Add permute_duplicate_pooled_embeddings op #1912
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: a398bc495e3461abc429974dc6d2212e0178e59d
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: 99a9d88a2f1ada30dd41c24b4df97745c5e108d8
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: 9ca8cfa7b066c84d20e3618b073bcd66627c32ee
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: 03f3792cc2309e5dae5af4532887e29ce0e07cd4
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: e66734ca9e6e105dbe0031025239ae585063c255
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: 922e8c472c3ffb42f23c36dd38c67a3dffa8e119
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: 96edf038b8c991b0331e05a0ec5a84d9e35bcf91
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: f8dd2cce92b768c2c1269d071d32fa795e6bf29e
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: 87fbb41662af0c8bb6cba0b6ecc8aa6f06b3d30c
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Differential Revision: D48090591 fbshipit-source-id: daa9b037786e44123afad875b05ab68792fbd2ab
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Reviewed By: sryap Differential Revision: D48090591 fbshipit-source-id: e649a33d6b5ff70733e37bd96e9419328c3c0624
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Reviewed By: sryap Differential Revision: D48090591 fbshipit-source-id: e12c85ab1ce9066a8cc4eb7bd29759d5c4a5be6c
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Reviewed By: sryap Differential Revision: D48090591 fbshipit-source-id: d484cd779edb37f9c3a4bb0af1725aa7960c03cd
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Reviewed By: sryap Differential Revision: D48090591 fbshipit-source-id: 083b519187afdb7ae9a75be68c7e5725b6968194
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Reviewed By: sryap Differential Revision: D48090591 fbshipit-source-id: bb202c905728d01171a642ae0722d0aa97f25af7
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Reviewed By: sryap Differential Revision: D48090591 fbshipit-source-id: 4096408033988ab17e0ca3c76a661e4bce6d8fde
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Reviewed By: sryap Differential Revision: D48090591 fbshipit-source-id: ebb5a15ae0a5cf9b0b03b6b5be78360838e05849
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Summary: Pull Request resolved: pytorch#1912 # Background Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation. # Details The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list. Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] Offset_dims: [0, 2, 5, 6, 10] Permute: [3, 0, 2, 1, 3] Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9] # Backwards Compatibility The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu. # Documentation [Link](https://docs.google.com/document/d/1rp31nhcRuVmh8RVbWcktL3Hq-0ccc84AYL4nVegDywI) Reviewed By: sryap Differential Revision: D48090591 fbshipit-source-id: 54fce7365a7608a175b0eb0de9484a829fe2cd34
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This pull request was exported from Phabricator. Differential Revision: D48090591 |
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This pull request has been merged in 9d221b7. |
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Summary:
Background
Currently permute_pooled_embs_gpu does not support duplicates in a permutation, this poses a problem with passing the same embeddings to multiple modules. This doc proposes a solution to allow duplicate subsets in the resultant permutation.
Details
The required implementation of permute_duplicate_pooled_embs_gpu should support a subset being repeated. This is represented by having duplicates in the permute list. This also results in the output list size being greater than the input list.
Input: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
Offset_dims: [0, 2, 5, 6, 10]
Permute: [3, 0, 2, 1, 3]
Output: [6, 7, 8, 9, 0, 1, 5, 2, 3, 4, 6, 7, 8, 9]
Backwards Compatibility
The permute_duplicate_pooled_embs_gpu is backwards compatible with the permute_pooled_embs_gpu (non duplicate permutations) use case, hence any use of permute_pooled_embs_gpu in the inference path can be replaced with permute_duplicate_pooled_embs_gpu.
Documentation
Link
Differential Revision: D48090591