Adding regression benchmark for the transformers SHA b175fc39d93512204e7e784bd5b4f6c87580d54b

raw_results/2023-08-10_07:13:52_b175fc39d93512204e7e784bd5b4f6c87580d54b/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: true
+  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/2023-08-10_07:13:52_b175fc39d93512204e7e784bd5b4f6c87580d54b/pytorch_bert_inference/0/inference_results.csv

@@ -0,0 +1,2 @@
+,forward.peak_memory(MB),forward.latency(s),forward.throughput(samples/s)
+0,433,0.00316,316.0

raw_results/2023-08-10_07:13:52_b175fc39d93512204e7e784bd5b4f6c87580d54b/pytorch_bert_inference/0/main.log

@@ -0,0 +1,20 @@
+[2023-08-10 08:49:27,936][benchmark][INFO] - Configuring inference benchmark
+[2023-08-10 08:49:27,937][benchmark][INFO] - 	+ Setting seed(42)
+[2023-08-10 08:49:28,130][pytorch][INFO] - 	+ Infered AutoModel class AutoModelForSequenceClassification for task text-classification and model_type bert
+[2023-08-10 08:49:28,131][backend][INFO] - Configuring pytorch backend
+[2023-08-10 08:49:28,131][backend][INFO] - 	+ Checking initial device isolation
+[2023-08-10 08:49:28,131][backend][INFO] - 	+ Checking contineous device isolation
+[2023-08-10 08:49:28,132][pytorch][INFO] - 	+ Disabling gradients
+[2023-08-10 08:49:28,132][pytorch][INFO] - 	+ Loading pretrained model weights in dtype: None on device: cpu
+[2023-08-10 08:49:28,799][pytorch][INFO] - 	+ Turning on eval mode
+[2023-08-10 08:49:28,800][inference][INFO] - Running inference benchmark
+[2023-08-10 08:49:28,928][dummy_input][INFO] - Generating dummy input for: ['input_ids', 'attention_mask', 'token_type_ids']
+[2023-08-10 08:49:28,930][inference][INFO] - 	+ Tracking forward pass peak memory
+[2023-08-10 08:49:28,989][inference][INFO] - 	+ Forward pass peak memory: 433 (MB)
+[2023-08-10 08:49:28,990][dummy_input][INFO] - Generating dummy input for: ['input_ids', 'attention_mask', 'token_type_ids']
+[2023-08-10 08:49:28,992][inference][INFO] - 	+ Warming up the forward pass
+[2023-08-10 08:49:29,030][inference][INFO] - 	+ Tracking forward pass latency and throughput
+[2023-08-10 08:49:39,142][inference][INFO] - 	+ Forward pass latency: 3.16e-03 (s)
+[2023-08-10 08:49:39,145][inference][INFO] - 	+ Forward pass throughput: 316.00 (samples/s)
+[2023-08-10 08:49:39,145][inference][INFO] - Saving inference results
+[2023-08-10 08:49:39,160][backend][INFO] - Cleaning backend

raw_results/2023-08-10_07:13:52_b175fc39d93512204e7e784bd5b4f6c87580d54b/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: true
+  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/2023-08-10_07:13:52_b175fc39d93512204e7e784bd5b4f6c87580d54b/pytorch_gpt2_inference/0/inference_results.csv

@@ -0,0 +1,2 @@
+,forward.peak_memory(MB),forward.latency(s),forward.throughput(samples/s),generate.latency(s),generate.throughput(tokens/s)
+0,436,0.00373,268.0,0.485,206.0

raw_results/2023-08-10_07:13:52_b175fc39d93512204e7e784bd5b4f6c87580d54b/pytorch_gpt2_inference/0/main.log

@@ -0,0 +1,22 @@
+[2023-08-10 08:49:42,937][benchmark][INFO] - Configuring inference benchmark
+[2023-08-10 08:49:42,938][benchmark][INFO] - 	+ Setting seed(42)
+[2023-08-10 08:49:43,127][pytorch][INFO] - 	+ Infered AutoModel class AutoModelForCausalLM for task text-generation and model_type gpt2
+[2023-08-10 08:49:43,128][backend][INFO] - Configuring pytorch backend
+[2023-08-10 08:49:43,128][backend][INFO] - 	+ Checking initial device isolation
+[2023-08-10 08:49:43,128][backend][INFO] - 	+ Checking contineous device isolation
+[2023-08-10 08:49:43,129][pytorch][INFO] - 	+ Disabling gradients
+[2023-08-10 08:49:43,130][pytorch][INFO] - 	+ Loading pretrained model weights in dtype: None on device: cpu
+[2023-08-10 08:49:43,801][pytorch][INFO] - 	+ Turning on eval mode
+[2023-08-10 08:49:43,802][inference][INFO] - Running inference benchmark
+[2023-08-10 08:49:44,011][inference][INFO] - 	+ Tracking forward pass peak memory
+[2023-08-10 08:49:44,062][inference][INFO] - 	+ Forward pass peak memory: 436 (MB)
+[2023-08-10 08:49:44,064][inference][INFO] - 	+ Warming up the forward pass
+[2023-08-10 08:49:44,100][inference][INFO] - 	+ Tracking forward pass latency and throughput
+[2023-08-10 08:49:54,198][inference][INFO] - 	+ Forward pass latency: 3.73e-03 (s)
+[2023-08-10 08:49:54,201][inference][INFO] - 	+ Forward pass throughput: 268.00 (samples/s)
+[2023-08-10 08:49:54,202][inference][INFO] - 	+ Warming up the generation pass
+[2023-08-10 08:49:54,792][inference][INFO] - 	+ Tracking generation latency and throughput
+[2023-08-10 08:50:04,982][inference][INFO] - 	+ Generation pass latency: 4.85e-01 (s)
+[2023-08-10 08:50:04,983][inference][INFO] - 	+ Generation pass throughput: 206.00 (tokens/s)
+[2023-08-10 08:50:04,983][inference][INFO] - Saving inference results
+[2023-08-10 08:50:04,996][backend][INFO] - Cleaning backend