#0: Update copyright year to 2024

CONTRIBUTING.md

@@ -476,7 +476,7 @@ To set up pre-commit on your local machine, follow these steps:
   scripts. For Python files, we are to use this convention:
 
   ```
-  # SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+  # SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
   # SPDX-License-Identifier: Apache-2.0
   ```
@@ -485,7 +485,7 @@ To set up pre-commit on your local machine, follow these steps:
   convention:
 
   ```
-  // SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+  // SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
   //
   // SPDX-License-Identifier: Apache-2.0
   ```

conftest.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

docs/source/conf.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

docs/source/tt-metalium/conf.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

docs/source/tt-metalium/tools/device_program_profiler.rst

@@ -56,7 +56,7 @@ The kernel code for full buffer is in ``{$TT_METAL_HOME}/tt_metal/programming_ex
 ..  code-block:: c++
     :linenos:
 
-    // SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+    // SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
     //
     // SPDX-License-Identifier: Apache-2.0
 

docs/source/ttnn/conf.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

infra/data_collection/cicd.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

infra/data_collection/github/utils.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

infra/data_collection/github/workflows.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

infra/data_collection/junit_xml_utils.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

infra/machine_setup/scripts/setup_hugepages.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/common/lightweightmodule.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/common/rmsnorm.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 import ttnn

models/common/tests/test_rmsnorm.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 import os

models/conftest.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/datasets/dataset_squadv2.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 
@@ -8,10 +8,20 @@
 from datasets import load_dataset
 from loguru import logger
 
+
 class SQUADV2Dataset(Dataset):
     """Configurable SQuad-V2 Dataset."""
 
-    def __init__(self, dataset_question: Any , dataset_context: Any, dataset_reference: Any, tokenizer: Any, seq_len: int, attention_mask: bool, token_type_ids: bool):
+    def __init__(
+        self,
+        dataset_question: Any,
+        dataset_context: Any,
+        dataset_reference: Any,
+        tokenizer: Any,
+        seq_len: int,
+        attention_mask: bool,
+        token_type_ids: bool,
+    ):
         """Init and preprocess SST-2 dataset.
 
         Parameters
@@ -30,7 +40,8 @@ def __init__(self, dataset_question: Any , dataset_context: Any, dataset_referen
 
         self.data = []
         for i in range(len(dataset_question)):
-            self.data.append((
+            self.data.append(
+                (
                     tokenizer.batch_encode_plus(
                         zip(dataset_question[i], dataset_context[i]),
                         max_length=seq_len,
@@ -39,13 +50,12 @@ def __init__(self, dataset_question: Any , dataset_context: Any, dataset_referen
                         return_attention_mask=attention_mask,
                         return_token_type_ids=token_type_ids,
                         return_tensors="pt",
-                    )
-                    , dataset_reference[i]
-                    , dataset_question[i]
-                    , dataset_context[i])
+                    ),
+                    dataset_reference[i],
+                    dataset_question[i],
+                    dataset_context[i],
                 )
-
-
+            )
 
     def __len__(self):
         """Return length of dataset.
@@ -74,19 +84,18 @@ def __getitem__(self, index: int):
         return X
 
 
-
 def squad_divide_chunks(dataset_question, dataset_context, dataset_reference, batch):
     dataset_question_b = []
     dataset_context_b = []
     dataset_reference_b = []
     for i in range(0, len(dataset_question), batch):
-        dataset_question_b.append(dataset_question[i:i + batch])
-        dataset_context_b.append(dataset_context[i:i + batch])
-        dataset_reference_b.append(dataset_reference[i:i + batch])
+        dataset_question_b.append(dataset_question[i : i + batch])
+        dataset_context_b.append(dataset_context[i : i + batch])
+        dataset_reference_b.append(dataset_reference[i : i + batch])
     return dataset_question_b, dataset_context_b, dataset_reference_b
 
 
-def squadv2_1K_samples_input(tokenizer, seq_len, attention_mask, token_type_ids,  microbatch=8):
+def squadv2_1K_samples_input(tokenizer, seq_len, attention_mask, token_type_ids, microbatch=8):
     squadv2_dataset = load_dataset("squad_v2", use_auth_token=False, streaming=True)["validation"]
     # squadv2_dataset = load_dataset("squad_v2", use_auth_token=True, streaming=True)["validation"]
 
@@ -97,23 +106,33 @@ def squadv2_1K_samples_input(tokenizer, seq_len, attention_mask, token_type_ids,
 
     for _ in range(2048):
         dataset_sgl = next(dataset_iter)
-        if len(dataset_sgl['answers']['text']) > 0:
-            dataset_question.append(dataset_sgl['question'])
-            dataset_context.append(dataset_sgl['context'])
-            dataset_reference.append({'answers': dataset_sgl['answers'], 'id': dataset_sgl['id']})
+        if len(dataset_sgl["answers"]["text"]) > 0:
+            dataset_question.append(dataset_sgl["question"])
+            dataset_context.append(dataset_sgl["context"])
+            dataset_reference.append({"answers": dataset_sgl["answers"], "id": dataset_sgl["id"]})
         if len(dataset_question) == 1024:
             logger.info("SQuADv2 1024 samples load ..done")
             break
 
-    dataset_question, dataset_context, dataset_reference = squad_divide_chunks(dataset_question, dataset_context, dataset_reference, microbatch)
-    dataset_processed = SQUADV2Dataset(dataset_question, dataset_context, dataset_reference, tokenizer=tokenizer, seq_len=seq_len, attention_mask=attention_mask, token_type_ids=token_type_ids)
+    dataset_question, dataset_context, dataset_reference = squad_divide_chunks(
+        dataset_question, dataset_context, dataset_reference, microbatch
+    )
+    dataset_processed = SQUADV2Dataset(
+        dataset_question,
+        dataset_context,
+        dataset_reference,
+        tokenizer=tokenizer,
+        seq_len=seq_len,
+        attention_mask=attention_mask,
+        token_type_ids=token_type_ids,
+    )
 
     return dataset_processed
 
 
-
-def squadv2_answer_decode_batch(HF_model, tokenizer, nlp, references, cpu_out, tt_untilized_output, BATCH_SIZE, question, context):
-
+def squadv2_answer_decode_batch(
+    HF_model, tokenizer, nlp, references, cpu_out, tt_untilized_output, BATCH_SIZE, question, context
+):
     tt_predictions = []
     cpu_predictions = []
 
@@ -123,7 +142,6 @@ def squadv2_answer_decode_batch(HF_model, tokenizer, nlp, references, cpu_out, t
     examples = nlp._args_parser(input_q)
 
     for i in range(BATCH_SIZE):
-
         logger.info(f"--REF-- {references[i]['answers']['text']}")
 
         answer_start_scores = cpu_out["start_logits"][i]
@@ -144,25 +162,29 @@ def squadv2_answer_decode_batch(HF_model, tokenizer, nlp, references, cpu_out, t
         }
 
         pt_res = {
-                    "start": answer_start_scores,
-                    "end": answer_end_scores,
-                    "example": single_input["example"],
-                    **single_input["inputs"],
-                }
+            "start": answer_start_scores,
+            "end": answer_end_scores,
+            "example": single_input["example"],
+            **single_input["inputs"],
+        }
         cpu_answer_nlp = nlp.postprocess([pt_res], **postprocess_params)["answer"]
 
         tt_res = {
-                    "start": tt_start_logits,
-                    "end": tt_end_logits,
-                    "example": single_input["example"],
-                    **single_input["inputs"],
-                }
+            "start": tt_start_logits,
+            "end": tt_end_logits,
+            "example": single_input["example"],
+            **single_input["inputs"],
+        }
         tt_answer_nlp = nlp.postprocess([tt_res], **postprocess_params)["answer"]
 
         logger.info(f"--CPU-- {cpu_answer_nlp}")
         logger.info(f"--TT--- {tt_answer_nlp}")
         logger.info(f"=======")
-        cpu_predictions.append({'prediction_text': cpu_answer_nlp, 'id': references[i]['id'], 'no_answer_probability': 0.})
-        tt_predictions.append({'prediction_text': tt_answer_nlp, 'id': references[i]['id'], 'no_answer_probability': 0.})
+        cpu_predictions.append(
+            {"prediction_text": cpu_answer_nlp, "id": references[i]["id"], "no_answer_probability": 0.0}
+        )
+        tt_predictions.append(
+            {"prediction_text": tt_answer_nlp, "id": references[i]["id"], "no_answer_probability": 0.0}
+        )
 
     return cpu_predictions, tt_predictions

models/datasets/llm_dataset_utils.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert/demo/demo.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert/reference/torch_bert.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert/tests/test_perf_device_bert.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert/tests/test_ttnn_optimized_bert.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert/tt/ttnn_bert.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert/tt/ttnn_optimized_bert.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert/tt/ttnn_optimized_sharded_bert.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert_tiny/demo/demo.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert_tiny/tests/test_performance.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/bert_tiny/tt/bert_tiny.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/convnet_mnist/convnet_mnist_preprocessing.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/convnet_mnist/convnet_mnist_utils.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/convnet_mnist/demo/demo.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/convnet_mnist/tests/test_performance.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/convnet_mnist/tt/convnet_mnist.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/distilbert/demo/demo.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/distilbert/distilbert_utils.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/distilbert/tests/test_perf_distilbert.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0
 

models/demos/distilbert/tt/ttnn_optimized_distilbert.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: © 2023 Tenstorrent Inc.
+# SPDX-FileCopyrightText: © 2024 Tenstorrent Inc.
 
 # SPDX-License-Identifier: Apache-2.0