switching to high quality piper tts and added label translations

2026-01-29 23:48:19 +01:00
commit d80c619df9
3934 changed files with 1451600 additions and 0 deletions
@@ -0,0 +1,163 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import datetime
+import json
+
+import pandas as pd
+
+
+class BaseObject:
+    def __init__(self):
+        self.customized = {}
+
+    def to_dict(self):
+        default_values = self.__dict__.copy()
+        default_values.pop("customized", None)
+        default_values.update(self.customized)
+
+        for k, v in default_values.items():
+            if isinstance(v, BaseObject):
+                default_values[k] = v.to_dict()
+
+        return {k: v for k, v in default_values.items() if v}
+
+
+class ModelInfo(BaseObject):
+    def __init__(
+        self,
+        full_name: str | None = None,
+        is_huggingface: bool | None = False,
+        is_text_generation: bool | None = False,
+        short_name: str | None = None,
+    ):
+        super().__init__()
+        self.full_name = full_name
+        self.is_huggingface = is_huggingface
+        self.is_text_generation = is_text_generation
+        self.short_name = short_name
+        self.input_shape = []
+
+
+class BackendOptions(BaseObject):
+    def __init__(
+        self,
+        enable_profiling: bool | None = False,
+        execution_provider: str | None = None,
+        use_io_binding: bool | None = False,
+    ):
+        super().__init__()
+        self.enable_profiling = enable_profiling
+        self.execution_provider = execution_provider
+        self.use_io_binding = use_io_binding
+
+
+class Config(BaseObject):
+    def __init__(
+        self,
+        backend: str | None = "onnxruntime",
+        batch_size: int | None = 1,
+        seq_length: int | None = 0,
+        precision: str | None = "fp32",
+        warmup_runs: int | None = 1,
+        measured_runs: int | None = 10,
+    ):
+        super().__init__()
+        self.backend = backend
+        self.batch_size = batch_size
+        self.seq_length = seq_length
+        self.precision = precision
+        self.warmup_runs = warmup_runs
+        self.measured_runs = measured_runs
+        self.model_info = ModelInfo()
+        self.backend_options = BackendOptions()
+
+
+class Metadata(BaseObject):
+    def __init__(
+        self,
+        device: str | None = None,
+        package_name: str | None = None,
+        package_version: str | None = None,
+        platform: str | None = None,
+        python_version: str | None = None,
+    ):
+        super().__init__()
+        self.device = device
+        self.package_name = package_name
+        self.package_version = package_version
+        self.platform = platform
+        self.python_version = python_version
+
+
+class Metrics(BaseObject):
+    def __init__(
+        self,
+        latency_ms_mean: float | None = 0.0,
+        throughput_qps: float | None = 0.0,
+        max_memory_usage_GB: float | None = 0.0,
+    ):
+        super().__init__()
+        self.latency_ms_mean = latency_ms_mean
+        self.throughput_qps = throughput_qps
+        self.max_memory_usage_GB = max_memory_usage_GB
+
+
+class BenchmarkRecord:
+    def __init__(
+        self,
+        model_name: str,
+        precision: str,
+        backend: str,
+        device: str,
+        package_name: str,
+        package_version: str,
+        batch_size: int | None = 1,
+        warmup_runs: int | None = 1,
+        measured_runs: int | None = 10,
+        trigger_date: str | None = None,
+    ):
+        self.config = Config()
+        self.metrics = Metrics()
+        self.metadata = Metadata()
+        self.trigger_date = trigger_date or datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+
+        self.config.model_info.full_name = model_name
+        self.config.precision = precision
+        self.config.backend = backend
+        self.config.batch_size = batch_size
+        self.config.warmup_runs = warmup_runs
+        self.config.measured_runs = measured_runs
+        self.metadata.device = device
+        self.metadata.package_name = package_name
+        self.metadata.package_version = package_version
+
+    def to_dict(self) -> dict:
+        return {
+            "config": self.config.to_dict(),
+            "metadata": self.metadata.to_dict(),
+            "metrics": self.metrics.to_dict(),
+            "trigger_date": self.trigger_date,
+        }
+
+    def to_json(self) -> str:
+        return json.dumps(self.to_dict(), default=str)
+
+    @classmethod
+    def save_as_csv(cls, file_name: str, records: list) -> None:
+        if records is None or len(records) == 0:
+            return
+        rds = [record.to_dict() for record in records]
+        df = pd.json_normalize(rds)
+        df.to_csv(file_name, index=False)
+
+    @classmethod
+    def save_as_json(cls, file_name: str, records: list) -> None:
+        if records is None or len(records) == 0:
+            return
+        rds = [record.to_dict() for record in records]
+        with open(file_name, "w") as f:
+            json.dump(rds, f, indent=4, default=str)