frozenleaves/pytorch
1
0
Fork 0
mirror of https://github.com/pytorch/pytorch.git synced 2025-10-22 22:25:10 +08:00
Code Issues Packages Projects Releases Wiki Activity

[C++ API] Remove deprecated torch::nn::BatchNorm / FeatureDropout / modules_ordered_dict and torch::nn::init::Nonlinearity / FanMode (#34508)

Browse Source 
Summary:
This PR is BC-breaking in the following way:
- The deprecated `torch::nn::BatchNorm` is removed in favor of `torch::nn::BatchNorm{1,2,3}d`
- The deprecated `torch::nn::FeatureDropout` is removed in favor of `torch::nn::Dropout{2,3}d`
- The deprecated `torch::nn::modules_ordered_dict` is removed. User should do `Sequential sequential({{"m1", MyModule(1)}, {"m2", MyModule(2)}})` instead.
- The deprecated `torch::nn::init::Nonlinearity` is removed, in favor of the following enums:
    - `torch::kLinear`
    - `torch::kConv1D`
    - `torch::kConv2D`
    - `torch::kConv3D`
    - `torch::kConvTranspose1D`
    - `torch::kConvTranspose2D`
    - `torch::kConvTranspose3D`
    - `torch::kSigmoid`
    - `torch::kTanh`
    - `torch::kReLU`
    - `torch::kLeakyReLU`
- The deprecated `torch::nn::init::FanMode` is removed, in favor of the following enums:
    - `torch::kFanIn`
    - `torch::kFanOut`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34508

Differential Revision: D20351601

Pulled By: yf225

fbshipit-source-id: cca0cd112f29a31bb023e348ca8f82780e42bea3
This commit is contained in:
Will Feng
2020-03-12 10:07:03 -07:00
committed by Facebook GitHub Bot
parent e95657b87e
commit a54416d208
19 changed files with 32 additions and 493 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
test/cpp/api/modulelist.cpp
View File

@ -158,7 +158,7 @@ TEST_F(ModuleListTest, SanityCheckForHoldingStandardModules) {
Linear(10, 3),
Conv2d(1, 2, 3),
Dropout(0.5),
BatchNorm(5),
BatchNorm2d(5),
Embedding(4, 10),
LSTM(4, 5));
}
@ -210,7 +210,7 @@ TEST_F(ModuleListTest, HasReferenceSemantics) {
}
TEST_F(ModuleListTest, IsCloneable) {
ModuleList list(Linear(3, 4), Functional(torch::relu), BatchNorm(3));
ModuleList list(Linear(3, 4), Functional(torch::relu), BatchNorm1d(3));
ModuleList clone = std::dynamic_pointer_cast<ModuleListImpl>(list->clone());
ASSERT_EQ(list->size(), clone->size());
@ -255,7 +255,7 @@ TEST_F(ModuleListTest, NestingIsPossible) {
}
TEST_F(ModuleListTest, CloneToDevice_CUDA) {
ModuleList list(Linear(3, 4), Functional(torch::relu), BatchNorm(3));
ModuleList list(Linear(3, 4), Functional(torch::relu), BatchNorm1d(3));
torch::Device device(torch::kCUDA, 0);
ModuleList clone =
std::dynamic_pointer_cast<ModuleListImpl>(list->clone(device));
@ -272,7 +272,7 @@ TEST_F(ModuleListTest, PrettyPrintModuleList) {
Linear(10, 3),
Conv2d(1, 2, 3),
Dropout(0.5),
BatchNorm(5),
BatchNorm2d(5),
Embedding(4, 10),
LSTM(4, 5));
ASSERT_EQ(
@ -281,7 +281,7 @@ TEST_F(ModuleListTest, PrettyPrintModuleList) {
" (0): torch::nn::Linear(in_features=10, out_features=3, bias=true)\n"
" (1): torch::nn::Conv2d(1, 2, kernel_size=[3, 3], stride=[1, 1])\n"
" (2): torch::nn::Dropout(p=0.5, inplace=false)\n"
" (3): torch::nn::BatchNorm(num_features=5, eps=1e-05, momentum=0.1, affine=true, track_running_stats=true)\n"
" (3): torch::nn::BatchNorm2d(5, eps=1e-05, momentum=0.1, affine=true, track_running_stats=true)\n"
" (4): torch::nn::Embedding(num_embeddings=4, embedding_dim=10)\n"
" (5): torch::nn::LSTM(input_size=4, hidden_size=5, layers=1, dropout=0)\n"
")");
@ -290,7 +290,7 @@ TEST_F(ModuleListTest, PrettyPrintModuleList) {
TEST_F(ModuleListTest, RangeBasedForLoop) {
torch::nn::ModuleList mlist(
torch::nn::Linear(3, 4),
torch::nn::BatchNorm(4),
torch::nn::BatchNorm1d(4),
torch::nn::Dropout(0.5)
);