Skip to content
This repository was archived by the owner on Nov 22, 2022. It is now read-only.

Beam Search + Top K Metrics #247

Closed
wants to merge 1 commit into from

Conversation

emilysw
Copy link

@emilysw emilysw commented Jan 27, 2019

Summary:
Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Differential Revision: D13219339

@facebook-github-bot facebook-github-bot added the CLA Signed Do not delete this pull request or issue due to inactivity. label Jan 27, 2019
@emilysw emilysw force-pushed the export-D13219339 branch 2 times, most recently from f0045b3 to 52cc381 Compare January 27, 2019 20:06
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 27, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Differential Revision: D13219339

fbshipit-source-id: ef9cbe257f7f3444cb72e4aa5719e6de33a747a3
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 28, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Differential Revision: D13219339

fbshipit-source-id: 2c1fc51c06a764d746f31135fe8b76a9f976ca05
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 29, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Differential Revision: D13219339

fbshipit-source-id: b2307ebe171658f482aa936e91e02ff8f04832a5
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 29, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Differential Revision: D13219339

fbshipit-source-id: 923a1550d72745a0d49a6bff0280458ebe3dec77
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 29, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Differential Revision: D13219339

fbshipit-source-id: 5edf7ff1ad1777d1c7f0ff6a89058d2ee648f418
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 30, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Reviewed By: wowitsmrinal

Differential Revision: D13219339

fbshipit-source-id: f8bddddb8ec9809506e3c97d3d4bd3f0e7615fbc
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 30, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Reviewed By: wowitsmrinal

Differential Revision: D13219339

fbshipit-source-id: 0490b4358a2d89ae67ffb5ddc5ba199dd056de62
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 30, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Reviewed By: wowitsmrinal

Differential Revision: D13219339

fbshipit-source-id: 8105283f0c6bf51305865ddf6b330a19a9d81e02
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 30, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Reviewed By: wowitsmrinal

Differential Revision: D13219339

fbshipit-source-id: ba4d2e34230380f259ae84a568c278a43aa1f325
emilysw pushed a commit to emilysw/pytext that referenced this pull request Jan 30, 2019
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Reviewed By: wowitsmrinal

Differential Revision: D13219339

fbshipit-source-id: 4c9574eb127bd3df1407be92080dbf00eb51fd22
Summary:
Pull Request resolved: facebookresearch#247

Implemented beam search (non-parallelized) for RNNG C++. Previously, the Parser's forward pass returned a single vector {predictedActionsIdx_, action_scores}. Now, the Parser's forward pass returns a vector of top k {predictedActionsIdx_, action_scores} vectors.

Also, implemented metrics for evaluating the top K frame accuracy. For each test example, top k frame accuracy is defined as at least 1 exact match between the expected frame and one of the top k frame predictions.

With higher beam size, top K frame accuracy increases for RNNG, but latency also increases.

Reviewed By: wowitsmrinal

Differential Revision: D13219339

fbshipit-source-id: 4749d485ce1df2678aa5a69426f3fc0eb13d76d9
Sign up for free to subscribe to this conversation on GitHub. Already have an account? Sign in.
Labels
CLA Signed Do not delete this pull request or issue due to inactivity.
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants