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Test solvers on fixed hdf5 data #2887

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Aug 9, 2015
Merged

Test solvers on fixed hdf5 data #2887

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2c356a4
TestGradientBasedSolver: drop doubled seed inititialization
shelhamer Aug 8, 2015
6019246
TestGradientBasedSolver: replace dummy data with hdf5
shelhamer Aug 8, 2015
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28 changes: 27 additions & 1 deletion src/caffe/test/test_data/generate_sample_data.py
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Original file line number Diff line number Diff line change
@@ -1,12 +1,14 @@
"""
Generate data used in the HDF5DataLayer test.
Generate data used in the HDF5DataLayer and GradientBasedSolver tests.
"""
import os
import numpy as np
import h5py

script_dir = os.path.dirname(os.path.abspath(__file__))

# Generate HDF5DataLayer sample_data.h5

num_cols = 8
num_rows = 10
height = 6
Expand Down Expand Up @@ -51,3 +53,27 @@
with open(script_dir + '/sample_data_list.txt', 'w') as f:
f.write(script_dir + '/sample_data.h5\n')
f.write(script_dir + '/sample_data_2_gzip.h5\n')

# Generate GradientBasedSolver solver_data.h5

num_cols = 3
num_rows = 8
height = 10
width = 10

data = np.random.randn(num_rows, num_cols, height, width)
data = data.reshape(num_rows, num_cols, height, width)
data = data.astype('float32')

targets = np.random.randn(num_rows, 1)
targets = targets.astype('float32')

print data
print targets

with h5py.File(script_dir + '/solver_data.h5', 'w') as f:
f['data'] = data
f['targets'] = targets

with open(script_dir + '/solver_data_list.txt', 'w') as f:
f.write(script_dir + '/solver_data.h5\n')
Binary file added src/caffe/test/test_data/solver_data.h5
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1 change: 1 addition & 0 deletions src/caffe/test/test_data/solver_data_list.txt
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Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
src/caffe/test/test_data/solver_data.h5
40 changes: 17 additions & 23 deletions src/caffe/test/test_gradient_based_solver.cpp
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Expand Up @@ -25,15 +25,26 @@ class GradientBasedSolverTest : public MultiDeviceTest<TypeParam> {
protected:
GradientBasedSolverTest() :
seed_(1701), num_(4), channels_(3), height_(10), width_(10),
constant_data_(false), share_(false) {}
share_(false) {
input_file_ = new string(
CMAKE_SOURCE_DIR "caffe/test/test_data/solver_data_list.txt" CMAKE_EXT);
}
~GradientBasedSolverTest() {
delete input_file_;
}

string snapshot_prefix_;
shared_ptr<SGDSolver<Dtype> > solver_;
int seed_;
// Dimensions are determined by generate_sample_data.py
// TODO this is brittle and the hdf5 file should be checked instead.
int num_, channels_, height_, width_;
bool constant_data_, share_;
bool share_;
Dtype delta_; // Stability constant for AdaGrad.

// Test data: check out generate_sample_data.py in the same directory.
string* input_file_;

virtual SolverParameter_SolverType solver_type() = 0;
virtual void InitSolver(const SolverParameter& param) = 0;

Expand Down Expand Up @@ -71,25 +82,10 @@ class GradientBasedSolverTest : public MultiDeviceTest<TypeParam> {
" name: 'TestNetwork' "
" layer { "
" name: 'data' "
" type: 'DummyData' "
" dummy_data_param { "
" num: " << num_ / iter_size << " "
" channels: " << channels_ << " "
" height: " << height_ << " "
" width: " << width_ << " "
" channels: 1 "
" height: 1 "
" width: 1 "
" data_filler { "
" type: '" << string(constant_data_ ? "constant" : "gaussian")
<< "' "
" std: 1.0 "
" value: 1.0 "
" } "
" data_filler { "
" type: 'gaussian' "
" std: 1.0 "
" } "
" type: 'HDF5Data' "
" hdf5_data_param { "
" source: '" << *(this->input_file_) << "' "
" batch_size: " << num_ / iter_size << " "
" } "
" top: 'data' "
" top: 'targets' "
Expand Down Expand Up @@ -180,7 +176,6 @@ class GradientBasedSolverTest : public MultiDeviceTest<TypeParam> {
}
Caffe::set_random_seed(this->seed_);
this->InitSolverFromProtoString(proto.str());
Caffe::set_random_seed(this->seed_);
if (from_snapshot != NULL) {
this->solver_->Restore(from_snapshot);
vector<Blob<Dtype>*> empty_bottom_vec;
Expand Down Expand Up @@ -355,7 +350,6 @@ class GradientBasedSolverTest : public MultiDeviceTest<TypeParam> {
const Dtype kMomentum, const int kNumIters, const int kIterSize) {
const double kPrecision = 1e-2;
const double kMinPrecision = 1e-7;
constant_data_ = true;
// Solve without accumulation and save parameters.
this->RunLeastSquaresSolver(kLearningRate, kWeightDecay, kMomentum,
kNumIters);
Expand Down