Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23679
Full Canary: https://fburl.com/fblearner/sa1pkpya
Add LambdaRank DCG Loss Option
* when use_idcg_normalization == true, regular LambdaRank with NDCG loss
* when use_idcg_normalization == false, gradient and loss functions are not normalized by idcg.
Differential Revision: D16605459
fbshipit-source-id: a16f071e69516974e48d27bef4ca179019ca4ae7
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22348
This is the last step of LRU hash eviction weight re-init. This diff checks if there's evicted values in sparse_lookup, if so call op created in D15709866 to re-init the values for indicies in evicted_values. Also created gradient op for the operator. The gradient op just passes the output gradient as input gradient.
Reviewed By: itomatik
Differential Revision: D16044736
fbshipit-source-id: 9afb85209b0de1038c5153bcb7dfc5f52e0b2abb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21927
Add `OUTPUT_PROB` output to CTCBeamSearchDecoderOp to return a probability for each sequence.
Add argument to output top-k instead of top-1 decoded sequences.
Reviewed By: SuperIRabbit
Differential Revision: D15797371
fbshipit-source-id: 737ca5cc4f90a0bcc3660ac9f58519a175977b69
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22279
This new operator is used for embedding table weight re-init. After we get the evicted indices, they will be the rows need reseting in embedding table. Then we can create a 1d tensor with default values, and apply this operator to copy the tensor to all evicted rows in embedding table
Will add gradient op in next diff
Reviewed By: itomatik
Differential Revision: D15709866
fbshipit-source-id: 2297b70a7326591524d0be09c73a588da245cc08
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21230
tsia; we support empty tensor with this diff for reshape operator
Reviewed By: jerryzh168
Differential Revision: D15583356
fbshipit-source-id: 6d44c04e95ca3546509bfb12102e29c878f9a7c7
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20868
When `input_boxes_include_bg_cls` is false (which means `input_scores_fg_cls_starting_id` is 0), It doesn't map the class index of score currectly when sorting and limiting the detections over all classes after nms.
Reviewed By: newstzpz
Differential Revision: D15472706
fbshipit-source-id: dc1e808b63ad09fb4bd95acf866771bb3fa92d69
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20802
Need this for sequence model
Reviewed By: dzhulgakov
Differential Revision: D15448529
fbshipit-source-id: cd5abe3b689fc0e02feff10faf8cd61c99369f4f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20502
Following D15307410 removing more floating point exceptions in unit tests
Reviewed By: hx89
Differential Revision: D15340930
fbshipit-source-id: 269fc75e0800bc9d39126767a0f3ca15cd8b0cad
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20501
Fixing unit tests related to optimizer related operators and tests
Reviewed By: hx89
Differential Revision: D15307410
fbshipit-source-id: e5400c26e08f26191ee542fe6b02e0a69bc4e1ae
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20020
Add shape inference for LearningRate op. The output (lr) should have similar shape with input (iteration), but not the same type (float vs int).
Reviewed By: un-disclosed
Differential Revision: D15112300
fbshipit-source-id: 09969aefa15172a6f3c70cd9b2548e3020da5d7a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/19660
Implementation of aggregated Scale operator.
The operator takes a list of tensors as an input and scales all of them them with the argument float value.
The tensor sizes can be different, therefore bookkeeping of the sizes and pointers to the tensors are
necessary for the GPU version of the kernel.
Reviewed By: BIT-silence
Differential Revision: D14984233
fbshipit-source-id: 37cc97159a4f2c38cd6fff4f5710ab7d3a773611
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20044
We do not have a gating functor. This diff adds it. I'm leveraging existing learning rate op because there are other policies I'll need to use as a union together.
* Since there are other policy in LearningRateOp which will be used as a union, I chose to add it as a LearningRateOp.
* constantwarmup cannot do step function of nonzero first and zero later
* There are multiple uses for it,
* e.g. as a gating blob generator that is useful for turning off.
* e.g. as a learning rate switcher at certain iteration.
* For generalizability, no regulation or constraint is applied on the range of the values
* see figure below for illustration
{F157366621}
Reviewed By: ccheng16
Differential Revision: D15178229
fbshipit-source-id: 1e66e9a4bc1bfb946a57f8aefc97d8170f6be731
Summary:
When output blob names are specified while load_all=1, output blob names are ignored. However, this behavior is not documented. In this diff, we just disallow users to provide blob names when load_all=1.
See discussion at https://fb.workplace.com/groups/1405155842844877/permalink/2714909788536136/
Pull Request resolved: https://github.com/pytorch/pytorch/pull/19133
Reviewed By: dzhulgakov
Differential Revision: D14883698
Pulled By: chandlerzuo
fbshipit-source-id: 6e4171e36c4ccc4f857e79da98b858a06b7d8ad6
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/19083
As we have discussed, there are too many of AdjustBatch ops and they incur reallocation overhead and affects the performance. We will eliminate these ops by
- inling the input adjust batch op into Glow
- inling the output adjust batch op into OnnxifiOp and do that only conditionally.
This is the C2 part of the change and requires change from Glow side to work e2e.
Reviewed By: rdzhabarov
Differential Revision: D14860582
fbshipit-source-id: ac2588b894bac25735babb62b1924acc559face6
Summary:
Almost there, feel free to review.
these c10 operators are exported to _caffe2 domain.
TODO:
- [x] let the onnx checker pass
- [x] test tensor list as argument
- [x] test caffe2 backend and converter
- [x] check the c10 schema can be exported to onnx
- [x] refactor the test case to share some code
- [x] fix the problem in ONNX_ATEN_FALLBACK
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18210
Reviewed By: zrphercule
Differential Revision: D14600916
Pulled By: houseroad
fbshipit-source-id: 2592a75f21098fb6ceb38c5d00ee40e9e01cd144
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18155
- Make a python decorator caffe2_flaky for caffe2 operator unit tests.
- The environment variable CAFFE2_RUN_FLAKY_TESTS are now used to mark flaky test mode
During test run,
- If flaky tests mode are on, only flaky tests are run
- If flaky tests mode are off, only non-flaky tests are run
Mark ctc_beam_search_decoder_op_test as flaky
Reviewed By: ezyang, salexspb
Differential Revision: D14468816
fbshipit-source-id: dceb4a48daeb5437ad9cc714bef3343e9761f3a4
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18129
A lot of tensor interference function assume the operator passes the schema.
So call Verity to make sure this is actually the case.
Created diff before to add checking in Concat (https://github.com/pytorch/pytorch/pull/17110), but I encountered lot more places where this is assumed (for example ElementwiseOpShapeInference)
Reviewed By: mdschatz
Differential Revision: D14503933
fbshipit-source-id: cf0097b8c3e4beb1cded6b61e092a6adee4b8fcb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18084
data_strategy parameter was not used in some of unit tests for optimizers
Reviewed By: hyuen
Differential Revision: D14487830
fbshipit-source-id: d757cd06aa2965f4c0570a4a18ba090b98820ef4
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18036
- Add macros to export c10 cuda operators to caffe2 frontend
- Instead of having a separate caffe2 registry for the c10 operator wrappers, use the existing caffe2 registries
Reviewed By: ezyang
Differential Revision: D14467495
fbshipit-source-id: 7715ed2e38d2bbe16f1446ae82c17193a3fabcb9
