Adding all project files

venv/Lib/site-packages/torch/ao/nn/qat/dynamic/__init__.py

@@ -0,0 +1 @@
+from .modules import *  # noqa: F403

venv/Lib/site-packages/torch/ao/nn/qat/dynamic/modules/__init__.py

@@ -0,0 +1,4 @@
+from .linear import Linear
+
+
+__all__ = ["Linear"]

venv/Lib/site-packages/torch/ao/nn/qat/dynamic/modules/linear.py

@@ -0,0 +1,40 @@
+from typing import Optional, TYPE_CHECKING, Union
+
+import torch
+
+
+if TYPE_CHECKING:
+    from torch.ao.quantization.qconfig import QConfig  # noqa: TC004
+
+
+__all__ = ["Linear"]
+
+
+class Linear(torch.ao.nn.qat.Linear):
+    r"""
+    A linear module attached with FakeQuantize modules for weight,
+    used for dynamic quantization aware training.
+
+    We adopt the same interface as `torch.nn.Linear`, please see
+    https://pytorch.org/docs/stable/nn.html#torch.nn.Linear
+    for documentation.
+
+    Similar to `torch.nn.Linear`, with FakeQuantize modules initialized to
+    default.
+    """
+
+    def __init__(
+        self,
+        in_features: int,
+        out_features: int,
+        bias: bool = True,
+        qconfig: Optional["QConfig"] = None,
+        device: Optional[Union[int, str, torch.device]] = None,
+        dtype: Optional[str] = None,
+    ) -> None:
+        super().__init__(in_features, out_features, bias, qconfig, device, dtype)
+        if not torch.ao.quantization.qconfig._activation_is_memoryless(qconfig):  # type: ignore[arg-type]
+            raise ValueError(
+                "Dynamic QAT requires a memoryless observer."
+                + "This means a MovingAverage observer with averaging constant equal to 1"
+            )