Adding regression benchmark for the transformers SHA ea5dda22904e807437e07cdfa5d3d89f17a590f7

raw_results/2023-08-09_10:09:09_ea5dda22904e807437e07cdfa5d3d89f17a590f7/pytorch_bert_inference/0/hydra_config.yaml

@@ -0,0 +1,68 @@
+backend:
+  name: pytorch
+  version: 2.0.1+cu117
+  _target_: optimum_benchmark.backends.pytorch.PyTorchBackend
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  initial_isolation_check: true
+  continous_isolation_check: true
+  delete_cache: false
+  no_weights: false
+  torch_dtype: null
+  load_in_8bit: false
+  load_in_4bit: false
+  bettertransformer: false
+  torch_compile: false
+  torch_compile_config:
+    fullgraph: false
+    dynamic: false
+    backend: inductor
+    mode: null
+    options: null
+    disable: false
+  amp_autocast: false
+  amp_dtype: null
+  disable_grad: true
+  eval_mode: true
+benchmark:
+  name: inference
+  _target_: optimum_benchmark.benchmarks.inference.InferenceBenchmark
+  seed: 42
+  memory: false
+  warmup_runs: 10
+  benchmark_duration: 10
+  input_shapes:
+    batch_size: 1
+    sequence_length: 16
+    num_choices: 4
+    width: 64
+    height: 64
+    num_channels: 3
+    point_batch_size: 3
+    nb_points_per_image: 2
+    feature_size: 80
+    nb_max_frames: 3000
+    audio_sequence_length: 16000
+  new_tokens: 100
+experiment_name: pytorch_bert_inference
+model: hf-internal-testing/tiny-random-bert
+device: cpu
+task: text-classification
+hub_kwargs:
+  revision: main
+  cache_dir: null
+  force_download: false
+  local_files_only: false
+  use_auth_token: false
+environment:
+  optimum_version: 1.11.0
+  transformers_version: 4.32.0.dev0
+  transformers_commit: null
+  accelerate_version: 0.21.0
+  accelerate_commit: null
+  diffusers_version: null
+  python_version: 3.10.12
+  system: Linux
+  cpu: ' Intel(R) Xeon(R) Platinum 8275CL CPU @ 3.00GHz'
+  cpu_count: 96
+  cpu_ram_mb: 1148738

raw_results/2023-08-09_10:09:09_ea5dda22904e807437e07cdfa5d3d89f17a590f7/pytorch_bert_inference/0/inference_results.csv

@@ -0,0 +1,2 @@
+,forward.latency(s),forward.throughput(samples/s)
+0,0.00302,331.0

raw_results/2023-08-09_10:09:09_ea5dda22904e807437e07cdfa5d3d89f17a590f7/pytorch_bert_inference/0/main.log

@@ -0,0 +1,17 @@
+[2023-08-09 10:49:43,795][benchmark][INFO] - Configuring inference benchmark
+[2023-08-09 10:49:43,796][benchmark][INFO] - 	+ Setting seed(42)
+[2023-08-09 10:49:43,973][pytorch][INFO] - 	+ Infered AutoModel class AutoModelForSequenceClassification for task text-classification and model_type bert
+[2023-08-09 10:49:43,973][backend][INFO] - Configuring pytorch backend
+[2023-08-09 10:49:43,973][backend][INFO] - 	+ Checking initial device isolation
+[2023-08-09 10:49:43,973][backend][INFO] - 	+ Checking contineous device isolation
+[2023-08-09 10:49:43,974][pytorch][INFO] - 	+ Disabling gradients
+[2023-08-09 10:49:43,974][pytorch][INFO] - 	+ Loading pretrained model weights in dtype: None on device: cpu
+[2023-08-09 10:49:44,571][pytorch][INFO] - 	+ Turning on eval mode
+[2023-08-09 10:49:44,571][inference][INFO] - Running inference benchmark
+[2023-08-09 10:49:44,692][dummy_input][INFO] - Generating dummy input for: ['input_ids', 'attention_mask', 'token_type_ids']
+[2023-08-09 10:49:44,694][inference][INFO] - 	+ Warming up the forward pass
+[2023-08-09 10:49:44,742][inference][INFO] - 	+ Tracking forward pass latency and throughput
+[2023-08-09 10:49:54,856][inference][INFO] - 	+ Forward pass latency: 3.02e-03 (s)
+[2023-08-09 10:49:54,858][inference][INFO] - 	+ Forward pass throughput: 331.00 (samples/s)
+[2023-08-09 10:49:54,859][inference][INFO] - Saving inference results
+[2023-08-09 10:49:54,870][backend][INFO] - Cleaning backend

raw_results/2023-08-09_10:09:09_ea5dda22904e807437e07cdfa5d3d89f17a590f7/pytorch_gpt2_inference/0/hydra_config.yaml

@@ -0,0 +1,68 @@
+backend:
+  name: pytorch
+  version: 2.0.1+cu117
+  _target_: optimum_benchmark.backends.pytorch.PyTorchBackend
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  initial_isolation_check: true
+  continous_isolation_check: true
+  delete_cache: false
+  no_weights: false
+  torch_dtype: null
+  load_in_8bit: false
+  load_in_4bit: false
+  bettertransformer: false
+  torch_compile: false
+  torch_compile_config:
+    fullgraph: false
+    dynamic: false
+    backend: inductor
+    mode: null
+    options: null
+    disable: false
+  amp_autocast: false
+  amp_dtype: null
+  disable_grad: true
+  eval_mode: true
+benchmark:
+  name: inference
+  _target_: optimum_benchmark.benchmarks.inference.InferenceBenchmark
+  seed: 42
+  memory: false
+  warmup_runs: 10
+  benchmark_duration: 10
+  input_shapes:
+    batch_size: 1
+    sequence_length: 16
+    num_choices: 4
+    width: 64
+    height: 64
+    num_channels: 3
+    point_batch_size: 3
+    nb_points_per_image: 2
+    feature_size: 80
+    nb_max_frames: 3000
+    audio_sequence_length: 16000
+  new_tokens: 100
+experiment_name: pytorch_gpt2_inference
+model: hf-internal-testing/tiny-random-gpt2
+device: cpu
+task: text-generation
+hub_kwargs:
+  revision: main
+  cache_dir: null
+  force_download: false
+  local_files_only: false
+  use_auth_token: false
+environment:
+  optimum_version: 1.11.0
+  transformers_version: 4.32.0.dev0
+  transformers_commit: null
+  accelerate_version: 0.21.0
+  accelerate_commit: null
+  diffusers_version: null
+  python_version: 3.10.12
+  system: Linux
+  cpu: ' Intel(R) Xeon(R) Platinum 8275CL CPU @ 3.00GHz'
+  cpu_count: 96
+  cpu_ram_mb: 1148738

raw_results/2023-08-09_10:09:09_ea5dda22904e807437e07cdfa5d3d89f17a590f7/pytorch_gpt2_inference/0/inference_results.csv

@@ -0,0 +1,2 @@
+,forward.latency(s),forward.throughput(samples/s),generate.latency(s),generate.throughput(tokens/s)
+0,0.00352,284.0,0.497,201.0

raw_results/2023-08-09_10:09:09_ea5dda22904e807437e07cdfa5d3d89f17a590f7/pytorch_gpt2_inference/0/main.log

@@ -0,0 +1,20 @@
+[2023-08-09 10:49:58,442][benchmark][INFO] - Configuring inference benchmark
+[2023-08-09 10:49:58,443][benchmark][INFO] - 	+ Setting seed(42)
+[2023-08-09 10:49:58,615][pytorch][INFO] - 	+ Infered AutoModel class AutoModelForCausalLM for task text-generation and model_type gpt2
+[2023-08-09 10:49:58,616][backend][INFO] - Configuring pytorch backend
+[2023-08-09 10:49:58,616][backend][INFO] - 	+ Checking initial device isolation
+[2023-08-09 10:49:58,616][backend][INFO] - 	+ Checking contineous device isolation
+[2023-08-09 10:49:58,618][pytorch][INFO] - 	+ Disabling gradients
+[2023-08-09 10:49:58,618][pytorch][INFO] - 	+ Loading pretrained model weights in dtype: None on device: cpu
+[2023-08-09 10:49:59,566][pytorch][INFO] - 	+ Turning on eval mode
+[2023-08-09 10:49:59,567][inference][INFO] - Running inference benchmark
+[2023-08-09 10:49:59,785][inference][INFO] - 	+ Warming up the forward pass
+[2023-08-09 10:49:59,824][inference][INFO] - 	+ Tracking forward pass latency and throughput
+[2023-08-09 10:50:09,926][inference][INFO] - 	+ Forward pass latency: 3.52e-03 (s)
+[2023-08-09 10:50:09,927][inference][INFO] - 	+ Forward pass throughput: 284.00 (samples/s)
+[2023-08-09 10:50:09,928][inference][INFO] - 	+ Warming up the generation pass
+[2023-08-09 10:50:10,514][inference][INFO] - 	+ Tracking generation latency and throughput
+[2023-08-09 10:50:20,951][inference][INFO] - 	+ Generation pass latency: 4.97e-01 (s)
+[2023-08-09 10:50:20,952][inference][INFO] - 	+ Generation pass throughput: 201.00 (tokens/s)
+[2023-08-09 10:50:20,952][inference][INFO] - Saving inference results
+[2023-08-09 10:50:20,964][backend][INFO] - Cleaning backend