Adding regression benchmark for the transformers SHA 3e41cf13fc56335ace852b14decc198557052d4f

raw_results/2023-08-10_09:54:26_3e41cf13fc56335ace852b14decc198557052d4f/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_09:54:26_3e41cf13fc56335ace852b14decc198557052d4f/pytorch_bert_inference/0/inference_results.csv

@@ -0,0 +1,2 @@
+,forward.peak_memory(MB),forward.latency(s),forward.throughput(samples/s)
+0,434,0.00386,259.0

raw_results/2023-08-10_09:54:26_3e41cf13fc56335ace852b14decc198557052d4f/pytorch_bert_inference/0/main.log

@@ -0,0 +1,20 @@
+[2023-08-10 10:53:27,381][benchmark][INFO] - Configuring inference benchmark
+[2023-08-10 10:53:27,382][benchmark][INFO] - 	+ Setting seed(42)
+[2023-08-10 10:53:27,593][pytorch][INFO] - 	+ Infered AutoModel class AutoModelForSequenceClassification for task text-classification and model_type bert
+[2023-08-10 10:53:27,593][backend][INFO] - Configuring pytorch backend
+[2023-08-10 10:53:27,593][backend][INFO] - 	+ Checking initial device isolation
+[2023-08-10 10:53:27,594][backend][INFO] - 	+ Checking contineous device isolation
+[2023-08-10 10:53:27,595][pytorch][INFO] - 	+ Disabling gradients
+[2023-08-10 10:53:27,595][pytorch][INFO] - 	+ Loading pretrained model weights in dtype: None on device: cpu
+[2023-08-10 10:53:28,227][pytorch][INFO] - 	+ Turning on eval mode
+[2023-08-10 10:53:28,228][inference][INFO] - Running inference benchmark
+[2023-08-10 10:53:28,440][dummy_input][INFO] - Generating dummy input for: ['input_ids', 'attention_mask', 'token_type_ids']
+[2023-08-10 10:53:28,441][inference][INFO] - 	+ Tracking forward pass peak memory
+[2023-08-10 10:53:28,498][inference][INFO] - 	+ Forward pass peak memory: 434 (MB)
+[2023-08-10 10:53:28,499][dummy_input][INFO] - Generating dummy input for: ['input_ids', 'attention_mask', 'token_type_ids']
+[2023-08-10 10:53:28,501][inference][INFO] - 	+ Warming up the forward pass
+[2023-08-10 10:53:28,537][inference][INFO] - 	+ Tracking forward pass latency and throughput
+[2023-08-10 10:53:38,632][inference][INFO] - 	+ Forward pass latency: 3.86e-03 (s)
+[2023-08-10 10:53:38,634][inference][INFO] - 	+ Forward pass throughput: 259.00 (samples/s)
+[2023-08-10 10:53:38,634][inference][INFO] - Saving inference results
+[2023-08-10 10:53:38,650][backend][INFO] - Cleaning backend

raw_results/2023-08-10_09:54:26_3e41cf13fc56335ace852b14decc198557052d4f/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_09:54:26_3e41cf13fc56335ace852b14decc198557052d4f/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)
+0,436,0.00396,253.0,0.528,189.0

raw_results/2023-08-10_09:54:26_3e41cf13fc56335ace852b14decc198557052d4f/pytorch_gpt2_inference/0/main.log

@@ -0,0 +1,22 @@
+[2023-08-10 10:53:42,340][benchmark][INFO] - Configuring inference benchmark
+[2023-08-10 10:53:42,341][benchmark][INFO] - 	+ Setting seed(42)
+[2023-08-10 10:53:42,532][pytorch][INFO] - 	+ Infered AutoModel class AutoModelForCausalLM for task text-generation and model_type gpt2
+[2023-08-10 10:53:42,533][backend][INFO] - Configuring pytorch backend
+[2023-08-10 10:53:42,533][backend][INFO] - 	+ Checking initial device isolation
+[2023-08-10 10:53:42,533][backend][INFO] - 	+ Checking contineous device isolation
+[2023-08-10 10:53:42,535][pytorch][INFO] - 	+ Disabling gradients
+[2023-08-10 10:53:42,535][pytorch][INFO] - 	+ Loading pretrained model weights in dtype: None on device: cpu
+[2023-08-10 10:53:43,195][pytorch][INFO] - 	+ Turning on eval mode
+[2023-08-10 10:53:43,196][inference][INFO] - Running inference benchmark
+[2023-08-10 10:53:43,400][inference][INFO] - 	+ Tracking forward pass peak memory
+[2023-08-10 10:53:43,447][inference][INFO] - 	+ Forward pass peak memory: 436 (MB)
+[2023-08-10 10:53:43,448][inference][INFO] - 	+ Warming up the forward pass
+[2023-08-10 10:53:43,481][inference][INFO] - 	+ Tracking forward pass latency and throughput
+[2023-08-10 10:53:53,572][inference][INFO] - 	+ Forward pass latency: 3.96e-03 (s)
+[2023-08-10 10:53:53,574][inference][INFO] - 	+ Forward pass throughput: 253.00 (samples/s)
+[2023-08-10 10:53:53,575][inference][INFO] - 	+ Warming up the generation pass
+[2023-08-10 10:53:54,173][inference][INFO] - 	+ Tracking generation latency and throughput
+[2023-08-10 10:54:04,214][inference][INFO] - 	+ Generation pass latency: 5.28e-01 (s)
+[2023-08-10 10:54:04,215][inference][INFO] - 	+ Generation pass throughput: 189.00 (tokens/s)
+[2023-08-10 10:54:04,215][inference][INFO] - Saving inference results
+[2023-08-10 10:54:04,228][backend][INFO] - Cleaning backend