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Merged
Knight-X merged 5 commits into from
Dec 7, 2017
Merged

F/context cg ref #60

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0b884b6
context stateful wip
neil-tan Nov 30, 2017
5209e03
codeGenTemplate test passed
neil-tan Nov 30, 2017
66468d8
context lambda wip
neil-tan Dec 2, 2017
1f96bc2
context: add_static, addCached, push_static; context internal gc wip
neil-tan Dec 3, 2017
ae3a7a4
updated comment in context.cpp
neil-tan Dec 3, 2017
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42 changes: 21 additions & 21 deletions ArrayTests.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -15,22 +15,22 @@ class ArrayOpsTest : public Test {
testStart("quantize_v2");

//reference inputs /Users/neitan01/Documents/mbed/uTensor.git/TESTS/scripts/PRE-GEN/qA
S_TENSOR b_q_ref = ctx.add(t_import.float_import ("/fs/testData/qB/in/Cast_1_0.idx", "b_q_ref"));
S_TENSOR b_min_q_ref = ctx.add(t_import.float_import("/fs/testData/qB/in/Min_1_0.idx", "b_min_q_ref"));
S_TENSOR b_max_q_ref = ctx.add(t_import.float_import("/fs/testData/qB/in/Max_1_0.idx", "b_max_q_ref"));
S_TENSOR b_q_ref = ctx.addCached(hold(t_import.float_import ("/fs/testData/qB/in/Cast_1_0.idx")), "b_q_ref");
S_TENSOR b_min_q_ref = ctx.addCached(hold(t_import.float_import("/fs/testData/qB/in/Min_1_0.idx")), "b_min_q_ref");
S_TENSOR b_max_q_ref = ctx.addCached(hold(t_import.float_import("/fs/testData/qB/in/Max_1_0.idx")), "b_max_q_ref");

//reference outputs
S_TENSOR ref_b_q = ctx.add(t_import.ubyte_import("/fs/testData/qB/out/qB_0.idx", "ref_b_q"));
S_TENSOR ref_b_min_q = ctx.add(t_import.float_import("/fs/testData/qB/out/qB_1.idx", "ref_b_min_q"));
S_TENSOR ref_b_max_q = ctx.add(t_import.float_import("/fs/testData/qB/out/qb_2.idx", "ref_b_max_q"));
S_TENSOR ref_b_q = ctx.addCached(hold(t_import.ubyte_import("/fs/testData/qB/out/qB_0.idx")), "ref_b_q");
S_TENSOR ref_b_min_q = ctx.addCached(hold(t_import.float_import("/fs/testData/qB/out/qB_1.idx")), "ref_b_min_q");
S_TENSOR ref_b_max_q = ctx.addCached(hold(t_import.float_import("/fs/testData/qB/out/qb_2.idx")), "ref_b_max_q");

S_TENSOR out_b_q = ctx.add(new RamTensor<unsigned char>(b_q_ref->getShape(), "b_q"));
S_TENSOR out_b_min_q = ctx.add(new RamTensor<float>(b_min_q_ref->getShape(), "b_min_q"));
S_TENSOR out_b_max_q = ctx.add(new RamTensor<float>(b_max_q_ref->getShape(), "b_max_q"));
S_TENSOR out_b_q = ctx.addCached(hold(new RamTensor<unsigned char>(b_q_ref->getShape())), "b_q");
S_TENSOR out_b_min_q = ctx.addCached(hold(new RamTensor<float>(b_min_q_ref->getShape())), "b_min_q");
S_TENSOR out_b_max_q = ctx.addCached(hold(new RamTensor<float>(b_max_q_ref->getShape())), "b_max_q");

//Implementation goes here
timer_start();
ctx.push(new QuantizeV2Op(), {"b_q_ref", "b_min_q_ref", "b_max_q_ref"}, {"b_q", "b_min_q", "b_max_q"});
ctx.push_static(hold(new QuantizeV2Op()), "QuantizeV2Op", {"b_q_ref", "b_min_q_ref", "b_max_q_ref"}, {"b_q", "b_min_q", "b_max_q"});
ctx.eval();
timer_stop();

Expand All @@ -44,18 +44,18 @@ class ArrayOpsTest : public Test {
testStart("dequantize");

//reference inputs
S_TENSOR a = ctx.add(t_import.ubyte_import("/fs/testData/deQ/in/rQ_0.idx", "a"));
S_TENSOR a_min = ctx.add(t_import.float_import("/fs/testData/deQ/in/rQ_1.idx", "a_min"));
S_TENSOR a_max = ctx.add(t_import.float_import("/fs/testData/deQ/in/rQ_2.idx", "a_max"));
S_TENSOR a = ctx.addCached(hold(t_import.ubyte_import("/fs/testData/deQ/in/rQ_0.idx")), "a");
S_TENSOR a_min = ctx.addCached(hold(t_import.float_import("/fs/testData/deQ/in/rQ_1.idx")), "a_min");
S_TENSOR a_max = ctx.addCached(hold(t_import.float_import("/fs/testData/deQ/in/rQ_2.idx")), "a_max");

//reference outputs
S_TENSOR out_ref = ctx.add(t_import.float_import("/fs/testData/deQ/out/deQ_0.idx", "out_ref"));
S_TENSOR out_ref = ctx.addCached(hold(t_import.float_import("/fs/testData/deQ/out/deQ_0.idx")), "out_ref");

//modify the checks below:
S_TENSOR out = ctx.add(new RamTensor<float>(out_ref->getShape(), "out"));
S_TENSOR out = ctx.addCached(hold(new RamTensor<float>(out_ref->getShape())), "out");

timer_start();
ctx.push(new DequantizeOp(), {"a", "a_min", "a_max"}, {"out"});
ctx.push_static(hold(new DequantizeOp()), "DequantizeOp", {"a", "a_min", "a_max"}, {"out"});
ctx.eval();
timer_stop();

Expand All @@ -69,18 +69,18 @@ class ArrayOpsTest : public Test {
TensorIdxImporter t_import;

//reference inputs
S_TENSOR ref_a = ctx.add(t_import.float_import("/fs/testData/ref_reshape/in/Const_0.idx", "ref_a"));
S_TENSOR ref_dim = ctx.add(t_import.int_import("/fs/testData/ref_reshape/in/Const_1_0.idx", "ref_dim"));
S_TENSOR ref_a = ctx.addCached(hold(t_import.float_import("/fs/testData/ref_reshape/in/Const_0.idx")), "ref_a");
S_TENSOR ref_dim = ctx.addCached(hold(t_import.int_import("/fs/testData/ref_reshape/in/Const_1_0.idx")), "ref_dim");

//reference outputs
S_TENSOR out_ref_2 = ctx.add(t_import.float_import("/fs/testData/ref_reshape/out/ref_reshape_0.idx", "out_ref_2"));
S_TENSOR out_ref_2 = ctx.addCached(hold(t_import.float_import("/fs/testData/ref_reshape/out/ref_reshape_0.idx")), "out_ref_2");

//modify the checks below:
S_TENSOR out_2 = ctx.add(new RamTensor<float>(out_ref_2->getShape(), "out_2"));
S_TENSOR out_2 = ctx.addCached(hold(new RamTensor<float>(out_ref_2->getShape())), "out_2");


timer_start();
ctx.push(new ReshapeOp(), {"ref_a", "ref_dim"}, {"out_2"});
ctx.push_static(hold(new ReshapeOp()), "ReshapeOp", {"ref_a", "ref_dim"}, {"out_2"});
ctx.eval();
timer_stop();

Expand Down
114 changes: 57 additions & 57 deletions MathTests.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -17,24 +17,24 @@ class MathOpsTest : public Test {

//Note: raw pointers should be owned ONLY by the context. no copy of the raw pointer should exist elsewhere
// reference inputs
ctx.add(t_import.int_import("/fs/testData/rqRange/in/qMatMul_0.idx", "a"));
ctx.add(t_import.float_import("/fs/testData/rqRange/in/qMatMul_1.idx", "a_min"));
ctx.add(t_import.float_import("/fs/testData/rqRange/in/qMatMul_2.idx", "a_max"));
ctx.addCached(hold(t_import.int_import("/fs/testData/rqRange/in/qMatMul_0.idx")), "a");
ctx.addCached(hold(t_import.float_import("/fs/testData/rqRange/in/qMatMul_1.idx")), "a_min");
ctx.addCached(hold(t_import.float_import("/fs/testData/rqRange/in/qMatMul_2.idx")), "a_max");

// reference output
ctx.add(t_import.float_import("/fs/testData/rqRange/out/rqRange_0.idx", "ref_min"));
ctx.add(t_import.float_import("/fs/testData/rqRange/out/rqRange_1.idx", "ref_max"));
ctx.addCached(hold(t_import.float_import("/fs/testData/rqRange/out/rqRange_0.idx")), "ref_min");
ctx.addCached(hold(t_import.float_import("/fs/testData/rqRange/out/rqRange_1.idx")), "ref_max");

// Implementation goes here

// modify the checks below:
ctx.add(new RamTensor<float>(ctx.get("ref_min")->getShape(), "out_min"));
ctx.add(new RamTensor<float>(ctx.get("ref_max")->getShape(), "out_max"));
ctx.addCached(hold(new RamTensor<float>(ctx.get("ref_min")->getShape())), "out_min");
ctx.addCached(hold(new RamTensor<float>(ctx.get("ref_max")->getShape())), "out_max");
TNameList inputs = {"a", "a_min", "a_max"};
TNameList outputs = {"out_min", "out_max"};

timer_start();
ctx.push(new Requantization_RangeOp(), inputs, outputs);
ctx.push_static(hold(new Requantization_RangeOp()), "Requantization_RangeOp", inputs, outputs);
ctx.eval();
timer_stop();

Expand All @@ -52,33 +52,33 @@ class MathOpsTest : public Test {
ctx.gc();

// reference inputs
ctx.add(t_import.int_import("/fs/testData/rQ/in/qMatMul_0.idx", "a"));
ctx.add(t_import.float_import("/fs/testData/rQ/in/qMatMul_1.idx", "a_min"));
ctx.add(t_import.float_import("/fs/testData/rQ/in/qMatMul_2.idx", "a_max"));
ctx.add(t_import.float_import("/fs/testData/rQ/in/rqRange_0.idx", "r_a_min"));
ctx.add(t_import.float_import("/fs/testData/rQ/in/rqRange_1.idx", "r_a_max"));
ctx.addCached(hold(t_import.int_import("/fs/testData/rQ/in/qMatMul_0.idx")), "a");
ctx.addCached(hold(t_import.float_import("/fs/testData/rQ/in/qMatMul_1.idx")), "a_min");
ctx.addCached(hold(t_import.float_import("/fs/testData/rQ/in/qMatMul_2.idx")), "a_max");
ctx.addCached(hold(t_import.float_import("/fs/testData/rQ/in/rqRange_0.idx")), "r_a_min");
ctx.addCached(hold(t_import.float_import("/fs/testData/rQ/in/rqRange_1.idx")), "r_a_max");
// tf.quint8

//Note:
//Instead of using ctx.get() to obtain a shared_ptr, you may also use the shared_ptr returned by ctx.add()

// reference outputs
S_TENSOR ref_a_q = ctx.add(t_import.ubyte_import("/fs/testData/rQ/out/rQ_0.idx", "ref_a_q"));
S_TENSOR ref_a_min = ctx.add(t_import.float_import("/fs/testData/rQ/out/rQ_1.idx", "ref_a_min"));
S_TENSOR ref_a_max = ctx.add(t_import.float_import("/fs/testData/rQ/out/rQ_2.idx", "ref_a_max"));
S_TENSOR ref_a_q = ctx.addCached(hold(t_import.ubyte_import("/fs/testData/rQ/out/rQ_0.idx")), "ref_a_q");
S_TENSOR ref_a_min = ctx.addCached(hold(t_import.float_import("/fs/testData/rQ/out/rQ_1.idx")), "ref_a_min");
S_TENSOR ref_a_max = ctx.addCached(hold(t_import.float_import("/fs/testData/rQ/out/rQ_2.idx")), "ref_a_max");

// modify the checks below:
S_TENSOR a_q = ctx.add(new RamTensor<unsigned char>(ref_a_q->getShape(), "a_q"));
S_TENSOR a_min_q = ctx.add(new RamTensor<float>(ref_a_min->getShape(), "a_min_q"));
S_TENSOR a_max_q = ctx.add(new RamTensor<float>(ref_a_max->getShape(), "a_max_q"));
S_TENSOR a_q = ctx.addCached(hold(new RamTensor<unsigned char>(ref_a_q->getShape())), "a_q");
S_TENSOR a_min_q = ctx.addCached(hold(new RamTensor<float>(ref_a_min->getShape())), "a_min_q");
S_TENSOR a_max_q = ctx.addCached(hold(new RamTensor<float>(ref_a_max->getShape())), "a_max_q");


TNameList inputs = {"a", "a_min", "a_max", "r_a_min", "r_a_max"};
TNameList outputs = {"a_q", "a_min_q", "a_max_q"};

// Implementation goes here
timer_start();
ctx.push(new RequantizeOp(), inputs, outputs);
ctx.push_static(hold(new RequantizeOp()), "RequantizeOp", inputs, outputs);
ctx.eval();
timer_stop();

Expand All @@ -95,23 +95,23 @@ class MathOpsTest : public Test {
ctx.gc();

// reference inputs
ctx.add(t_import.int_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_quantized_mat_mul_0.idx", "a"));
ctx.add(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_quantized_mat_mul_1.idx", "a_min"));
ctx.add(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_quantized_mat_mul_2.idx", "a_max"));
ctx.add(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_requant_range_0.idx", "r_a_min"));
ctx.add(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_requant_range_1.idx", "r_a_max"));
ctx.addCached(hold(t_import.int_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_quantized_mat_mul_0.idx")), "a");
ctx.addCached(hold(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_quantized_mat_mul_1.idx")), "a_min");
ctx.addCached(hold(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_quantized_mat_mul_2.idx")), "a_max");
ctx.addCached(hold(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_requant_range_0.idx")), "r_a_min");
ctx.addCached(hold(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/in/import-MatMul_eightbit_requant_range_1.idx")), "r_a_max");
// tf.quint8

// reference outputs
ctx.add(t_import.ubyte_import("/fs/testData/import-MatMul_eightbit_requantize/out/import-MatMul_eightbit_requantize_0.idx", "ref_a_q"));
ctx.add(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/out/import-MatMul_eightbit_requantize_1.idx", "ref_a_min"));
ctx.add(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/out/import-MatMul_eightbit_requantize_2.idx", "ref_a_max"));
ctx.addCached(hold(t_import.ubyte_import("/fs/testData/import-MatMul_eightbit_requantize/out/import-MatMul_eightbit_requantize_0.idx")), "ref_a_q");
ctx.addCached(hold(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/out/import-MatMul_eightbit_requantize_1.idx")), "ref_a_min");
ctx.addCached(hold(t_import.float_import("/fs/testData/import-MatMul_eightbit_requantize/out/import-MatMul_eightbit_requantize_2.idx")), "ref_a_max");


// modify the checks below:
ctx.add(new RamTensor<unsigned char>(ctx.get("ref_a_q")->getShape(), "a_q"));
ctx.add(new RamTensor<float>(ctx.get("ref_a_min")->getShape(), "a_min_q"));
ctx.add(new RamTensor<float>(ctx.get("ref_a_max")->getShape(), "a_max_q"));
ctx.addCached(hold(new RamTensor<unsigned char>(ctx.get("ref_a_q")->getShape())), "a_q");
ctx.addCached(hold(new RamTensor<float>(ctx.get("ref_a_min")->getShape())), "a_min_q");
ctx.addCached(hold(new RamTensor<float>(ctx.get("ref_a_max")->getShape())), "a_max_q");

S_TENSOR ref_val = ctx.get("ref_a_q");
S_TENSOR ref_min = ctx.get("ref_a_min");
Expand All @@ -122,7 +122,7 @@ class MathOpsTest : public Test {

// Implementation goes here
timer_start();
ctx.push(new RequantizeOp(), {"a", "a_min", "a_max", "r_a_min", "r_a_max"}, {"a_q", "a_min_q", "a_max_q"});
ctx.push_static(hold(new RequantizeOp()), "RequantizeOp", {"a", "a_min", "a_max", "r_a_min", "r_a_max"}, {"a_q", "a_min_q", "a_max_q"});
ctx.eval();
timer_stop();

Expand Down Expand Up @@ -158,28 +158,28 @@ class MathOpsTest : public Test {
ctx.gc();

// reference inputs
ctx.add(t_import.float_import("/fs/testData/ArgMax/in/ArgMax-input_0.idx", "ref_a"));
ctx.add(t_import.int_import("/fs/testData/ArgMax/in/ArgMax-dimension_0.idx", "ref_dim"));
ctx.addCached(hold(t_import.float_import("/fs/testData/ArgMax/in/ArgMax-input_0.idx")), "ref_a");
ctx.addCached(hold(t_import.int_import("/fs/testData/ArgMax/in/ArgMax-dimension_0.idx")), "ref_dim");

// reference outputs
/// NT: FIXME: argmax outputs int64 tensor which isn't supported by
/// int_import.
S_TENSOR ref_out = ctx.add(t_import.float_import("/fs/testData/ArgMax/out/ArgMax_0.idx", "ref_out"));
S_TENSOR ref_out = ctx.addCached(hold(t_import.float_import("/fs/testData/ArgMax/out/ArgMax_0.idx")), "ref_out");

// Implementation goes here

// modify the checks below:
S_TENSOR out = ctx.add(new RamTensor<int>(ref_out->getShape(), "out"));
S_TENSOR out = ctx.addCached(hold(new RamTensor<int>(ref_out->getShape())), "out");

TNameList inputs = {"ref_a", "ref_dim"};
TNameList outputs = {"out"};

timer_start();
ctx.push(new ArgMaxOp<float, int>(), inputs, outputs);
ctx.push_static(hold(new ArgMaxOp<float, int>()), "ArgMaxOp", inputs, outputs);
ctx.eval();
timer_stop();

Tensor* out_float = TensorCast<int, float>(out.get(), "out_float"); ///NT: /WIP how to handle the name?
Tensor* out_float = TensorCast<int, float>(out.get()); ///NT: /WIP how to handle the name?

double result = meanPercentErr<float>(ref_out.get(), out_float);

Expand All @@ -192,24 +192,24 @@ class MathOpsTest : public Test {

ctx.gc();

S_TENSOR test_input = ctx.add(TensorConstant<float>({10, 5}, 0.0f, "test_input"));
S_TENSOR test_input = ctx.add(TensorConstant<float>({10, 5}, 0.0f), "test_input");
*(test_input->write<float>(25, 0)) = 1.0f;
*(test_input->write<float>(26, 0)) = 1.0f;
*(test_input->write<float>(7, 0)) = 1.0f;
*(test_input->write<float>(48, 0)) = 1.0f;
*(test_input->write<float>(14, 0)) = 1.0f;

S_TENSOR test_dim = ctx.add(new RamTensor<int>({1}, "test_dim"));
S_TENSOR test_dim = ctx.add(new RamTensor<int>({1}), "test_dim");
*(test_dim->write<int>(0, 0)) = 0;

S_TENSOR test_out_ref = ctx.add(new RamTensor<float>({5}, "test_out_ref"));
S_TENSOR test_out_ref = ctx.add(new RamTensor<float>({5}), "test_out_ref");
*(test_out_ref->write<float>(0, 0)) = 5.0f;
*(test_out_ref->write<float>(1, 0)) = 5.0f;
*(test_out_ref->write<float>(2, 0)) = 1.0f;
*(test_out_ref->write<float>(3, 0)) = 9.0f;
*(test_out_ref->write<float>(4, 0)) = 2.0f;

S_TENSOR test_out = ctx.add(new RamTensor<float>(test_out_ref->getShape(), "test_out"));
S_TENSOR test_out = ctx.add(new RamTensor<float>(test_out_ref->getShape()), "test_out");
TNameList inputs = {"test_input", "test_dim"};
TNameList outputs = {"test_out"};

Expand All @@ -227,20 +227,20 @@ class MathOpsTest : public Test {
testStart("add");

// reference inputs
ctx.add(t_import.float_import("/fs/testData/ref_add/in/Const_5_0.idx", "a"));
ctx.add(t_import.float_import("/fs/testData/ref_add/in/Const_6_0.idx", "b"));
ctx.addCached(hold(t_import.float_import("/fs/testData/ref_add/in/Const_5_0.idx")), "a");
ctx.addCached(hold(t_import.float_import("/fs/testData/ref_add/in/Const_6_0.idx")), "b");

// reference outputs
S_TENSOR ref_out = ctx.add(t_import.float_import("/fs/testData/ref_add/out/ref_add_0.idx", "ref_out"));
S_TENSOR ref_out = ctx.addCached(hold(t_import.float_import("/fs/testData/ref_add/out/ref_add_0.idx")), "ref_out");

// Implementation goes here

// modify the checks below:
S_TENSOR out = ctx.add(new RamTensor<float>(ref_out->getShape(), "out"));
S_TENSOR out = ctx.addCached(hold(new RamTensor<float>(ref_out->getShape())), "out");
TNameList inputs = {"a", "b"};
TNameList outputs = {"out"};
timer_start();
ctx.push(new AddOp<float, float>(), inputs, outputs);
ctx.push_static(hold(new AddOp<float, float>()), "AddOp", inputs, outputs);
ctx.eval();
timer_stop();

Expand All @@ -255,21 +255,21 @@ class MathOpsTest : public Test {
ctx.gc();

// reference inputs
ctx.add(t_import.float_import("/fs/testData/ref_min/in/Const_2_0.idx", "a"));
ctx.add(t_import.int_import("/fs/testData/ref_min/in/Const_3_0.idx", "dim"));
ctx.addCached(hold(t_import.float_import("/fs/testData/ref_min/in/Const_2_0.idx")), "a");
ctx.addCached(hold(t_import.int_import("/fs/testData/ref_min/in/Const_3_0.idx")), "dim");

// reference outputs
S_TENSOR ref_out = ctx.add(t_import.float_import("/fs/testData/ref_min/out/ref_min_0.idx", "ref_out"));
S_TENSOR ref_out = ctx.addCached(hold(t_import.float_import("/fs/testData/ref_min/out/ref_min_0.idx")), "ref_out");

// Implementation goes here

// modify the checks below:
S_TENSOR out = ctx.add(new RamTensor<float>(ref_out->getShape(), "out"));
S_TENSOR out = ctx.addCached(hold(new RamTensor<float>(ref_out->getShape())), "out");
TNameList inputs = {"a", "dim"};
TNameList outputs = {"out"};

timer_start();
ctx.push(new MinOp(), inputs, outputs);
ctx.push_static(hold(new MinOp()), "MinOp", inputs, outputs);
ctx.eval();
timer_stop();

Expand All @@ -284,20 +284,20 @@ class MathOpsTest : public Test {
ctx.gc();

// reference inputs
ctx.add(t_import.float_import("/fs/testData/ref_max/in/Const_2_0.idx", "a"));
ctx.add(t_import.int_import("/fs/testData/ref_max/in/Const_4_0.idx", "dim"));
ctx.addCached(hold(t_import.float_import("/fs/testData/ref_max/in/Const_2_0.idx")), "a");
ctx.addCached(hold(t_import.int_import("/fs/testData/ref_max/in/Const_4_0.idx")), "dim");

// reference outputs
S_TENSOR ref_out = ctx.add(t_import.float_import("/fs/testData/ref_max/out/ref_max_0.idx", "ref_out"));
S_TENSOR ref_out = ctx.addCached(hold(t_import.float_import("/fs/testData/ref_max/out/ref_max_0.idx")), "ref_out");

// Implementation goes here

// modify the checks below:
S_TENSOR out = ctx.add(new RamTensor<float>(ref_out->getShape(), "out"));
S_TENSOR out = ctx.addCached(hold(new RamTensor<float>(ref_out->getShape())), "out");
TNameList inputs = {"a", "dim"};
TNameList outputs = {"out"};
timer_start();
ctx.push(new MaxOp(), inputs, outputs);
ctx.push_static(hold(new MaxOp()), "MaxOp", inputs, outputs);
ctx.eval();
timer_stop();

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