GetCommandLineArgs(rs_file) - extra_args = extra_args_str.split() - - args = base_args + extra_args + rs_files - return args - -def Cleanup(): - """Cleans up the cwd of any tmp files created in current test.""" - try: - os.remove('stdout.txt') - os.remove('stderr.txt') - shutil.rmtree('tmp/') - except OSError: - pass - - -def CheckTestResult(dir_name, subprocess_ret, tests, args): - """Checks the result of the subprocess command to see if it passed/failed. - - If dir_name starts with 'F_', then subprocess is expected to fail. - If it instead succeeded, then this test is failed. - Vice versa with a dir_name starting with 'P_'. - - Args: - dir_name: name of current directory/test name - subprocess_ret: return code of subprocess - tests: unittest, call tests.fail(reason) when failure - args: the arguments for the command that was run - """ - if dir_name[0:2] == 'F_': - if subprocess_ret == 0: - if Options.verbose: - err_message = ('Command (%s) passed on invalid input\n' - 'stdout:\n%s\n%s%s\n') % ( - ' '.join(args), - DOTTED_LINE, ReadFileToStr('stdout.txt'), DOTTED_LINE - ) - else: - err_message = 'Command passed on invalid input' - tests.fail(err_message) - elif dir_name[0:2] == 'P_': - if subprocess_ret != 0: - if Options.verbose: - err_message = ('Command (%s) failed on valid input\n' - 'stderr:\n%s\n%s%s\n') % ( - ' '.join(args), - DOTTED_LINE, ReadFileToStr('stderr.txt'), DOTTED_LINE - ) - else: - err_message = 'Command failed on valid input' - tests.fail(err_message) - else: - tests.fail('Invalid test name: ' + dir_name + - ', should start with F_ or P_') - - - -def ExecTest(dir_name, tests): - """Executes an test generator test from dir_name.""" - - os.chdir(dir_name) - stdout_file = open('stdout.txt', 'w+') - stderr_file = open('stderr.txt', 'w+') - run_vts = (dir_name[2:5] == 'vts') - args = CreateCmd(run_vts) - - if Options.verbose > 1: - print ('Executing:', ' '.join(args)) - - # Execute the command and check the resulting shell return value. - # All tests that are expected to FAIL have directory names that - # start with 'F_'. Other tests that are expected to PASS have - # directory names that start with 'P_'. - ret = 0 - try: - ret = subprocess.call(args, stdout=stdout_file, stderr=stderr_file) - except OSError: - tests.fail('subprocess.call failed: ' + ' '.join(args)) - - stdout_file.close() - stderr_file.close() - - CheckTestResult(dir_name, ret, tests, args) - - ReportIfDifferFromExpected(tests, 'stdout', 'stdout.txt.expect', 'stdout.txt') - ReportIfDifferFromExpected(tests, 'stderr', 'stderr.txt.expect', 'stderr.txt') - - if Options.cleanup: - Cleanup() - - -def Usage(): - """Print out usage information.""" - print ('Usage: %s [OPTION]... [TESTNAME]...' - 'Renderscript Compiler Test Harness\n' - 'Runs TESTNAMEs (all tests by default)\n' - 'Available Options:\n' - ' -h, --help Help message\n' - ' -n, --no-cleanup Don\'t clean up after running tests\n' - ' -v, --verbose Verbose output. Enter multiple -v to get more verbose.\n' - ' -z, --zero-return Return 0 as exit code no matter if tests fail. Required for TreeHugger.\n' - ) % (sys.argv[0]), - return - - -def main(): - """Runs the unittest suite. - - Parses command line arguments, adds test directories as tests. - - Returns: - 0 if '-z' flag is set. - Else unittest.main() returns with its own error code. - """ - - OrigFile.OrigDir = os.path.dirname(os.path.abspath(__file__)) - # Chdir to the directory this file is in since tests are in this directory - os.chdir(OrigFile.OrigDir) - files = [] - for arg in sys.argv[1:]: - if arg in ('-h', '--help'): - Usage() - return 0 - elif arg in ('-n', '--no-cleanup'): - Options.cleanup = 0 - elif arg in ('-u', '--update-cts'): - Options.update_cts = 1 - elif arg in ('-v', '--verbose'): - Options.verbose += 1 - elif arg in ('-z', '--zero-return'): - Options.zero_return = 1 - else: - # Test list to run - if os.path.isdir(arg): - files.append(arg) - else: - print >> sys.stderr, 'Invalid test or option: %s' % arg - return 1 - - if not files: - file_names = os.listdir('.') - # Test names must start with 'F_' or 'P_' - # 'F_' tests are expected to fail - # 'P_' tests are expected to pass - for f in file_names: - if os.path.isdir(f) and (f[0:2] == 'F_' or f[0:2] == 'P_'): - files.append(f) - files.sort() - - AddUnitTests(files) - - # verbosity=2 is necessary for PythonUnitTestRunner to parse the results - # Otherwise verbosity does not matter - # If Options.zero_return is set, do not let unittest.main() exit - # This is necessary in TreeHugger to distinguish between failing tests and - # failing to execute the python script - # If Options.zero_return is not set, let unittest.main() exit - # In this case it will return a non-zero code if any tests fail - unittest_exit = Options.zero_return == 0 - unittest.main(verbosity=2, - argv=[sys.argv[0]] + ['TestGeneratorTests'], - exit=unittest_exit) - - return 0 - - -if __name__ == '__main__': - sys.exit(main()) - |