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Merged
merged 5 commits into from
Dec 7, 2020
Merged

Qsim upgrade #445

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1ca4cd8
Upgrade qsim 0.3.1 -> 0.6.0.
MichaelBroughton Dec 4, 2020
c7c911b
removed benchmarking includes.
MichaelBroughton Dec 4, 2020
faf47ef
Merge branch 'master' into qsim_upgrade
MichaelBroughton Dec 4, 2020
e542497
Update tfq_inner_product.cc
MichaelBroughton Dec 7, 2020
c2a9a57
re-trigger CI.
MichaelBroughton Dec 7, 2020
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6 changes: 3 additions & 3 deletions WORKSPACE
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Original file line number Diff line number Diff line change
Expand Up @@ -67,9 +67,9 @@ http_archive(

http_archive(
name = "qsim",
sha256 = "7e5fe6c909d0007488f910d57ed765729133437f5c5f88085fa6deb544cb97dc",
strip_prefix = "qsim-0.3.1",
urls = ["https://github.com/quantumlib/qsim/archive/v0.3.1.zip"],
sha256 = "f390ee72cf88c48d81c98262c599dc45d660a2a9308a9ee903bfa73aec08a9b4",
strip_prefix = "qsim-0.6.0",
urls = ["https://github.com/quantumlib/qsim/archive/v0.6.0.zip"],
)

# Added for crosstool in tensorflow.
Expand Down
26 changes: 12 additions & 14 deletions tensorflow_quantum/core/ops/math_ops/tfq_inner_product.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -155,25 +155,24 @@ class TfqInnerProductOp : public tensorflow::OpKernel {
const auto tfq_for = tfq::QsimFor(context);
using Simulator = qsim::Simulator<const tfq::QsimFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

// Begin simulation.
int largest_nq = 1;
State sv = StateSpace(largest_nq, tfq_for).CreateState();
State scratch = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
auto scratch = ss.Create(largest_nq);

// Simulate programs one by one. Parallelizing over state vectors
// we no longer parallelize over circuits. Each time we encounter a
// a larger circuit we will grow the Statevector as necessary.
for (int i = 0; i < fused_circuits.size(); i++) {
int nq = num_qubits[i];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);
if (nq > largest_nq) {
// need to switch to larger statespace.
largest_nq = nq;
sv = ss.CreateState();
scratch = ss.CreateState();
sv = ss.Create(largest_nq);
scratch = ss.Create(largest_nq);
}
// TODO: add heuristic here so that we do not always recompute
// the state if there is a possibility that circuit[i] and
Expand Down Expand Up @@ -211,7 +210,6 @@ class TfqInnerProductOp : public tensorflow::OpKernel {
const auto tfq_for = qsim::SequentialFor(1);
using Simulator = qsim::Simulator<const qsim::SequentialFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

const int output_dim_internal_size = output_tensor->dimension(1);

Expand All @@ -221,15 +219,15 @@ class TfqInnerProductOp : public tensorflow::OpKernel {
int largest_nq = 1;
int cur_internal_index;

State sv = StateSpace(largest_nq, tfq_for).CreateState();
State scratch = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
auto scratch = ss.Create(largest_nq);
for (int i = start; i < end; i++) {
cur_batch_index = i / output_dim_internal_size;
cur_internal_index = i % output_dim_internal_size;

const int nq = num_qubits[cur_batch_index];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);

// (#679) Just ignore empty program
if (fused_circuits[cur_batch_index].size() == 0) {
Expand All @@ -242,9 +240,9 @@ class TfqInnerProductOp : public tensorflow::OpKernel {
// We've run into a new state vector we must compute.
// Only compute a new state vector when we have to.
if (nq > largest_nq) {
sv = ss.CreateState();
scratch = ss.CreateState();
largest_nq = nq;
sv = ss.Create(largest_nq);
scratch = ss.Create(largest_nq);
}
// no need to update scratch_state since ComputeExpectation
// will take care of things for us.
Expand Down
39 changes: 19 additions & 20 deletions tensorflow_quantum/core/ops/tfq_adj_grad_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -172,25 +172,24 @@ class TfqAdjointGradientOp : public tensorflow::OpKernel {
const auto tfq_for = qsim::SequentialFor(1);
using Simulator = qsim::Simulator<const qsim::SequentialFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

auto DoWork = [&](int start, int end) {
// Begin simulation.
int largest_nq = 1;
State sv = StateSpace(largest_nq, tfq_for).CreateState();
State scratch = StateSpace(largest_nq, tfq_for).CreateState();
State scratch2 = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
auto scratch = ss.Create(largest_nq);
auto scratch2 = ss.Create(largest_nq);

for (int i = start; i < end; i++) {
int nq = num_qubits[i];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);
if (nq > largest_nq) {
// need to switch to larger statespace.
largest_nq = nq;
sv = ss.CreateState();
scratch = ss.CreateState();
scratch2 = ss.CreateState();
sv = ss.Create(largest_nq);
scratch = ss.Create(largest_nq);
scratch2 = ss.Create(largest_nq);
}

// (#679) Just ignore empty program
Expand Down Expand Up @@ -225,7 +224,7 @@ class TfqAdjointGradientOp : public tensorflow::OpKernel {
for (int k = 0; k < gradient_gates[i][j - 1].grad_gates.size(); k++) {
// Copy sv onto scratch2 in anticipation of non-unitary "gradient
// gate".
ss.CopyState(sv, scratch2);
ss.Copy(sv, scratch2);
qsim::ApplyGate(sim, gradient_gates[i][j - 1].grad_gates[k],
scratch2);

Expand Down Expand Up @@ -269,24 +268,24 @@ class TfqAdjointGradientOp : public tensorflow::OpKernel {
const auto tfq_for = tfq::QsimFor(context);
using Simulator = qsim::Simulator<const tfq::QsimFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

// Begin simulation.
int largest_nq = 1;
State sv = StateSpace(largest_nq, tfq_for).CreateState();
State scratch = StateSpace(largest_nq, tfq_for).CreateState();
State scratch2 = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
auto scratch = ss.Create(largest_nq);
auto scratch2 = ss.Create(largest_nq);

for (int i = 0; i < partial_fused_circuits.size(); i++) {
int nq = num_qubits[i];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);

if (nq > largest_nq) {
// need to switch to larger statespace.
largest_nq = nq;
sv = ss.CreateState();
scratch = ss.CreateState();
scratch2 = ss.CreateState();
sv = ss.Create(largest_nq);
scratch = ss.Create(largest_nq);
scratch2 = ss.Create(largest_nq);
}

// (#679) Just ignore empty program
Expand Down Expand Up @@ -321,7 +320,7 @@ class TfqAdjointGradientOp : public tensorflow::OpKernel {
for (int k = 0; k < gradient_gates[i][j - 1].grad_gates.size(); k++) {
// Copy sv onto scratch2 in anticipation of non-unitary "gradient
// gate".
ss.CopyState(sv, scratch2);
ss.Copy(sv, scratch2);
qsim::ApplyGate(sim, gradient_gates[i][j - 1].grad_gates[k],
scratch2);

Expand Down
27 changes: 13 additions & 14 deletions tensorflow_quantum/core/ops/tfq_simulate_expectation_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -127,25 +127,25 @@ class TfqSimulateExpectationOp : public tensorflow::OpKernel {
const auto tfq_for = tfq::QsimFor(context);
using Simulator = qsim::Simulator<const tfq::QsimFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

// Begin simulation.
int largest_nq = 1;
State sv = StateSpace(largest_nq, tfq_for).CreateState();
State scratch = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
auto scratch = ss.Create(largest_nq);

// Simulate programs one by one. Parallelizing over state vectors
// we no longer parallelize over circuits. Each time we encounter a
// a larger circuit we will grow the Statevector as necessary.
for (int i = 0; i < fused_circuits.size(); i++) {
int nq = num_qubits[i];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);

if (nq > largest_nq) {
// need to switch to larger statespace.
largest_nq = nq;
sv = ss.CreateState();
scratch = ss.CreateState();
sv = ss.Create(largest_nq);
scratch = ss.Create(largest_nq);
}
// TODO: add heuristic here so that we do not always recompute
// the state if there is a possibility that circuit[i] and
Expand Down Expand Up @@ -178,7 +178,6 @@ class TfqSimulateExpectationOp : public tensorflow::OpKernel {
const auto tfq_for = qsim::SequentialFor(1);
using Simulator = qsim::Simulator<const qsim::SequentialFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

const int output_dim_op_size = output_tensor->dimension(1);

Expand All @@ -188,15 +187,15 @@ class TfqSimulateExpectationOp : public tensorflow::OpKernel {
int largest_nq = 1;
int cur_op_index;

State sv = StateSpace(largest_nq, tfq_for).CreateState();
State scratch = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
auto scratch = ss.Create(largest_nq);
for (int i = start; i < end; i++) {
cur_batch_index = i / output_dim_op_size;
cur_op_index = i % output_dim_op_size;

const int nq = num_qubits[cur_batch_index];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);

// (#679) Just ignore empty program
if (fused_circuits[cur_batch_index].size() == 0) {
Expand All @@ -208,9 +207,9 @@ class TfqSimulateExpectationOp : public tensorflow::OpKernel {
// We've run into a new state vector we must compute.
// Only compute a new state vector when we have to.
if (nq > largest_nq) {
sv = ss.CreateState();
scratch = ss.CreateState();
largest_nq = nq;
sv = ss.Create(largest_nq);
scratch = ss.Create(largest_nq);
}
// no need to update scratch_state since ComputeExpectation
// will take care of things for us.
Expand Down
27 changes: 13 additions & 14 deletions tensorflow_quantum/core/ops/tfq_simulate_sampled_expectation_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -144,25 +144,25 @@ class TfqSimulateSampledExpectationOp : public tensorflow::OpKernel {
const auto tfq_for = tfq::QsimFor(context);
using Simulator = qsim::Simulator<const tfq::QsimFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

// Begin simulation.
int largest_nq = 1;
State sv = StateSpace(largest_nq, tfq_for).CreateState();
State scratch = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
auto scratch = ss.Create(largest_nq);

// Simulate programs one by one. Parallelizing over state vectors
// we no longer parallelize over circuits. Each time we encounter a
// a larger circuit we will grow the Statevector as necessary.
for (int i = 0; i < fused_circuits.size(); i++) {
int nq = num_qubits[i];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);

if (nq > largest_nq) {
// need to switch to larger statespace.
largest_nq = nq;
sv = ss.CreateState();
scratch = ss.CreateState();
sv = ss.Create(largest_nq);
scratch = ss.Create(largest_nq);
}
// TODO: add heuristic here so that we do not always recompute
// the state if there is a possibility that circuit[i] and
Expand Down Expand Up @@ -196,7 +196,6 @@ class TfqSimulateSampledExpectationOp : public tensorflow::OpKernel {
const auto tfq_for = qsim::SequentialFor(1);
using Simulator = qsim::Simulator<const qsim::SequentialFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

const int output_dim_op_size = output_tensor->dimension(1);

Expand All @@ -206,15 +205,15 @@ class TfqSimulateSampledExpectationOp : public tensorflow::OpKernel {
int largest_nq = 1;
int cur_op_index;

State sv = StateSpace(largest_nq, tfq_for).CreateState();
State scratch = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
auto scratch = ss.Create(largest_nq);
for (int i = start; i < end; i++) {
cur_batch_index = i / output_dim_op_size;
cur_op_index = i % output_dim_op_size;

const int nq = num_qubits[cur_batch_index];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);

// (#679) Just ignore empty program
if (fused_circuits[cur_batch_index].size() == 0) {
Expand All @@ -226,9 +225,9 @@ class TfqSimulateSampledExpectationOp : public tensorflow::OpKernel {
// We've run into a new state vector we must compute.
// Only compute a new state vector when we have to.
if (nq > largest_nq) {
sv = ss.CreateState();
scratch = ss.CreateState();
largest_nq = nq;
sv = ss.Create(largest_nq);
scratch = ss.Create(largest_nq);
}
// no need to update scratch_state since ComputeExpectation
// will take care of things for us.
Expand Down
20 changes: 10 additions & 10 deletions tensorflow_quantum/core/ops/tfq_simulate_samples_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -127,23 +127,23 @@ class TfqSimulateSamplesOp : public tensorflow::OpKernel {
const auto tfq_for = tfq::QsimFor(context);
using Simulator = qsim::Simulator<const tfq::QsimFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

// Begin simulation.
int largest_nq = 1;
State sv = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);

// Simulate programs one by one. Parallelizing over state vectors
// we no longer parallelize over circuits. Each time we encounter a
// a larger circuit we will grow the Statevector as nescessary.
for (int i = 0; i < fused_circuits.size(); i++) {
int nq = num_qubits[i];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);

if (nq > largest_nq) {
// need to switch to larger statespace.
largest_nq = nq;
sv = ss.CreateState();
sv = ss.Create(largest_nq);
}
ss.SetStateZero(sv);
for (int j = 0; j < fused_circuits[i].size(); j++) {
Expand Down Expand Up @@ -180,19 +180,19 @@ class TfqSimulateSamplesOp : public tensorflow::OpKernel {
const auto tfq_for = qsim::SequentialFor(1);
using Simulator = qsim::Simulator<const qsim::SequentialFor&>;
using StateSpace = Simulator::StateSpace;
using State = StateSpace::State;

auto DoWork = [&](int start, int end) {
int largest_nq = 1;
State sv = StateSpace(largest_nq, tfq_for).CreateState();
Simulator sim = Simulator(tfq_for);
StateSpace ss = StateSpace(tfq_for);
auto sv = ss.Create(largest_nq);
for (int i = start; i < end; i++) {
int nq = num_qubits[i];
Simulator sim = Simulator(nq, tfq_for);
StateSpace ss = StateSpace(nq, tfq_for);

if (nq > largest_nq) {
// need to switch to larger statespace.
largest_nq = nq;
sv = ss.CreateState();
sv = ss.Create(largest_nq);
}
ss.SetStateZero(sv);
for (int j = 0; j < fused_circuits[i].size(); j++) {
Expand Down
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