[caffe] 05/08: patch: remove not needed patches
Zhou Mo
cdluminate-guest at moszumanska.debian.org
Mon Apr 17 02:52:00 UTC 2017
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cdluminate-guest pushed a commit to branch master
in repository caffe.
commit 9bc6bed4e2f0fabc7f04d129894df3204ccd7d7e
Author: Zhou Mo <cdluminate at gmail.com>
Date: Mon Apr 17 02:29:50 2017 +0000
patch: remove not needed patches
---
debian/changelog | 4 +-
.../fix-more-float-comparison-precision-issue | 73 ---------
debian/patches/post_rc5_upstream_updates.patch | 174 ---------------------
debian/patches/series | 2 -
4 files changed, 3 insertions(+), 250 deletions(-)
diff --git a/debian/changelog b/debian/changelog
index 106875e..49396bc 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -2,7 +2,9 @@ caffe (1.0.0-1) UNRELEASED; urgency=medium
* New upstream release. (The first stable release)
* Patchset update:
- - Remove patch make-using-gnuinstalldirs, which is merged by upstream.
+ - Remove merged patch make-using-gnuinstalldirs .
+ - Remove merged patch fix-more-float-comparison-precision-issue .
+ - Drop patch post_rc5_upstream_updates.patch .
-- Zhou Mo <cdluminate at gmail.com> Mon, 17 Apr 2017 02:21:16 +0000
diff --git a/debian/patches/fix-more-float-comparison-precision-issue b/debian/patches/fix-more-float-comparison-precision-issue
deleted file mode 100644
index 2f8e248..0000000
--- a/debian/patches/fix-more-float-comparison-precision-issue
+++ /dev/null
@@ -1,73 +0,0 @@
-Forward: [yes] https://github.com/BVLC/caffe/pull/4566
-
-commit d607858b90b645d8177c3970d782f0ab5c529558
-Author: Zhou Mo <cdluminate at gmail.com>
-Date: Tue Aug 9 15:13:47 2016 +0000
-
- Fix more float comparison precision issue
-
- With reference to this commit:
- f1a8470aa21e35a5b2bb83007f8fb7680a354815
-
- This fix changes some EXPECT_EQ into EXPECT_FLOAT_EQ .
-
---- a/src/caffe/test/test_convolution_layer.cpp
-+++ b/src/caffe/test/test_convolution_layer.cpp
-@@ -695,7 +695,7 @@
- }
- ASSERT_EQ(backward_result_nd.count(), backward_result_2d.count());
- for (int i = 0; i < backward_result_2d.count(); ++i) {
-- EXPECT_EQ(backward_result_2d.cpu_diff()[i],
-+ EXPECT_FLOAT_EQ(backward_result_2d.cpu_diff()[i],
- backward_result_nd.cpu_diff()[i]);
- }
- ASSERT_EQ(backward_weight_result_nd.count(),
---- a/src/caffe/test/test_gradient_based_solver.cpp
-+++ b/src/caffe/test/test_gradient_based_solver.cpp
-@@ -558,9 +558,9 @@
- const vector<Blob<Dtype>*>& params = solver_->net()->learnable_params();
- for (int i = 0; i < params.size(); ++i) {
- for (int j = 0; j < params[i]->count(); ++j) {
-- EXPECT_EQ(param_copies[i]->cpu_data()[j], params[i]->cpu_data()[j])
-+ EXPECT_FLOAT_EQ(param_copies[i]->cpu_data()[j], params[i]->cpu_data()[j])
- << "param " << i << " data differed at dim " << j;
-- EXPECT_EQ(param_copies[i]->cpu_diff()[j], params[i]->cpu_diff()[j])
-+ EXPECT_FLOAT_EQ(param_copies[i]->cpu_diff()[j], params[i]->cpu_diff()[j])
- << "param " << i << " diff differed at dim " << j;
- }
- }
-@@ -569,9 +569,9 @@
- const vector<shared_ptr<Blob<Dtype> > >& history = solver_->history();
- for (int i = 0; i < history.size(); ++i) {
- for (int j = 0; j < history[i]->count(); ++j) {
-- EXPECT_EQ(history_copies[i]->cpu_data()[j], history[i]->cpu_data()[j])
-+ EXPECT_FLOAT_EQ(history_copies[i]->cpu_data()[j], history[i]->cpu_data()[j])
- << "history blob " << i << " data differed at dim " << j;
-- EXPECT_EQ(history_copies[i]->cpu_diff()[j], history[i]->cpu_diff()[j])
-+ EXPECT_FLOAT_EQ(history_copies[i]->cpu_diff()[j], history[i]->cpu_diff()[j])
- << "history blob " << i << " diff differed at dim " << j;
- }
- }
---- a/src/caffe/test/test_neuron_layer.cpp
-+++ b/src/caffe/test/test_neuron_layer.cpp
-@@ -791,16 +791,16 @@
- ip2.Backward(blob_middle_vec_2, propagate_down, blob_bottom_vec_2);
- // Check numbers
- for (int s = 0; s < blob_bottom_2->count(); ++s) {
-- EXPECT_EQ(this->blob_bottom_->cpu_diff()[s], blob_bottom_2->cpu_diff()[s]);
-+ EXPECT_FLOAT_EQ(this->blob_bottom_->cpu_diff()[s], blob_bottom_2->cpu_diff()[s]);
- }
- for (int s = 0; s < ip.blobs()[0]->count(); ++s) {
-- EXPECT_EQ(ip.blobs()[0]->cpu_diff()[s], ip2.blobs()[0]->cpu_diff()[s]);
-+ EXPECT_FLOAT_EQ(ip.blobs()[0]->cpu_diff()[s], ip2.blobs()[0]->cpu_diff()[s]);
- }
- for (int s = 0; s < ip.blobs()[1]->count(); ++s) {
-- EXPECT_EQ(ip.blobs()[1]->cpu_diff()[s], ip2.blobs()[1]->cpu_diff()[s]);
-+ EXPECT_FLOAT_EQ(ip.blobs()[1]->cpu_diff()[s], ip2.blobs()[1]->cpu_diff()[s]);
- }
- for (int s = 0; s < prelu.blobs()[0]->count(); ++s) {
-- EXPECT_EQ(prelu.blobs()[0]->cpu_diff()[s],
-+ EXPECT_FLOAT_EQ(prelu.blobs()[0]->cpu_diff()[s],
- prelu2.blobs()[0]->cpu_diff()[s]);
- }
- }
diff --git a/debian/patches/post_rc5_upstream_updates.patch b/debian/patches/post_rc5_upstream_updates.patch
deleted file mode 100644
index b822197..0000000
--- a/debian/patches/post_rc5_upstream_updates.patch
+++ /dev/null
@@ -1,174 +0,0 @@
-diff --git a/docs/tutorial/layers.md b/docs/tutorial/layers.md
-index a903d5ac..2faacc58 100644
---- a/docs/tutorial/layers.md
-+++ b/docs/tutorial/layers.md
-@@ -128,7 +128,7 @@ Layers:
- * [Infogain Loss](layers/infogainloss.html) - a generalization of MultinomialLogisticLossLayer.
- * [Softmax with Loss](layers/softmaxwithloss.html) - computes the multinomial logistic loss of the softmax of its inputs. It's conceptually identical to a softmax layer followed by a multinomial logistic loss layer, but provides a more numerically stable gradient.
- * [Sum-of-Squares / Euclidean](layers/euclideanloss.html) - computes the sum of squares of differences of its two inputs, $$\frac 1 {2N} \sum_{i=1}^N \| x^1_i - x^2_i \|_2^2$$.
--* [Hinge / Margin](layers/hiddenloss.html) - The hinge loss layer computes a one-vs-all hinge (L1) or squared hinge loss (L2).
-+* [Hinge / Margin](layers/hingeloss.html) - The hinge loss layer computes a one-vs-all hinge (L1) or squared hinge loss (L2).
- * [Sigmoid Cross-Entropy Loss](layers/sigmoidcrossentropyloss.html) - computes the cross-entropy (logistic) loss, often used for predicting targets interpreted as probabilities.
- * [Accuracy / Top-k layer](layers/accuracy.html) - scores the output as an accuracy with respect to target -- it is not actually a loss and has no backward step.
- * [Contrastive Loss](layers/contrastiveloss.html)
-diff --git a/include/caffe/util/hdf5.hpp b/include/caffe/util/hdf5.hpp
-index ce568c5e..71549c1c 100644
---- a/include/caffe/util/hdf5.hpp
-+++ b/include/caffe/util/hdf5.hpp
-@@ -13,12 +13,12 @@ namespace caffe {
- template <typename Dtype>
- void hdf5_load_nd_dataset_helper(
- hid_t file_id, const char* dataset_name_, int min_dim, int max_dim,
-- Blob<Dtype>* blob);
-+ Blob<Dtype>* blob, bool reshape);
-
- template <typename Dtype>
- void hdf5_load_nd_dataset(
- hid_t file_id, const char* dataset_name_, int min_dim, int max_dim,
-- Blob<Dtype>* blob);
-+ Blob<Dtype>* blob, bool reshape = false);
-
- template <typename Dtype>
- void hdf5_save_nd_dataset(
-diff --git a/python/caffe/_caffe.cpp b/python/caffe/_caffe.cpp
-index 3589e476..be011699 100644
---- a/python/caffe/_caffe.cpp
-+++ b/python/caffe/_caffe.cpp
-@@ -288,7 +288,7 @@ void Solver_add_callback(Solver<Dtype> * solver, bp::object on_start,
- }
-
- // Seems boost cannot call the base method directly
--void Solver_add_nccl(SGDSolver<Dtype>* solver
-+void Solver_add_nccl(Solver<Dtype>* solver
- #ifdef USE_NCCL
- , NCCL<Dtype>* nccl
- #endif
-diff --git a/src/caffe/layers/hdf5_data_layer.cpp b/src/caffe/layers/hdf5_data_layer.cpp
-index b9a071ce..00716a92 100644
---- a/src/caffe/layers/hdf5_data_layer.cpp
-+++ b/src/caffe/layers/hdf5_data_layer.cpp
-@@ -39,8 +39,9 @@ void HDF5DataLayer<Dtype>::LoadHDF5FileData(const char* filename) {
-
- for (int i = 0; i < top_size; ++i) {
- hdf_blobs_[i] = shared_ptr<Blob<Dtype> >(new Blob<Dtype>());
-+ // Allow reshape here, as we are loading data not params
- hdf5_load_nd_dataset(file_id, this->layer_param_.top(i).c_str(),
-- MIN_DATA_DIM, MAX_DATA_DIM, hdf_blobs_[i].get());
-+ MIN_DATA_DIM, MAX_DATA_DIM, hdf_blobs_[i].get(), true);
- }
-
- herr_t status = H5Fclose(file_id);
-diff --git a/src/caffe/test/test_hdf5_output_layer.cpp b/src/caffe/test/test_hdf5_output_layer.cpp
-index 3833ebff..2bc2de1e 100644
---- a/src/caffe/test/test_hdf5_output_layer.cpp
-+++ b/src/caffe/test/test_hdf5_output_layer.cpp
-@@ -77,10 +77,12 @@ TYPED_TEST(HDF5OutputLayerTest, TestForward) {
- H5P_DEFAULT);
- ASSERT_GE(file_id, 0)<< "Failed to open HDF5 file" <<
- this->input_file_name_;
-+ // Allow reshape here as we are loading data not params
-+ bool reshape = true;
- hdf5_load_nd_dataset(file_id, HDF5_DATA_DATASET_NAME, 0, 4,
-- this->blob_data_);
-+ this->blob_data_, reshape);
- hdf5_load_nd_dataset(file_id, HDF5_DATA_LABEL_NAME, 0, 4,
-- this->blob_label_);
-+ this->blob_label_, reshape);
- herr_t status = H5Fclose(file_id);
- EXPECT_GE(status, 0)<< "Failed to close HDF5 file " <<
- this->input_file_name_;
-@@ -105,12 +107,12 @@ TYPED_TEST(HDF5OutputLayerTest, TestForward) {
-
- Blob<Dtype>* blob_data = new Blob<Dtype>();
- hdf5_load_nd_dataset(file_id, HDF5_DATA_DATASET_NAME, 0, 4,
-- blob_data);
-+ blob_data, reshape);
- this->CheckBlobEqual(*(this->blob_data_), *blob_data);
-
- Blob<Dtype>* blob_label = new Blob<Dtype>();
- hdf5_load_nd_dataset(file_id, HDF5_DATA_LABEL_NAME, 0, 4,
-- blob_label);
-+ blob_label, reshape);
- this->CheckBlobEqual(*(this->blob_label_), *blob_label);
-
- status = H5Fclose(file_id);
-diff --git a/src/caffe/test/test_hdf5data_layer.cpp b/src/caffe/test/test_hdf5data_layer.cpp
-index 68e10286..487f5176 100644
---- a/src/caffe/test/test_hdf5data_layer.cpp
-+++ b/src/caffe/test/test_hdf5data_layer.cpp
-@@ -70,7 +70,7 @@ TYPED_TEST(HDF5DataLayerTest, TestRead) {
- int height = 6;
- int width = 5;
-
-- // Test that the layer setup got the correct parameters.
-+ // Test that the layer setup gives correct parameters.
- HDF5DataLayer<Dtype> layer(param);
- layer.SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
- EXPECT_EQ(this->blob_top_data_->num(), batch_size);
-diff --git a/src/caffe/util/hdf5.cpp b/src/caffe/util/hdf5.cpp
-index d255877b..ed737429 100644
---- a/src/caffe/util/hdf5.cpp
-+++ b/src/caffe/util/hdf5.cpp
-@@ -9,7 +9,7 @@ namespace caffe {
- template <typename Dtype>
- void hdf5_load_nd_dataset_helper(
- hid_t file_id, const char* dataset_name_, int min_dim, int max_dim,
-- Blob<Dtype>* blob) {
-+ Blob<Dtype>* blob, bool reshape) {
- // Verify that the dataset exists.
- CHECK(H5LTfind_dataset(file_id, dataset_name_))
- << "Failed to find HDF5 dataset " << dataset_name_;
-@@ -56,17 +56,38 @@ void hdf5_load_nd_dataset_helper(
- LOG(FATAL) << "Datatype class unknown";
- }
-
-+
- vector<int> blob_dims(dims.size());
- for (int i = 0; i < dims.size(); ++i) {
- blob_dims[i] = dims[i];
- }
-- blob->Reshape(blob_dims);
-+
-+ if (reshape) {
-+ blob->Reshape(blob_dims);
-+ } else {
-+ if (blob_dims != blob->shape()) {
-+ // create shape string for error message
-+ ostringstream stream;
-+ int count = 1;
-+ for (int i = 0; i < blob_dims.size(); ++i) {
-+ stream << blob_dims[i] << " ";
-+ count = count * blob_dims[i];
-+ }
-+ stream << "(" << count << ")";
-+ string source_shape_string = stream.str();
-+
-+ CHECK(blob_dims == blob->shape()) << "Cannot load blob from hdf5; shape "
-+ << "mismatch. Source shape is " << source_shape_string
-+ << " target shape is " << blob->shape_string();
-+ }
-+ }
- }
-
- template <>
- void hdf5_load_nd_dataset<float>(hid_t file_id, const char* dataset_name_,
-- int min_dim, int max_dim, Blob<float>* blob) {
-- hdf5_load_nd_dataset_helper(file_id, dataset_name_, min_dim, max_dim, blob);
-+ int min_dim, int max_dim, Blob<float>* blob, bool reshape) {
-+ hdf5_load_nd_dataset_helper(file_id, dataset_name_, min_dim, max_dim, blob,
-+ reshape);
- herr_t status = H5LTread_dataset_float(
- file_id, dataset_name_, blob->mutable_cpu_data());
- CHECK_GE(status, 0) << "Failed to read float dataset " << dataset_name_;
-@@ -74,8 +95,9 @@ void hdf5_load_nd_dataset<float>(hid_t file_id, const char* dataset_name_,
-
- template <>
- void hdf5_load_nd_dataset<double>(hid_t file_id, const char* dataset_name_,
-- int min_dim, int max_dim, Blob<double>* blob) {
-- hdf5_load_nd_dataset_helper(file_id, dataset_name_, min_dim, max_dim, blob);
-+ int min_dim, int max_dim, Blob<double>* blob, bool reshape) {
-+ hdf5_load_nd_dataset_helper(file_id, dataset_name_, min_dim, max_dim, blob,
-+ reshape);
- herr_t status = H5LTread_dataset_double(
- file_id, dataset_name_, blob->mutable_cpu_data());
- CHECK_GE(status, 0) << "Failed to read double dataset " << dataset_name_;
diff --git a/debian/patches/series b/debian/patches/series
index 6fa1986..e6a2974 100644
--- a/debian/patches/series
+++ b/debian/patches/series
@@ -1,6 +1,4 @@
cmake-using-basic-blas
cmake-fix-python-module-installdir
-fix-more-float-comparison-precision-issue
fix-more-float-comparison-precision-issue2
cmake-link-correct-python-lib.patch
-post_rc5_upstream_updates.patch
--
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