add embeddingbag operator the the benchmark suite (#29784)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/29784
Add embeddingbag operator to the benchmark suite with different number of embeddings, dims, and inputs.
Test Plan:
```
buck run //caffe2/benchmarks/operator_benchmark/pt:embeddingbag_test -- --iterations 1
# ----------------------------------------
# PyTorch/Caffe2 Operator Micro-benchmarks
# ----------------------------------------
# Tag : short
# Benchmarking PyTorch: embeddingbag
# Mode: Eager
# Name: embeddingbag_embeddingbags2300_dim64_modesum_input_size16_offset0_sparseTrue
# Input: embeddingbags: 2300, dim: 64, mode: sum, input_size: 16, offset: 0, sparse: True
Forward Execution Time (us) : 624.838
# Benchmarking PyTorch: embeddingbag
# Mode: Eager
# Name: embeddingbag_embeddingbags2300_dim64_modesum_input_size64_offset0_sparseTrue
# Input: embeddingbags: 2300, dim: 64, mode: sum, input_size: 64, offset: 0, sparse: True
Forward Execution Time (us) : 636.744
# Benchmarking PyTorch: embeddingbag
# Mode: Eager
# Name: embeddingbag_embeddingbags80_dim64_modesum_input_size8_offset0_sparseTrue
# Input: embeddingbags: 80, dim: 64, mode: sum, input_size: 8, offset: 0, sparse: True
Backward Execution Time (us) : 2325.291
# Benchmarking PyTorch: embeddingbag
# Mode: Eager
# Name: embeddingbag_embeddingbags80_dim64_modesum_input_size16_offset0_sparseTrue
# Input: embeddingbags: 80, dim: 64, mode: sum, input_size: 16, offset: 0, sparse: True
Backward Execution Time (us) : 2528.658
...
Reviewed By: bddppq
Differential Revision: D18496340
fbshipit-source-id: 157dcff2ea4ec13416fe161382fcefd47ce4cc01
