🚀 feat(model): Enable Patchcore Training Half Precision (#3031)

patchcore infer dtype from model dtype

Co-authored-by: Rajesh Gangireddy <rajesh.gangireddy@intel.com>

Author: alexriedel1

src/anomalib/models/components/dimensionality_reduction/random_projection.py

@@ -193,4 +193,4 @@ def transform(self, embedding: torch.Tensor) -> torch.Tensor:
             msg = "`fit()` has not been called on SparseRandomProjection yet."
             raise NotFittedError(msg)
 
-        return embedding @ self.sparse_random_matrix.T.float()
+        return embedding @ self.sparse_random_matrix.T.type(embedding.dtype)

src/anomalib/models/image/patchcore/torch_model.py

@@ -153,6 +153,7 @@ def forward(self, input_tensor: torch.Tensor) -> torch.Tensor | InferenceBatch:
             ... else:
             ...     assert isinstance(output, InferenceBatch)
         """
+        input_tensor = input_tensor.type(self.memory_bank.dtype)
         output_size = input_tensor.shape[-2:]
         if self.tiler:
             input_tensor = self.tiler.tile(input_tensor)